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 .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 12/31/2025 is in compliance with the provisions of 35 CFR 1.97. Accordingly, the IDS has been considered by the examiner.
Response to Amendment
Applicant’s amendment with arguments and remarks filed on 12/29/2025 have been fully considered.
Claims 1–9 and 11–16 are pending.
Claim 10 has been canceled.
Claims 1, 11, 13, and 14 have been amended.
New claims 15 and 16 have been added.
Applicant’s amendments to claims 13 and 14 do not overcome the 35 U.S.C. 101 rejection.
Response to Arguments
Applicant’s arguments, see remarks pages 8-9, filed 12/29/2025, with respect to the rejection(s) of claims 1-14 under 35 U.S.C. 103 have been fully considered and are persuasive. Therefore, the rejection has been withdrawn. However, upon further consideration and necessitated by amendment, a new ground(s) of rejection is made in view of Zhang et al. (US 2023/0288577 A1) in view of Martin et al. (US 2017/0276799 A1).
Claim Objections
Claim 1 objected to because of the following informalities: claim 1 recites, “a navigation satellite system, hereinafter abbreviated as “NSS”, receiver,…” which appears to be a typographical error of . Appropriate correction is required.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitations are:
"processing entity capable of receiving data" is a nonce term in claims 1 and 11. The Examiner acknowledges that the specification discloses mathematical equations and process flowcharts (Figs. 1–13; Figs. 2–4, 6a–7b, 11–17). The specification confirms its ambiguity on page 9 where it is noted that the term encompasses “one or more computers and/or servers, or more generally by any number of processing entities implemented in hardware, firmware, and/or software.” It identifies no particular processor architecture, circuit design, or hardware module, it is the functional equivalent of means for processing. In claim 1, the ‘processing entity’ performs four recited functions: operating the NSS estimator set, obtaining ionospheric disturbance information, determining that disturbance level exceeds a threshold, and adapting the ionospheric and/or observation noise model. In claim 11, the ‘processing entity’ is expressly ‘configured to perform steps comprising’ the same functions of claim 1. Each function is defined entirely by is result with no structural configuration recited. Neither claim recites structural language constraining how the ‘processing entity’ performs the prior noted functions.
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 13 and 14 rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
The term ‘non-transitory computer program’ (claim 13) and ‘non-transitory computer program product’ (claim 14) are not terms of art in the patent or computing arts, are not defined in the specification, and render the metes and bounds of the claims fatally unclear: a person of ordinary skill in the art cannot determine with reasonable certainty whether each claim is directed to a computer program (software) or to a non-transitory storage medium embodying that program.
The modifier ‘non-transitory’ is well understood in patent practice when applied to a storage medium — it distinguishes a durable physical medium from a transitory propagating signal, consistent with USPTO guidance. However, ‘non-transitory’ is not a recognized modifier when applied to a computer program itself. A computer program is not the type of article to which ‘transitory’ versus ‘non-transitory’ is a meaningful distinction: a program is an abstract set of instructions. The transitory/non-transitory distinction is meaningful for the physical medium that carries or stores the program, not for the program itself.
The specification of the present application does not define ‘non-transitory computer program’ or explain what the modifier ‘non-transitory’ is intended to convey when applied to a computer program. Spec. Page 45 describe computer programs and storage media in general terms — the computer program(s) may be ‘loaded on an apparatus’ and the computer-readable medium ‘may for instance be a magnetic tape, an optical memory disk, a magnetic disk… a CD-ROM, a DVD, a CD, a flash memory unit, or the like’, but nowhere does the specification attribute a specific meaning to the phrase ‘non-transitory computer program.’ In the absence of a lexicographic definition in the specification, the term must be given its ordinary meaning in the art; as established above, no such ordinary meaning exists.
