DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Amendment
Claims 1, 7, 9, 15, and 17 are amended, claim 8 is cancelled, and claim 21 is new. Claims 1-7 and 9-21 are pending.
Response to Arguments
Applicant's arguments filed 2/18/2026 have been fully considered.
Regarding the objection to claim 3, and as noted by Applicant on page 8 of the response, the amendment to claim 1 overcomes the objection, which is withdrawn.
Regarding the rejections of independent claims 1, 9, and 17 under 101, Examiner respectfully disagrees with Applicant’s arguments on pages 8-12 for the following reasons.
On pages 8-9 of the response, Applicant contends that the steps of claim 9 are not directed to a mental process. Specifically, Applicant contends on page 9 that the steps including “update an atmospheric delay model … by executing one or more reconfiguration actions” and “effectuate, by the service provider, transmission of updated atmospheric delay correction data …” cannot be performed via mental processes. In support, Applicant cites paragraphs [0008], [0030]-[0032], [0037], [0043]-[0045], and [0059] as explaining the claimed functions and confirming that the claims recite machine-implemented control and transmission activity rather than mental activity.
Examiner acknowledges that claim 9 does not recite steps that are actually implemented as mental processes. Instead, claim 9 expressly recites that the steps are implemented using computer processing code and circuitry. Examiner submits, however, that the analysis under Step 2A, Prong One considers whether the steps could be performed via mental processes or mathematical concepts and therefore constitute an abstract idea, even if the claimed implementation is via computer processing.
In accordance with a broadest reasonable interpretation in view of Applicant’s specification in which a correction model may entail a methodology which may be conceived, formulated, and applied via mental processes, updating an atmospheric delay correction model by executing one or more reconfiguration actions may also be performed via mental processes (e.g., determine updates/reconfiguration that may be required such as determining a new setting for updating the frequency/rate of correction).
The current grounds of rejection acknowledge that “effectuate, by the service provider, transmission of updated atmospheric delay correction data …” falls outside the mental processes exception. As noted in the current grounds of rejection, a broadest reasonable interpretation in view of Applicant’s specification, of “effectuating, by the service provider, transmission of updated atmospheric delay correction data generated using the updated atmospheric delay correction model to one or more requesting devices,” entails activity following a decision to perform the transmission, such as sending a signal to perform such output transmission activity or the transmission activity itself, which has no particularized functional relation to the steps falling within the judicial exception (i.e., steps determining what the result to be outputted will be), and therefore constitutes extra solution activity that neither integrates the judicial exception into a practical application nor results in the claim as a whole amounting to significantly more than the judicial exception.
On pages 9-10 of the response in regard to the prediction modeling element, Applicant contends that even if some modeling uses mathematics, the claim is not directed to mathematics itself, and instead applied such modeling within a specific service-side control loop for detecting atmospheric abnormalities by comparing prediction modeling data with observation data for a particular geography, updating the delay correction model by executing reconfiguration actions, and effectuating transmission of updated atmospheric delay correction data to devices for improved real-world positioning during abnormal atmospheric activity. On page 10, Applicant cites these functions as supporting Applicant’s contention that the claims do not seek to preempt mathematical relations, but instead use modeling as an input to drive concrete system reconfiguration and broadcast/transmission in a technological application that is beyond mathematics.
The foregoing arguments do not appear to explain with any specificity, why the categorization of the prediction modeling element does not properly fall within a judicial exception and instead appear to be directed to Step 2A, Prong 2 (i.e., whether the claim as a whole includes additional elements that integrate the recited judicial exception into a practical application. Regarding Step 2A Prong one, Examiner submits that the element in question - “generate” “prediction modeling data, wherein the prediction modeling data comprises one or more atmospheric activity predictions, and wherein the prediction modeling data is generated based at least in part on one or more atmospheric activity models associated with the atmospheric abnormality mitigation system” – falls within the mental processes category because generating the prediction modeling data “based on” “atmospheric activity models” may be performed via mental processes (e.g., evaluation of atmospheric activity model output and judgment in determining corresponding “prediction modeling data.” The use of “atmospheric activity models” to provide the information upon which the prediction model data is generated falls within the mathematical concepts judicial exception because as disclosed in Applicant’s specification (e.g., paragraphs [0033] and [0060] the atmospheric activity prediction modeling may be implemented by modeling techniques such as Klobuchar, NeQuick, and Quasi-Zenith Satellite System (QZSS), which are fundamentally characterized by mathematical calculations/relations and therefore constitutes mathematical relationships.
Regarding Step 2A Prong 2 aspect of Applicant’s argument, Examiner further submits that the sequence of processing steps do not include additional elements that result in the claim as a whole integrating the abstract idea into a practical application. Instead, the “specific server-side loop” alluded to by Applicant appears to comprise a computer system for executing basic computer functions (processing and outputting of results) for implementing the judicial exception.
Further regarding Step 2A Prong 2, Applicant contends on page 11 of the response that the claims, evaluated as a whole, integrate any arguable abstract idea into a concrete, technological application. More specifically, Applicant asserts that “update an atmospheric delay correction model associated with a service provider, based on detected atmospheric abnormalities,” and “effectuating, by the service provider, transmission of updated atmospheric delay correction data to one or more requesting devices,” are not generic computer functions and instead represent a specific improvement to a technical field of adaptive GNSS atmospheric-delay correction during abnormal atmospheric activity, including solar/ionospheric disturbances. In support on page 12 of the response, Applicant notes that Applicant’s specification explains the negative effect that abnormal atmospheric activity has on positional activity, and that the “application” provides a technical solution by reconfiguring the atmospheric delay correction model and deploying updated corrections to improve device performance. Applicant further cites portions of the specification describing various ways in which such adaptive correction may be implemented and further describing intended benefits of such adaptive correction.
Regarding the model update step cited by Applicant, Examiner submits that this element represents a highly generalized characterization of how a methodology to determine corrections may be updated that falls within the mental processes exception with its main functional relation being to the preceding “comparing” step, which may also be performed via mental processes. Examiner acknowledges that the effectuation of adapting the manner of correction (i.e., updating the model) based on comparing predicted atmospheric conditions with observed atmospheric conditions may have real-world utility. However, viewing the elements of the claim in combination, Examiner submits that such utility is largely confined to the comparing and modeling update steps that fall within the judicial exception without any technologically significant coordinated contribution by “additional elements” falling outside the exception, such that no discernable improvement to a technology or technical field can be ascertained such as described in MPEP 2106.05 (a).
Regarding the transmission effectuation step, Examiner submits that this element plays no significant role that contributes to an improvement to a technical field because it merely represents outputting results obtained as a result of the comparing and model update steps.
In sum, regarding Step 2A Prong 2, Examiner submits that claim 9 (and similarly for independent claims 1 and 17) is directed to an abstract idea because the claim does not appear to include any combination of elements that results in the judicial exception being integrated into a practical application. For example, considering the factors set forth in MPEP 2106.05(b), the technology recited in claim 9 is characterized very generally such that a “field-of-use” is only evident in terms of labelling the application “atmospheric abnormality mitigation system” and reciting otherwise ordinary computer processing components/function that merely link the processing steps to a technical field application. Instead, the functional steps are implemented by a generic computer processing system as a tool to implement the mathematical and/or mental process steps (see MPEP 2106.05(f)), such that the additional elements are insufficient in combination with the math/mental steps to prevent preemption of the abstract idea over a broad array of plausible applications.
Regarding Step 2B, Applicant contends on page 12 of the response that amended claim 9 recites significantly more that any alleged abstract idea by specifying a service-side control flow that produces and transmits updated atmospheric corrections used in GNSS positioning, not merely data analysis on a generic computer. In support, Applicant asserts that the references cited in the Step 2B analysis portion of the 101 rejections confirm Applicant’s contention that the claims recite an improvement to a technical field in terms of entailing a concrete, machine-implemented operation.