EXAMINER SUGGESTED CLAIM MODIFICATION
The examiner notes that the 35 U.S.C. 101 rejection of Claims 13 and 14 may be overcome by amending the claim language to clearly recite the computer program as stored on or embodied in a non-transitory computer-readable storage medium. The following amended language is suggested for consideration by Applicant:
Suggested Amended Claim 13:
(Currently Amended) Non-transitory computer-readable storage medium storing a computer program or set of computer programs comprising computer-readable instructions configured, when executed on a computer or set of computers, to cause the computer or set of computers to carry out the method according to claim 1.
Suggested Amended Claim 14:
(Currently Amended) Non-transitory computer-readable storage medium according to claim 13, wherein the non-transitory computer-readable storage medium is at least one of: a magnetic tape, an optical memory disk, a magnetic disk, a magneto-optical disk, a solid-state disk (SSD), a CD-ROM, a DVD, a CD, and a flash memory unit.
The suggested amendment to Claim 13 resolves the 35 U.S.C. 112(b) rejection by recasting the claim as a manufacture — specifically a non-transitory computer-readable storage medium — rather than a bare computer program per se. A non-transitory computer-readable storage medium is a recognized statutory manufacture under 35 U.S.C. 101. See In re Beauregard, 53 F.3d 1583 (Fed. Cir. 1995).
The suggested amendment to Claim 14 resolves the inherited 35 U.S.C. 112(b) deficiency from Claim 13 and the ambiguity in the original preamble by recasting Claim 14 as dependent on the amended Claim 13 and enumerating specific tangible storage media drawn directly from the specification at page 45 (see Fig. 1 below), which recites: “a magnetic tape, an optical memory disk, a magnetic disk, a magneto-optical disk, an SSD, a CD-ROM, a DVD, a CD, a flash memory unit, or the like.” This directly ties the claim to tangible, non-transitory media expressly supported by the specification, satisfying both 35 U.S.C. 101 and the written description requirement of 35 U.S.C. 112(a).
The examiner notes that these suggestions are offered as guidance only. Applicant is free to propose alternative amended language provided it resolves the 35 U.S.C. 112(b) rejection and finds clear support in the specification. No new matter may be introduced pursuant to 35 U.S.C. § 132.
PNG
media_image1.png
198
618
media_image1.png
Greyscale
Fig. 1, Specification Page 45
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 1-9, 11-12, and 15-16 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. The claim(s) does/do not fall within at least one of the four categories of patent eligible subject matter because the claims recite: computing ionospheric disturbance metrics via defined equations (Eqs. 1-13), comparing a computed numerical value against a threshold (a mathematical relationship), and adjusting Gauss-Markov stochastic parameters by applying a scale factor (a mathematical calculation). All of this map directly to the mathematical concepts. Under the Alice/Mayo two-step framework and the USPTO’s January 2019 Revised Guidance (84 Fed. Reg. 50), the claims are directed to an abstract idea — specifically mathematical concepts under Grouping (a)(1) — and recite no additional elements sufficient to amount to significantly more. Alice Corp. v. CLS Bank Int’l, 573 U.S. 208 (2014); Mayo Collaborative Servs. v. Prometheus Labs., Inc., 566 U.S. 66 (2012).
Step 2A, Prong 1 — Abstract Idea (Mathematical Concepts)
The claims are directed to the following abstract idea: mathematically computing ionospheric disturbance metrics from navigation satellite signal data (scintillation levels and gradient levels via Equations 1–13, Spec. Pages 19-26); comparing those computed metrics to a threshold value (Spec. Pages 39-40); and conditionally applying mathematical adjustments to the Gauss-Markov stochastic parameters of a positioning estimator’s noise model (scale factor application; correlated noise and correlation time modification, Spec. Pages 39-41; claims 8–9). This constitutes mathematical relationships, mathematical calculations, and mathematical formulas — each a recognized mathematical concepts category under the 2019 Revised Guidance. 84 Fed. Reg. at 52. The ionospheric noise model is itself a ‘mathematical model.’ Spec. Page 35. The field-of-use limitation to GNSS/NSS positioning does not alter this characterization. Alice, 573 U.S. at 223. See also Electric Power Group, LLC v. Alstom S.A., 830 F.3d 1350, 1354 (Fed. Cir. 2016); Digitech Image Techs., LLC v. Electronics for Imaging, Inc., 758 F.3d 1344, 1350 (Fed. Cir. 2014).