Examiner submits that as explained with respect to the Step 2A Prong 2 analysis, claim 9 does not appear to entail an improvement to a technical field, instead applying generalized computer processing functions to process and output atmospheric condition and correction results in a manner in which a technical improvement is not discernable. Examiner further submits that the generalized and ordinary manner of implementation of the “control flow” is affirmed by the disclosures of the cited references such that no particular technical improvement is evident from the elements of the independent claims.
Regarding the rejections of claims 1-2, 9-10, and 17-18 under 102, and the rejections of dependent claims 4, 12, and 20 under 103, Examiner respectfully disagrees with Applicant’s arguments on pages 13-15 for the following reasons.
On page 13 of the response, Applicant contends that Rikoski’s disclosure of updates to a model and result position error in [0049] do not constitute the reconfiguration “action” as required in claim 1. In support, Applicant asserts that Rikoski’s updated model is a climate/weather model used for forecasting with the transmitted article being device position-error values, such that updating the forecast model state and outputting position error values is not the same as reconfiguring a service-provider atmospheric delay correction model to generate device-consumable atmospheric delay corrections and broadcasting those corrections.
Examiner notes that Applicant’s argument combines features added by amendment (“effectuating … transmission of updated atmospheric delay correction data …”) to the question of whether Rikoski teaches the model reconfiguration action. Regarding the reconfiguring, Rikoski teaches such reconfiguring in terms of updating an atmospheric delay correction model ([0008] update atmospheric model(s) that per [0006] are used for propagation correction (therefore are part of overall “correction model”; FIGS. 1 and 5 models 106 are included and utilized in overall correction system 100; [0019] data from models used for updates (corrections) of position data; [0036] and [0043] climate model implemented as part of overall correction method/model) associated with the service provider (FIGS. 1 and 5 models 106 are included and utilized on overall correction system 100), wherein updating the atmospheric delay correction model comprises executing one or more reconfiguration actions (FIG. 5 climate/weather models 106 configured to be reconfigured with data from GPS-enabled devices/data relevant to client model; [0049] update both the climate model (part of overall correction model) and the GPS position error estimate. Examiner notes that each of these updates constitutes a reconfiguration because they represent a change in the model and the resultant position error from previous iterations of the model).
Examiner notes that as set forth above (and similarly in the current grounds of rejection), Rikoski clearly teaches a reconfiguration (update) of the forecast models that are included as part of an overall atmospheric delay correction model, such that the delay correction model is thereby updated/reconfigured.
On pages 13-14 of the response, Applicant contends that “treating routine model-state updates in a climate model disclosed by Rikoski as the claimed ‘reconfiguration actions’ of a service-provider atmospheric correction model is an overbroad interpretation inconsistent with the claim language and Applicant’s specification.” In support, Applicant cites examples of “reconfiguration actions” disclosed in Applicant’s specification and concludes that “[t]his numerical update to a model state disclosed in Rikoski is different from deployment reconfiguration as recited in claim 1.”
Examiner submits that while the examples provided in Applicant’s specification of what may constitute a reconfiguration action are significant in terms of what may constitute a reconfiguration action, they do not appear to exclude Rikoski’s disclosed model update as being a possible alternative. On the contrary, the significant qualitative differences in the forms/types of possible examples of what may constitute a reconfiguration cited in Applicant’s specification infers that the reconfiguration may entail a broad array of modeling modifications.
As a point aside from Applicant’s particular arguments but potentially relevant to the clarity of the updating/reconfiguring step in relation to the overall claim language, the Examiner notes that while arguably inferred, the current claim language does not directly require that the determined “atmospheric abnormality” be utilized in performing the update/reconfigure step.
Regarding the rejections of claims 2, 10, and 18 under 102, Applicant contends on page 14 that Rikoski’s disclosure of voxels that discretize an atmospheric volume do not teach that the particularized geographical area is associated with one or more correction grids. In support, Applicant asserts that “[t]he voxels are not a service-provider correction grid used to deploy atmospheric corrections to devices, for are they reconfigured and transmitted as deployment artifacts.”
Applicant’s argument in this regard goes beyond the claim language. As set forth in the grounds of rejection Rikoski teaches that the particular geographical area (e.g., area proximate a GPS-enabled device as depicted in FIG. 6) is associated with one or more correction grids (FIG. 6 depicting grid comprising voxels 602 associated with atmospheric volume between satellite and GPS-enabled device 104 (therefore associated with geographic area proximate to the GPS-enabled device)) related to the atmospheric delay correction model ([0036]-[0043] describing the position-related parameters related to the grid depicted in FIG. 6 used to update/correct model parameters).
On page 14 of the response, Applicant points out that “area” is a two-dimensional geographic association for correction grids, whereas Rikoski’s voxels are three-dimensional partitions of atmospheric volume for model estimation.
Examiner acknowledges that an “area” is two-dimensional but notes that a volume entails “areas” with the addition of a third, depth dimension. Furthermore, and more to the point, Examiner notes that the dimensionality of the “correction grids” is not specified by the claim and that the grounds of rejection cite the geographic area as entailing an area proximate the GPS-enabled device (e.g., a plane within the depicted voxelized region depicted in FIG. 6 between the GPS-enabled device and the satellite) that inherently corresponds to some geographic area.
Regarding the rejections of claims 4, 12, and 20 under 103, Applicant contends that Limberger’s disclosed interpolation between grid points does not teach “modifying a grid layout” because modifying the grid layout is a “deployment level change” not merely a change to grid values. In support, Applicant cites examples from Applicant’s specification in which such modification is described as entailing a reconfiguration.
Examiner submits that Applicant’s arguments provide no basis for excluding interpolation between points in a grid from a broadest reasonable interpretation of “modifying the grid layout.” The grid layout may entail any of a variety of aspects of the grid including values included at points constituting the grid and determining additional points, such as via interpolation, appears to fall within a broadest reasonable interpretation of modifying a grid layout.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-7 and 9-21 are rejected under 35 U.S.C. 101 because the claimed invention in each of these claims is directed to the abstract idea judicial exception without significantly more.
Independent claim 9, substantially representative also of independent claims 1 and 17, recites:
“[a]n apparatus comprising processing circuitry and at least one memory including computer program code, the at least one memory and the computer program code configured to, with the processing circuitry, cause the apparatus at least to:
generate, by an atmospheric abnormality mitigation system related to a service provider, prediction modeling data, wherein the prediction modeling data comprises one or more atmospheric activity predictions, and wherein the prediction modeling data is generated based at least in part on one or more atmospheric activity models associated with the atmospheric abnormality mitigation system;
receive observation data, wherein the observation data comprises data related to current atmospheric activity associated with a particular geographical area;
compare the prediction modeling data and the observation data;
determine, based in part on results of comparing the prediction modeling data and the observation data, that an atmospheric abnormality is adversely affecting one or more navigational signals associated with the particular geographical area;
update an atmospheric delay correction model associated with the service provider, wherein the atmospheric delay correction model is updated by executing one or more reconfiguration actions; and
effectuate, by the service provider, transmission of updated atmospheric delay correction data generated using the updated atmospheric delay correction model to one or more requesting devices.”
The claim limitations considered to fall within in the abstract idea are highlighted in bold font above and the remaining features are “additional elements.”
Step 1 of the subject matter eligibility analysis entails determining whether the claimed subject matter falls within one of the four statutory categories of patentable subject matter identified by 35 U.S.C. 101: process, machine, manufacture, or composition of matter. Claims 9 and 17 each recite an apparatus and claim 1 recites a method and each therefore falls within a statutory category.
Step 2A, Prong One of the analysis entails determining whether the claim recites a judicial exception such as an abstract idea. Under a broadest reasonable interpretation, the highlighted portions of claim 9 fall within the abstract idea judicial exception. Specifically, under the 2019 Revised Patent Subject matter Eligibility Guidance, the highlighted subject matter falls within the mental processes category (including an observation, evaluation, judgment, opinion) and the mathematical concepts category (mathematical relationships, mathematical formulas or equations, mathematical calculations). MPEP § 2106.04(a)(2).
The recited functions:
“generate” “prediction modeling data, wherein the prediction modeling data comprises one or more atmospheric activity predictions”
“receive observation data, wherein the observation data comprises data related to current atmospheric activity associated with a particular geographical area;
compare the prediction modeling data and the observation data;
determine, based in part on results of comparing the prediction modeling data and the observation data, that an atmospheric abnormality is adversely affecting one or more navigational signals associated with the particular geographical area; and
update an atmospheric delay correction model associated with the service provider, wherein the atmospheric delay correction model is updated by executing one or more reconfiguration actions,”
may be performed, individually or in combination, as mental processes.
Generating prediction modeling data that comprises one or more atmospheric activity predictions may be performed via mental processes (e.g., evaluation of information related to atmospheric activity and judgement in determining prediction of values such as estimation of what values should be). Receiving observation data, wherein the observation data comprises data related to current atmospheric activity associated with a particular geographical area may be performed via mental processes (e.g., observation of observation data displayed on a computer). Comparing prediction modeling data and observation data may be performed via mental processes (e.g., evaluation and judgement relating to similarities/differences between prediction modeling data and observation data). Determining, based in part on results of comparing the prediction modeling data and the observation data, that an atmospheric abnormality is adversely affecting one or more navigational signals associated with the particular geographical area may be performed via mental processes (e.g., evaluation of the comparison information and judgement in determining resultant characterization as indicating an atmospheric abnormality that under the circumstances would affect navigation signals). In accordance with a broadest reasonable interpretation in view of Applicant’s specification in which a correction model may entail a methodology, updating an atmospheric delay correction model by executing one or more reconfiguration actions may also be performed via mental processes (e.g., determine updates/reconfiguration that may be required such as determining a new setting for updating the frequency/rate of correction).
The recited function “generate” “prediction modeling data, wherein the prediction modeling data comprises one or more atmospheric activity predictions, and wherein the prediction modeling data is generated based at least in part on one or more atmospheric activity models associated with the atmospheric abnormality mitigation system” is further determined by the Examiner as falling within the mathematical relationships sub-category of mathematical concepts (MPEP 2106.04(a)(2)) because as disclosed in Applicant’s specification (e.g., paragraphs [0033] and [0060] the atmospheric activity prediction modeling may be implemented by modeling techniques such as Klobuchar, NeQuick, and Quasi-Zenith Satellite System (QZSS), which are fundamentally characterized by mathematical calculations/relations and therefore constitutes mathematical relationships.
Step 2A, Prong Two of the analysis entails determining whether the claim includes additional elements that integrate the recited judicial exception into a practical application. “A claim that integrates a judicial exception into a practical application will apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception, such that the claim is more than a drafting effort designed to monopolize the judicial exception” (MPEP § 2106.04(d)).
MPEP § 2106.04(d) sets forth considerations to be applied in Step 2A, Prong Two for determining whether or not a claim integrates a judicial exception into a practical application. Based on the individual and collective limitations of claim 9 and applying a broadest reasonable interpretation, the most applicable of such considerations appear to include: improvements to the functioning of a computer, or to any other technology or technical field (MPEP 2106.05(a)); applying the judicial exception with, or by use of, a particular machine (MPEP 2106.05(b)); and effecting a transformation or reduction of a particular article to a different state or thing (MPEP 2106.05(c)).
Regarding improvements to the functioning of a computer or other technology, none of the “additional elements” including “processing circuitry and at least one memory including computer program code, the at least one memory and the computer program code configured to, with the processing circuitry, cause the apparatus at least to” perform the recited functions, generating prediction modeling data “by an atmospheric abnormality mitigation system related to a service provider,” and “effectuate, by the service provider, transmission of updated atmospheric delay correction data generated using the updated atmospheric delay correction model to one or more requesting devices” in any combination appear to integrate the abstract idea in a manner that technologically improves any aspect of a device or system that may be used to implement the highlighted steps or a device for implementing the highlighted steps such as a signal processing device or a generic computer. Instead, processing circuitry and memory for performing the functions represents use of computer processing means for merely implementing, in no particularized functional manner, the underlying functions that fall within the judicial exception and therefore constitutes insignificant extra solution activity that fails to integrate the judicial exception into a practical application. Using an atmospheric abnormality mitigation system related to a service provider represents a high-level processing environment environment/context that does not significantly characterize the manner or means of the processing mechanism itself and therefore constitutes insignificant extra solution activity. A broadest reasonable interpretation in view of Applicant’s specification, of “effectuating, by the service provider, transmission of updated atmospheric delay correction data generated using the updated atmospheric delay correction model to one or more requesting devices,” entail post-decision activity, such as sending a signal to perform such output transmission activity, which has no particularized functional relation to the steps falling within the judicial exception (i.e., steps determine what the result to be outputted will be), and therefore also constitutes extra solution activity that fails to integrate the judicial exception into a practical application.
Regarding application of the judicial exception with, or by use of, a particular machine, the additional elements are configured and implemented in non-particularized manner of implementing atmospheric condition monitoring for delay correction.
Regarding a transformation or reduction of a particular article to a different state or thing, claim 9 does not include any such transformation or reduction. Instead, claim 9 as a whole entails generating and receiving input information (e.g., generated prediction modeling data and received observation data), applying standard computer processing techniques to the information to determine atmospheric activity condition and differentiation information with the additional elements failing to provide a meaningful integration of the abstract idea (comparing current, location-specific atmospheric activity data with prediction modeling data and determining correction model/method changes accordingly) in an application that transforms an article to a different state. Instead, the additional elements represent extra-solution activity that does not integrate the judicial exception into a practical application. In view of the various considerations encompassed by the Step 2A, Prong Two analysis, claim 9 does not include additional elements that integrate the recited abstract idea into a practical application.
The Examiner notes that even if “wherein the prediction modeling data is generated based at least in part on one or more atmospheric activity models associated with the atmospheric abnormality mitigation system” is interpreted to fall outside the mathematical concepts exception, this element represents high-level computer-based implementation (modeling entailing computer program/instruction implementation) of the underlying function that falls within the mental processes judicial exception. Therefore, the use of “atmospheric activity models” constitutes insignificant extra solution activity that fails to integrate the judicial exception into a practical application.
Therefore, claim 9 is directed to a judicial exception and requires further analysis under Step 2B.
Regarding Step 2B, and as explained in the Step 2A Prong Two analysis, the additional elements in claim 9 constitute insignificant extra solution activity and therefore, in addition to failing to integrate the judicial exception into a practical application, also fail to result in the claim as a whole amounting to significantly more than the judicial exception. Furthermore, the additional elements appear to be generic and well understood as evidenced by the disclosures of Rikoski (US 2013/0325425 A1) and Limberger (US 2021/0149060 A1), each of which teach substantially the same computer-implemented platform for performing atmospheric activity modeling/prediction and delay correction modeling/updating.
As explained in the grounds for rejecting claim 9 under 102, Rikoski teaches “processing circuitry and at least one memory including computer program code, the at least one memory and the computer program code configured to, with the processing circuitry, cause the apparatus at least to” perform the recited functions, generating prediction modeling data “by an atmospheric abnormality mitigation system related to a service provider,” and “effectuate, by the service provider, transmission of updated atmospheric delay correction data generated using the updated atmospheric delay correction model to one or more requesting devices” as does Limberger (see FIG. 2 satellite navigation system 200 including apparatus 210 that performs error correction; [0017] and [0020] computer program implementation of method; Abstract correction data transmitted to the satellite and then transmitted from the satellite (to end-user devices such as correction data 275 transmitted to receivers 230 in FIG. 2) ).
Therefore, the additional elements are insufficient to amount to significantly more than the judicial exception.
Independent claim 9 is therefore not patent eligible under 101.
Independent claims 1 and 17 include substantially the same elements falling within the judicial exception as claim 9 and include no significant additional elements that either integrate the judicial exception into a practical application or result in the claim as a whole amounting to significantly more than the judicial exception.
Claims 1 and 17 therefore are also not patent eligible under 101.
Claims 2-7 depending from claim 1, claims 10-16 and 21 depending from claim 9, and claims 18-20 depending from claim 17 provide additional features/steps which are part of an expanded algorithm that includes the abstract idea of the respective independent claim (Step 2A, Prong One). None of dependent claims 2-7, 10-16, and 18-20 recite additional elements that integrate the abstract idea into practical application (Step 2A, Prong Two), and all fail the “significantly more” test under the step 2B for substantially similar reasons as discussed with regards to the independent claims.
For example, claim 2, substantially representative also of claims 10 and 18, further characterizes the “geographic area” as being associated with data structures in the form of “correction grids” having a “grid layout comprising one or more respective data points,” which represents various data structures that do not constitute additional element functions (steps that fall outside the judicial exception).
Claim 3, substantially representative also of claims 11 and 19, further recites “updating a correction data update rate defined by the atmospheric delay correction model, wherein the correction data update rate is a rate at which correction data is transmitted to the one or more requesting devices, and wherein the correction is generated to mitigate atmospheric delay impacting the one or more navigational signals related to the one or more correction grids” which falls within the mental processes judicial exception because updating a correction data update rate may be performed via mental processes (e.g., evaluation of information related to atmospheric conditions and judgement to determine a modification to an update rate). The Examiner notes that even if this element is interpreted more narrowly (e.g., requiring an implementation of an updated correction data update rate) such as to exclude mental processes, this element would represent insignificant extra solution activity at least in part because the reconfiguration generally as recited in claim 1 is not functionally related to the steps falling within the judicial exception.
Claim 4, substantially representative also of claims 12 and 20, further recites “modifying the grid layout associated with a respective correction grid of the one or more correction grids,” which falls within the mental processes judicial exception because it can be performed via mental processes (e.g., evaluation of information related to atmospheric conditions and judgement to determine modifications to the grid layout). The Examiner notes that even if this element is interpreted more narrowly (e.g., requiring modification of stored data structure) such as to exclude mental processes, this element would represent insignificant extra solution activity at least in part because the reconfiguration generally as recited in claim 1 is not functionally related to the steps falling within the judicial exception.
Claim 5, substantially representative also of claim 13, further recites “modifying one or more operational parameters of the atmospheric delay correction model,” which falls within the mental processes judicial exception because it can be performed via mental processes (e.g., evaluation of information related to atmospheric conditions and judgement to determine modifications to operational parameters). The Examiner notes that even if this element is interpreted more narrowly (e.g., requiring modification of stored data structure) such as to exclude mental processes, this element would represent insignificant extra solution activity at least in part because the reconfiguration generally as recited in claim 1 is not functionally related to the steps falling within the judicial exception.
Claim 6, substantially representative also of claim 14, further recites “wherein the one or more reconfiguration actions are generated based in part on a severity level associated with the atmospheric abnormality,” which falls within the mental processes judicial exception because it can be performed via mental processes (e.g., evaluation of severity level of atmospheric abnormality and judgement in determining response thereto to (or how to) implement reconfiguration actions).
Claim 7, substantially representative also of claim 15, further recites “in response to determining that an atmospheric abnormality is adversely affecting the one or more navigational signals associated with the particular geographical area,” which falls within the mental processes exception because formulating a response to a determined atmospheric abnormality may be performed via mental processes. Claim 7 further recites “generating one or more warning indicators associated with the atmospheric abnormality; and transmitting the one or more warning indicators to one or more requesting devices associated with the service provider,” which represent routine, conventional data processing activities (outputting and transmitting warning data) having no significant functional relation to the elements falling within the judicial exception and therefore constitute insignificant post-solution activity that neither integrates the judicial exception into a practical application nor results in the claim as a whole amounting to significantly more than the judicial exception.
Claim 16, further recites that one or more machine learning models may be included in the mitigation system and configured to generate the prediction modeling data, which represents computer instruction (via modeling) implementation (via routing, conventional programming in the form of machine learning) of the element falling within the judicial exception and therefore constitutes extra solution activity that neither integrates the judicial exception into a practical application nor results in the claim as a whole amounting to significantly more than the judicial exception.
Claim 21 further recites “wherein determining the atmospheric abnormality comprises detecting a deviation exceeding a threshold between the prediction modeling data and the observation data for the particular geographical area,” which falls within the mental processes judicial exception because it may be performed via mental processes (e.g., evaluation and judgment).
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1-2, 5-6, 9-10, 13-14, 17-18 and 21 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Rikoski (US 2013/0325425 A1).
As to claim 1, Rikoski teaches “[a] computer-implemented method (method depicted in FIG. 7 implemented by computer system such as depicted in FIG. 2) comprising:
generating, by an atmospheric abnormality mitigation system (FIGS. 1 and 5 atmospheric modeling and GPS correction system 100) related to a service provider (portions of system 100 such as networked access to climate/weather modeling and operation of central processor 101 implement services that are inherently provided), prediction modeling data, wherein the prediction modeling data comprises one or more atmospheric activity predictions (FIG. 5 climate/weather models 106 configured to generate climate model data, [0032]-[0033] climate/weather models predict (estimate what the weather/climate should be) atmospheric activity; FIG. 7 blocks 702 and 704, [0047]), and wherein the prediction modeling data is generated based at least in part on one or more atmospheric activity models associated with the atmospheric abnormality mitigation system (FIG. 5 climate/weather models 106 included in overall system 100);
receiving observation data (FIGS. 1 and 5 central processor 101 configured to receive data from GPS-enabled devices 104, [0019], [0035] device 104 sends information determined/observed by the device; [0036] central processor receives and uses the received data; [0048]), wherein the observation data comprises data related to current atmospheric activity associated with a particular geographical area (FIG. 5 information from GPS-enabled device includes position, time, and errors (errors associated with a time and position); [0027] “errors” may be due to delays caused by atmospheric conditions; [0029] delay errors are corrected for in accordance with variations (indicates temporal change) “at” each GPS-enabled device; [0032] modelling process uses numerical prediction and current surface weather observations; [0019] and [0029] data from GPS-enabled devices used to update the modeled output (data from GPS-enabled devices is substantially current at least with respect to previous modeling iteration); [0048]);
comparing the prediction modeling data and the observation data ([0048] calculate error by comparing values derived from the climate model with values obtained from the GPS-enabled devices);
determining, based in part on results of comparing the prediction modeling data and the observation data, that an atmospheric abnormality is adversely affecting one or more navigational signals associated with the particular geographical area ([0048] calculate errors in propagation velocities and position values (delay metrics) that per [0027] are caused by atmospheric conditions. Examiner notes that a deviation from modeled/predicted values entails a change from modeled weather/climate expectation and hence falls within a broadest reasonable interpretation of an abnormality, which as explained in [0027] and inferentially disclosed by the error determination in [0048] is effectively a determination that abnormal (not expected) atmospheric conditions are adversely affecting navigation signals);
updating an atmospheric delay correction model ([0008] update atmospheric model(s) that per [0006] are used for propagation correction (therefore are part of overall “correction model”; FIGS. 1 and 5 models 106 are included and utilized on overall correction system 100; [0019] data from models used for updates (corrections) of position data; [0036] and [0043] climate model implemented as part of overall correction method/model) associated with the service provider (FIGS. 1 and 5 models 106 are included and utilized on overall correction system 100), wherein updating the atmospheric delay correction model comprises executing one or more reconfiguration actions (FIG. 5 climate/weather models 106 configured to be reconfigured with data from GPS-enabled devices/data relevant to client model; [0049] update both the climate model (part of overall correction model) and the GPS position error estimate. Examiner notes that each of these updates constitutes a reconfiguration because they represent a change in the model and the resultant position error from previous iterations of the model); and
effectuating, by the service provider, transmission of updated atmospheric delay correction data generated using the updated atmospheric delay correction model to one or more requesting devices ([0006] and [0029] explaining that position error correction performed at the individual GPS devices, which in the context in which information to correct for position errors is routinely processed by (and therefore received by) the GPS-enabled devices, such devices are effectively “requesting” devices; FIG. 5 GPS-enabled device 104 configured to receive GPS Error Correction transmitted by central processor 101 (deployed by service provider) via network 102; [0036] central processor 101 uses modeled estimates to update position error values; [0043] position error value used to correct position values within GPS-enabled devices (requires transmission of correction data); [0049] updated model used to estimate new value for propagation velocity and position and the central processor 101 transmits the position error estimates to each of the GPS-enabled devices).
As to claim 2, Rikoski teaches “[t]he computer-implemented method of claim 1, wherein the particular geographical area is associated with one or more correction grids related to the atmospheric delay correction model (FIG. 6 depicting grid comprising voxels 602 associated with atmospheric volume between satellite and GPS-enabled device 104 (therefore associated with geographic area proximate to the GPS-enabled device); [0036]-[0043] describing the position-related parameters related to the grid depicted in FIG. 6 used to update/correct model parameters), and wherein the one or more correction grids is characterized by a grid layout comprising one or more respective data points (FIG. 6 depicting grid comprising voxels 602 (layout of data points) associated with atmospheric volume between satellite and GPS-enabled device 104).”
As to claim 5, Rikoski teaches “[t]he computer-implemented method of claim 2, wherein the one or more reconfiguration actions comprise modifying one or more operational parameters of the atmospheric delay correction model (FIG. 5 climate/weather models 106 configured to be reconfigured with data from GPS-enabled devices/data relevant to client model (Examiner notes that the data from the GPS-enabled devices is used in/as part of the models that are operative components of the overall correction model and therefore constitute operational parameters; FIG. 7 block 714 model is updated).”
As to claim 6, Rikoski teaches “[t]he computer-implemented method of claim 2, wherein the one or more reconfiguration actions are generated based in part on a severity level associated with the atmospheric abnormality (FIG. 5 climate/weather models 106 configured to be reconfigured with data from GPS-enabled devices/data relevant to client model that per FIG. 7 blocks 706 and 708 include propagation velocities and corresponding errors that will correspond including in magnitude to the observations (in this manner the magnitude/severity of the atmospheric abnormality is entailed within the data used to update the model such that the model reconfiguration is based on a severity level associated with the abnormality).”
As to claim 9, Rikoski teaches “[a]n apparatus (FIG. 5 system 100 that may include computer-based system depicted in FIG. 2) comprising processing circuitry and at least one memory including computer program code, the at least one memory and the computer program code configured to, with the processing circuitry (FIG. 2 computer-based system including processor 202 and memory 204; [0020]-[0024]) , cause the apparatus at least to:
generate, by an atmospheric abnormality mitigation system (FIGS. 1 and 5 atmospheric modeling and GPS correction system 100) related to a service provider (portions of system 100 such as networked access to climate/weather modeling and operation of central processor 101 implement services that are inherently provided), prediction modeling data, wherein the prediction modeling data comprises one or more atmospheric activity predictions (FIG. 5 climate/weather models 106 configured to generate climate model data, [0032]-[0033] climate/weather models predict (estimate what the weather/climate should be) atmospheric activity; FIG. 7 blocks 702 and 704, [0047]), and wherein the prediction modeling data is generated based at least in part on one or more atmospheric activity models associated with the atmospheric abnormality mitigation system (FIG. 5 climate/weather models 106 included in overall system 100);
receive observation data (FIGS. 1 and 5 central processor 101 configured to receive data from GPS-enabled devices 104, [0019], [0035] device 104 sends information determined/observed by the device; [0036] central processor receives and uses the received data; [0048]), wherein the observation data comprises data related to current atmospheric activity associated with a particular geographical area (FIG. 5 information from GPS-enabled device includes position, time, and errors (errors associated with a time and position); [0027] “errors” may be due to delays caused by atmospheric conditions; [0029] delay errors are corrected for in accordance with variations (indicates temporal change) “at” each GPS-enabled device; [0032] modelling process uses numerical prediction and current surface weather observations; [0019] and [0029] data from GPS-enabled devices used to update the modeled output (data from GPS-enabled devices is substantially current at least with respect to previous modeling iteration); [0048]);
compare the prediction modeling data and the observation data ([0048] calculate error by comparing values derived from the climate model with values obtained from the GPS-enabled devices);
determine, based in part on results of comparing the prediction modeling data and the observation data, that an atmospheric abnormality is adversely affecting one or more navigational signals associated with the particular geographical area ([0048] calculate errors in propagation velocities and position values (delay metrics) that per [0027] are caused by atmospheric conditions. Examiner notes that a deviation from modeled/predicted values entails a change from modeled weather/climate expectation and hence falls within a broadest reasonable interpretation of an abnormality, which as explained in [0027] and inferentially disclosed by the error determination in [0048] is effectively a determination that abnormal (not expected) atmospheric conditions are adversely affecting navigation signals);
update an atmospheric delay correction model ([0008] update atmospheric model(s) that per [0006] are used for propagation correction (therefore are part of overall “correction model”; FIGS. 1 and 5 models 106 are included and utilized on overall correction system 100; [0019] data from models used for updates (corrections) of position data; [0036] and [0043] climate model implemented as part of overall correction method/model) associated with the service provider (FIGS. 1 and 5 models 106 are included and utilized on overall correction system 100), wherein the atmospheric delay correction model is updated by executing one or more reconfiguration actions (FIG. 5 climate/weather models 106 configured to be reconfigured with data from GPS-enabled devices/data relevant to client model; [0049] update both the climate model (part of overall correction model) and the GPS position error estimate. Examiner notes that each of these updates constitutes a reconfiguration because they represent a change in the model and the resultant position error from previous iterations of the model); and
effectuate, by the service provider, transmission of updated atmospheric delay correction data generated using the updated atmospheric delay correction model to one or more requesting devices ([0006] and [0029] explaining that position error correction performed at the individual GPS devices, which in the context in which information to correct for position errors is routinely processed by (and therefore received by) the GPS-enabled devices, such devices are effectively “requesting” devices; FIG. 5 GPS-enabled device 104 configured to receive GPS Error Correction transmitted by central processor 101 (deployed by service provider) via network 102; [0036] central processor 101 uses modeled estimates to update position error values; [0043] position error value used to correct position values within GPS-enabled devices (requires transmission of correction data); [0049] updated model used to estimate new value for propagation velocity and position and the central processor 101 transmits the position error estimates to each of the GPS-enabled devices).
As to claim 10, Rikoski teaches “[t]he apparatus of claim 9, wherein the particular geographical area is associated with one or more correction grids related to the atmospheric delay correction model (FIG. 6 depicting grid comprising voxels 602 associated with atmospheric volume between satellite and GPS-enabled device 104 (therefore associated with geographic area proximate to the GPS-enabled device); [0036]-[0043] describing the position-related parameters related to the grid depicted in FIG. 6 used to update/correct model parameters), and wherein the one or more correction grids is characterized by a grid layout comprising one or more respective data points (FIG. 6 depicting grid comprising voxels 602 (layout of data points) associated with atmospheric volume between satellite and GPS-enabled device 104).”
As to claim 13, Rikoski teaches “[t]he apparatus method of claim 10, wherein the one or more reconfiguration actions comprise modifying one or more operational parameters of the atmospheric delay correction model (FIG. 5 climate/weather models 106 configured to be reconfigured with data from GPS-enabled devices/data relevant to client model (Examiner notes that the data from the GPS-enabled devices is used in/as part of the models that are operative components of the overall correction model and therefore constitute operational parameters; FIG. 7 block 714 model is updated).”
As to claim 14, Rikoski teaches “[t]he apparatus of claim 10, wherein the one or more reconfiguration actions are generated based in part on a severity level associated with the atmospheric abnormality (FIG. 5 climate/weather models 106 configured to be reconfigured with data from GPS-enabled devices/data relevant to client model that per FIG. 7 blocks 706 and 708 include propagation velocities and corresponding errors that will correspond including in magnitude to the observations (in this manner the magnitude/severity of the atmospheric abnormality is entailed within the data used to update the model such that the model reconfiguration is based on a severity level associated with the abnormality).”
As to claim 17, Rikoski teaches “[a] computer program product comprising at least one non-transitory computer-readable storage medium having computer-executable program code instructions stored therein, the computer-executable program code instructions comprising program code instructions (FIG. 2 computer-based system including processor 202 and memory 204; [0020]-[0024]) to:
generate, by an atmospheric abnormality mitigation system (FIGS. 1 and 5 atmospheric modeling and GPS correction system 100) related to a service provider (portions of system 100 such as networked access to climate/weather modeling and operation of central processor 101 implement services that are inherently provided), prediction modeling data, wherein the prediction modeling data comprises one or more atmospheric activity predictions (FIG. 5 climate/weather models 106 configured to generate climate model data, [0032]-[0033] climate/weather models predict (estimate what the weather/climate should be) atmospheric activity; FIG. 7 blocks 702 and 704, [0047]), and wherein the prediction modeling data is generated based at least in part on one or more atmospheric activity models associated with the atmospheric abnormality mitigation system (FIG. 5 climate/weather models 106 included in overall system 100);
receive observation data (FIGS. 1 and 5 central processor 101 configured to receive data from GPS-enabled devices 104, [0019], [0035] device 104 sends information determined/observed by the device; [0036] central processor receives and uses the received data; [0048]), wherein the observation data comprises data related to current atmospheric activity associated with a particular geographical area (FIG. 5 information from GPS-enabled device includes position, time, and errors (errors associated with a time and position); [0027] “errors” may be due to delays caused by atmospheric conditions; [0029] delay errors are corrected for in accordance with variations (indicates temporal change) “at” each GPS-enabled device; [0032] modelling process uses numerical prediction and current surface weather observations; [0019] and [0029] data from GPS-enabled devices used to update the modeled output (data from GPS-enabled devices is substantially current at least with respect to previous modeling iteration); [0048]);
compare the prediction modeling data and the observation data ([0048] calculate error by comparing values derived from the climate model with values obtained from the GPS-enabled devices);
determine, based in part on results of comparing the prediction modeling data and the observation data, that an atmospheric abnormality is adversely affecting one or more navigational signals associated with the particular geographical area ([0048] calculate errors in propagation velocities and position values (delay metrics) that per [0027] are caused by atmospheric conditions. Examiner notes that a deviation from modeled/predicted values entails a change from modeled weather/climate expectation and hence falls within a broadest reasonable interpretation of an abnormality, which as explained in [0027] and inferentially disclosed by the error determination in [0048] is effectively a determination that abnormal (not expected) atmospheric conditions are adversely affecting navigation signals);
update an atmospheric delay correction model ([0008] update atmospheric model(s) that per [0006] are used for propagation correction (therefore are part of overall “correction model”; FIGS. 1 and 5 models 106 are included and utilized on overall correction system 100; [0019] data from models used for updates (corrections) of position data; [0036] and [0043] climate model implemented as part of overall correction method/model) associated with the service provider (FIGS. 1 and 5 models 106 are included and utilized on overall correction system 100), wherein the atmospheric delay correction model is updated by executing one or more reconfiguration actions (FIG. 5 climate/weather models 106 configured to be reconfigured with data from GPS-enabled devices/data relevant to client model; [0049] update both the climate model (part of overall correction model) and the GPS position error estimate. Examiner notes that each of these updates constitutes a reconfiguration because they represent a change in the model and the resultant position error from previous iterations of the model); and
effectuate, by the service provider, transmission of updated atmospheric delay correction data generated using the updated atmospheric delay correction model to one or more requesting devices ([0006] and [0029] explaining that position error correction performed at the individual GPS devices, which in the context in which information to correct for position errors is routinely processed by (and therefore received by) the GPS-enabled devices, such devices are effectively “requesting” devices; FIG. 5 GPS-enabled device 104 configured to receive GPS Error Correction transmitted by central processor 101 (deployed by service provider) via network 102; [0036] central processor 101 uses modeled estimates to update position error values; [0043] position error value used to correct position values within GPS-enabled devices (requires transmission of correction data); [0049] updated model used to estimate new value for propagation velocity and position and the central processor 101 transmits the position error estimates to each of the GPS-enabled devices).”
As to claim 18, Rikoski teaches “[t]he computer program product of claim 17, wherein the particular geographical area is associated with one or more correction grids related to the atmospheric delay correction model (FIG. 6 depicting grid comprising voxels 602 associated with atmospheric volume between satellite and GPS-enabled device 104 (therefore associated with geographic area proximate to the GPS-enabled device); [0036]-[0043] describing the position-related parameters related to the grid depicted in FIG. 6 used to update/correct model parameters), and wherein the one or more correction grids is characterized by a grid layout comprising one or more respective data points (FIG. 6 depicting grid comprising voxels 602 (layout of data points) associated with atmospheric volume between satellite and GPS-enabled device 104).”
As to claim 21, Rikoski teaches “[t]he apparatus of claim 9, wherein determining the atmospheric abnormality comprises detecting a deviation exceeding a threshold between the prediction modeling data and the observation data for the particular geographical area ([0048]-[0049] central processor 101 calculates an error estimate by comparing the modeled propagation velocity and position and the values obtained from GPS-enabled devices and if the error is greater than a predetermined threshold the process continues with updating the model and position error estimates (i.e., error must exceed threshold to ascertain sufficient abnormality to warrant model and error updates)).”
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 3, 11, and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Rikoski in view of Hide (US 2023/0358898 A1).
As to claim 3, Rikoski teaches “[t]he computer-implemented method of claim 2,” “wherein the correction is generated to mitigate atmospheric delay impacting the one or more navigational signals related to the one or more correction grids (Abstract; FIG. 5 “Climate Model Data” includes “Data relevant to GPS positions” processed by central processor 101 to provide GPS Error Correction to be provided to GPS-enabled devices (per FIG. 6 is related to geographic areas associated with correction grid).”
Rikoski further teaches the relation between temporal variations in atmospheric conditions and response (update) timing ([0046]) but does not expressly teach “wherein the one or more reconfiguration actions comprise updating a correction data update rate defined by the atmospheric delay correction model, wherein the correction data update rate is a rate at which correction data is transmitted to the one or more requesting devices.”
The utility of varying the correction data update rate in accordance with temporal variations in atmospheric conditions (e.g., more rapid fluctuation) was known in the art prior to the effective filing date. For example, Hide discloses a method for improving satellite positioning by using delay correction (Abstract) in which the correction processing (reconfiguration of the processing) includes updating a correction data update rate defined by the modeling (processing of data to determine corrections) in which the correction data update rate is a rate at which correction data is transmitted to requesting devices (devices that by design of the overall correction recipients are effectively requestors of correction data) ([0017]-[0019] local assistance (for correction) may be required to be transmitted as a higher bitrate due to the local rate being bursty (as responding to rapidly changing local conditions); [0065]-[0066] different error correction update rates may be used depending on differing rates of changes in the errors).
It would have been obvious to one of ordinary skill in the art before the effective filing date, to have applied Hide’s teaching of using different update error correction update rates for different rates of changes in observed error to the method taught by Rikoski such that in combination the method includes the one or more reconfiguration actions comprise updating a correction data update rate defined by the atmospheric delay correction model, wherein the correction data update rate is a rate at which correction data is transmitted to the one or more requesting devices.
The motivation would have been to adjust the rate of correction updates in accordance with the need for such updates that vary temporally, particular for locally observed errors, as disclosed by Hide.
It should be noted that while Rikoski teaches “to mitigate atmospheric delay impacting the one or more navigational signals related to the one or more correction grids,” this feature conveys an intended purpose/result that does not positively limit the scope of the functions recited in the method and is therefore not given patentable weight.
As to claim 11, Rikoski teaches “[t]he apparatus of claim 10,” “wherein the correction is generated to mitigate atmospheric delay impacting the one or more navigational signals related to the one or more correction grids (Abstract; FIG. 5 “Climate Model Data” includes “Data relevant to GPS positions” processed by central processor 101 to provide GPS Error Correction to be provided to GPS-enabled devices (per FIG. 6 is related to geographic areas associated with correction grid).”
Rikoski further teaches the relation between temporal variations in atmospheric conditions and response (update) timing ([0046]) but does not expressly teach “wherein the one or more reconfiguration actions comprise updating a correction data update rate defined by the atmospheric delay correction model, wherein the correction data update rate is a rate at which correction data is transmitted to the one or more requesting devices.”
The utility of varying the correction data update rate in accordance with temporal variations in atmospheric conditions (e.g., more rapid fluctuation) was known in the art prior to the effective filing date. For example, Hide discloses a system/method for improving satellite positioning by using delay correction (Abstract) in which the correction processing (reconfiguration of the processing) includes updating a correction data update rate defined by the modeling (processing of data to determine corrections) in which the correction data update rate is a rate at which correction data is transmitted to requesting devices (devices that by design of the overall correction recipients are effectively requestors of correction data) ([0017]-[0019] local assistance (for correction) may be required to be transmitted as a higher bitrate due to the local rate being bursty (as responding to rapidly changing local conditions); [0065]-[0066] different error correction update rates may be used depending on differing rates of changes in the errors).
It would have been obvious to one of ordinary skill in the art before the effective filing date, to have applied Hide’s teaching of using different update error correction update rates for different rates of changes in observed error to the apparatus taught by Rikoski such that in combination the apparatus is configured to implement the one or more reconfiguration actions as comprising updating a correction data update rate defined by the atmospheric delay correction model, wherein the correction data update rate is a rate at which correction data is transmitted to the one or more requesting devices.
The motivation would have been to adjust the rate of correction updates in accordance with the need for such updates that vary temporally, particular for locally observed errors, as disclosed by Hide.
It should be noted that while Rikoski teaches “to mitigate atmospheric delay impacting the one or more navigational signals related to the one or more correction grids,” this feature conveys an intended purpose/result that does not positively limit the structure/function recited in the apparatus and is therefore not given patentable weight.
As to claim 19, Rikoski teaches “[t]he computer program product of claim 18,” “wherein the correction is generated to mitigate atmospheric delay impacting the one or more navigational signals related to the one or more correction grids (Abstract; FIG. 5 “Climate Model Data” includes “Data relevant to GPS positions” processed by central processor 101 to provide GPS Error Correction to be provided to GPS-enabled devices (per FIG. 6 is related to geographic areas associated with correction grid).”
Rikoski further teaches the relation between temporal variations in atmospheric conditions and response (update) timing ([0046]) but does not expressly teach “wherein the one or more reconfiguration actions comprise updating a correction data update rate defined by the atmospheric delay correction model, wherein the correction data update rate is a rate at which correction data is transmitted to the one or more requesting devices.”
The utility of varying the correction data update rate in accordance with temporal variations in atmospheric conditions (e.g., more rapid fluctuation) was known in the art prior to the effective filing date. For example, Hide discloses a system/method for improving satellite positioning by using delay correction (Abstract) in which the correction processing (reconfiguration of the processing) includes updating a correction data update rate defined by the modeling (processing of data to determine corrections) in which the correction data update rate is a rate at which correction data is transmitted to requesting devices (devices that by design of the overall correction recipients are effectively requestors of correction data) ([0017]-[0019] local assistance (for correction) may be required to be transmitted as a higher bitrate due to the local rate being bursty (as responding to rapidly changing local conditions); [0065]-[0066] different error correction update rates may be used depending on differing rates of changes in the errors).
It would have been obvious to one of ordinary skill in the art before the effective filing date, to have applied Hide’s teaching of using different update error correction update rates for different rates of changes in observed error to the apparatus taught by Rikoski such that in combination the apparatus is configured to implement the one or more reconfiguration actions as comprising updating a correction data update rate defined by the atmospheric delay correction model, wherein the correction data update rate is a rate at which correction data is transmitted to the one or more requesting devices.
The motivation would have been to adjust the rate of correction updates in accordance with the need for such updates that vary temporally, particular for locally observed errors, as disclosed by Hide.
It should be noted that while Rikoski teaches “to mitigate atmospheric delay impacting the one or more navigational signals related to the one or more correction grids,” this feature conveys an intended purpose/result that does not positively limit the structure/function recited in the apparatus and is therefore not given patentable weight.
Claims 4, 12, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Rikoski in view of Limberger (US 2021/0149060 A1).
As to claim 4, Rikoski teaches “[t]he computer-implemented method of claim 2,” and as noted in the grounds for rejecting claim 2 discloses use of a correction grid. However, Rikoski does not appear to expressly teach “wherein the one or more reconfiguration actions comprise modifying the grid layout associated with a respective correction grid of the one or more correction grids.”
Limberger discloses a method for providing delay correction data for satellite-based positioning and navigation (Abstract) that includes modeling atmospheric conditions/corrections using TEC values that may be implemented as a grid ([0052]) and in which the overall grid layout may be modified based on updated correction data ([0056] calculated (updated) TEC/STEC values determined as part of correction modeling and used to optimize (modify) estimates of ionosphere activity such as between grid points in a thin-layer model).
It would have been obvious to one of ordinary skill in the art before the effective filing date, to have applied Limberger’s teaching of using a thin-layer grid model for tracking ionosphere conditions as part of a correction model and to reconfigure the correction model by modifying the grid layout to the method taught by Rikoski such that in combination the method includes wherein the one or more reconfiguration actions comprise modifying the grid layout associated with a respective correction grid of the one or more correction grids.
Such a combination would amount to selecting a known design option for implementing correction modeling and updating of such correction modeling to achieve predictable results.
As to claim 12, Rikoski teaches “[t]he apparatus of claim 10,” and as noted in the grounds for rejecting claim 10 discloses use of a correction grid. However, Rikoski does not appear to expressly teach “wherein the one or more reconfiguration actions comprise modifying the grid layout associated with a respective correction grid of the one or more correction grids.”
Limberger discloses a system/method for providing delay correction data for satellite-based positioning and navigation (Abstract) that includes modeling atmospheric conditions/corrections using TEC values that may be implemented as a grid ([0052]) and in which the overall grid layout may be modified based on updated correction data ([0056] calculated (updated) TEC/STEC values determined as part of correction modeling and used to optimize (modify) estimates of ionosphere activity such as between grid points in a thin-layer model).
It would have been obvious to one of ordinary skill in the art before the effective filing date, to have applied Limberger’s teaching of using a thin-layer grid model for tracking ionosphere conditions as part of a correction model and to reconfigure the correction model by modifying the grid layout to the apparatus taught by Rikoski such that in combination the apparatus is configured such that the one or more reconfiguration actions comprise modifying the grid layout associated with a respective correction grid of the one or more correction grids.
Such a combination would amount to selecting a known design option for implementing correction modeling and updating of such correction modeling to achieve predictable results.
As to claim 20, Rikoski teaches “[t]he computer program product of claim 19,” and as noted in the grounds for rejecting claim 18 discloses use of a correction grid. However, Rikoski does not appear to expressly teach “wherein the one or more reconfiguration actions comprise modifying the grid layout associated with a respective correction grid of the one or more correction grids.”
Limberger discloses a system/method for providing delay correction data for satellite-based positioning and navigation (Abstract) that includes modeling atmospheric conditions/corrections using TEC values that may be implemented as a grid ([0052]) and in which the overall grid layout may be modified based on updated correction data ([0056] calculated (updated) TEC/STEC values determined as part of correction modeling and used to optimize (modify) estimates of ionosphere activity such as between grid points in a thin-layer model).
It would have been obvious to one of ordinary skill in the art before the effective filing date, to have applied Limberger’s teaching of using a thin-layer grid model for tracking ionosphere conditions as part of a correction model and to reconfigure the correction model by modifying the grid layout to the apparatus taught by Rikoski such that in combination the apparatus is configured such that the one or more reconfiguration actions comprise modifying the grid layout associated with a respective correction grid of the one or more correction grids.
Such a combination would amount to selecting a known design option for implementing correction modeling and updating of such correction modeling to achieve predictable results.
Claims 7 and 15 are rejected under 35 U.S.C. 103 as being unpatentable over Rikoski in view of Kleeman (US 2021/0033735 A1).
As to claim 7, Rikoski teaches “[t]he computer-implemented method of claim 2, wherein the computer-implemented method further comprises:
“determining that an atmospheric abnormality is adversely affecting the one or more navigational signals associated with the particular geographical area ([0048] calculate errors in propagation velocities and position values (delay metrics) that per [0027] are caused by atmospheric conditions. Examiner notes that a deviation from modeled/predicted values entails a change from modeled weather/climate expectation and hence falls within a broadest reasonable interpretation of an abnormality, which as explained in [0027] and inferentially disclosed by the error determination in [0048] is effectively a determination that abnormal (not expected) atmospheric conditions are adversely affecting navigation signals).”
Rikoski does not expressly teach “in response to” determining that an atmospheric abnormality is adversely affecting the one or more navigational signals associated with the particular geographical area:
“generating one or more warning indicators associated with the atmospheric abnormality; and
transmitting the one or more warning indicators to one or more requesting devices associated with the service provider.”
Kleeman discloses a method for optimizing GNSS corrections (Abstract) that includes as part of the correction processing (in response to determining atmospheric conditions that may adversely affect navigation signals), generating and transmitting a warning indicator associated with the atmospheric condition variations to requesting devices ([0131] a flag/warning may be included in the GNSS corrections (associated with the corrections) that are used for correcting the model; [0133] corrections transmitted to a mobile receiver).
It would have been obvious to one of ordinary skill in the art before the effective filing date, to have applied Kleeman’s teaching of in response to determining atmospheric conditions that may adversely affect navigation signals, generating a warning indicator associated with the variations in atmospheric conditions and transmitting the warning indicator to requesting devices to the method taught by Rikoski in which the variations in atmospheric conditions constitute atmospheric disturbances/abnormalities and in which the requesting devices are associated with a service provider such that in combination the method includes in response to determining that an atmospheric abnormality is adversely affecting the one or more navigational signals associated with the particular geographical area: generating one or more warning indicators associated with the atmospheric abnormality; and transmitting the one or more warning indicators to one or more requesting devices associated with the service provider.
The motivation would have been to provide an enhanced indication to requesting devices (e.g., GPS-enabled devices) that atmospheric conditions have changed significantly as suggested by Kleeman.
As to claim 15, Rikoski teaches “[t]he apparatus of claim 10, wherein the at least one memory and the computer program code are further configured to, with the processing circuitry, cause the apparatus to:
“determining that an atmospheric abnormality is adversely affecting the one or more navigational signals associated with the particular geographical area ([0048] calculate errors in propagation velocities and position values (delay metrics) that per [0027] are caused by atmospheric conditions. Examiner notes that a deviation from modeled/predicted values entails a change from modeled weather/climate expectation and hence falls within a broadest reasonable interpretation of an abnormality, which as explained in [0027] and inferentially disclosed by the error determination in [0048] is effectively a determination that abnormal (not expected) atmospheric conditions are adversely affecting navigation signals).”
Rikoski does not expressly teach “in response to” determining that an atmospheric abnormality is adversely affecting the one or more navigational signals associated with the particular geographical area:
“generate one or more warning indicators associated with the atmospheric abnormality; and
transmit the one or more warning indicators to one or more requesting devices associated with the service provider.”
Kleeman discloses a system/method for optimizing GNSS corrections (Abstract) that includes as part of the correction processing (in response to determining atmospheric conditions that may adversely affect navigation signals), generating and transmitting a warning indicator associated with the atmospheric condition variations to requesting devices ([0131] a flag/warning may be included in the GNSS corrections (associated with the corrections) that are used for correcting the model; [0133] corrections transmitted to a mobile receiver).
It would have been obvious to one of ordinary skill in the art before the effective filing date, to have applied Kleeman’s teaching of in response to determining atmospheric conditions that may adversely affect navigation signals, generating a warning indicator associated with the variations in atmospheric conditions and transmitting the warning indicator to requesting devices to the apparatus taught by Rikoski in which the variations in atmospheric conditions constitute atmospheric disturbances/abnormalities and in which the requesting devices are associated with a service provider such that in combination the apparatus is configured to perform in response to determining that an atmospheric abnormality is adversely affecting the one or more navigational signals associated with the particular geographical area: generating one or more warning indicators associated with the atmospheric abnormality; and transmitting the one or more warning indicators to one or more requesting devices associated with the service provider.
The motivation would have been to provide an enhanced indication to requesting devices (e.g., GPS-enabled devices) that atmospheric conditions have changed significantly as suggested by Kleeman.
Claim 16 is rejected under 35 U.S.C. 103 as being unpatentable over Rikoski in view of Wang (US 2023/0017707 A1).
As to claim 16, Rikoski teaches “[t]he apparatus of claim 9,” but does not teach “wherein the atmospheric abnormality mitigation system comprises one or more machine learning models configured to generate the prediction modeling data.”
Wang discloses a system/method for correcting for/mitigating ionospheric error (Abstract) in which machine learning modeling may be used for generating prediction modeling data relating to atmospheric activity ([0069] TEC values may be determined by machine learning model that is configured to compute (estimate what the value should be and therefore entails prediction) ionospheric delay (atmospheric activity) and corresponding correction value).
It would have been obvious to one of ordinary skill in the art before the effective filing date, to have applied Wang’s teaching of implementing machine learning modeling in an atmospheric delay mitigation system in which the machine learning model is used for generating prediction modeling data relating to atmospheric activity to the apparatus taught by Rikoski such that in combination Rikoski’s disclosed modeling for estimating what the atmospheric activity should be (predicting atmospheric activity) includes, at least in part, a machine learning model.
Such a combination would amount to selecting a known design option for predicting atmospheric activity such as may be used for atmospheric delay correction to achieve predictable results. Furthermore, a particular motivation would have been to leverage the learning/training adaptability of machine learning models to provide more accurate atmospheric activity results.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MATTHEW W BACA whose telephone number is (571)272-2507. The examiner can normally be reached Monday - Friday 8:00 am - 5:30 pm.
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/MATTHEW W. BACA/Examiner, Art Unit 2857
/ANDREW SCHECHTER/Supervisory Patent Examiner, Art Unit 2857
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