Step 2A, Prong 2 — No Integration into a Practical Application
The additional claim elements do not integrate the abstract idea into a practical application. The NSS receiver/processing entity is generic computing hardware (CPU, memory, I/O — Spec. Page 46); the NSS estimator (Kalman filter, LMS, robust estimator) is explicitly acknowledged as well-known (Spec. [0168]); receipt of correction data from a reference station is foundational RTK/PPP architecture identified as background art (Spec. Pages 1-3); and the ionospheric-free switching of claims 15–16 is a known fallback (Spec. Page 35). The claims improve positioning accuracy as an outcome but disclose no improvement to the receiver hardware, signal processing circuitry, or computer functionality itself. An improvement to results, as opposed to technology, does not integrate an abstract idea into a practical application. Electric Power Group, 830 F.3d at 1356.
Step 2B — No Significantly More
Considered individually and as an ordered combination, the additional elements are well-understood, routine, and conventional in the GNSS art. Generic computing hardware running known estimation algorithms on received satellite data, applying a mathematical scale factor when a computed threshold is exceeded, is a straightforward ‘apply it’ instruction that Alice, 573 U.S. at 221, held insufficient. The dependent claims (2–9, 15–16) narrow the abstract idea through mathematical modeling choices (Gauss-Markov parameters, scintillation data types, ionospheric-free switching) but introduce no inventive concept beyond the abstract idea itself.
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1-9 and 11-16 are rejected under 35 U.S.C. 103 as being unpatentable over Zhang et al. (US 2023/0288577 A1) in view of Martin et al. (US 2017/0276799 A1).
Regarding Claim 1, Zhang et al. (‘577) in view of Martin et al. (‘799) teaches:
Zhang et al. (‘577) teaches: Method, carried out by at least one of a navigation satellite system, hereinafter abbreviated as “NSS”, receiver, and a processing entity capable of receiving data from the NSS receiver, for estimating parameters useful to determine a position, the NSS receiver observing NSS signals from NSS satellites, ([0006]: “a system is disclosed for a estimating position by a rover receiver in wireless communication with a base station receiver at a known location. The rover receiver and the base station receiver are capable of receiving a plurality of Global Navigation Satellite System (GNSS) signals from GNSS satellites.”)
Zhang et al. (‘577) teaches: the method comprising: operating at least one estimation process, each estimation process being hereinafter referred to as “NSS estimator” and the at least one NSS estimator being hereinafter referred to as “NSS estimator set”, wherein each NSS estimator uses state variables and computes values of its state variables based on at least one of: NSS signals observed by the NSS receiver, and information derived from the NSS signals; ([0083]: “the navigation positioning estimator 57 comprises a real-time kinematic (RTK) estimator 122, a precise position estimator 120 (e.g., PPP estimator), and the ambiguity resolution module 407”; [0094]: “the RTK engine, error estimator, electronic data processor 159 or GNSS rover receiver 12 is configured to apply a positioning filter with a dual (e.g., two stage) error model or a dual (e.g., two stage) adaptive statistical model to estimate residual errors.”)
Zhang et al. (‘577) teaches: obtaining ionospheric disturbance information comprising at least one of: ionospheric scintillation information and ionospheric gradient information, ([0003]: “Scintillation refers to propagation of electromagnetic signals that are subject to frequency-dependent fluctuations in amplitude and phase associated with the signals passing through atmospheric (e.g., ionospheric) differences”; [0093]: “the RTK engine, data processor 159 or GNSS rover receiver 12 is configured to model ionospheric properties associated with a given propagation path between any satellite and the rover receiver 12 in accordance with an ionospheric model that can estimate and/or mitigate one or more of the following: ionosphere delay, ionospheric amplitude shifts in the received carrier signal of a respective satellite, ionospheric phase shifts in the received carrier signal of a respective satellite.” The ‘at least one of’ language means the art need only teach one alternative.)
Zhang et al. (‘577) teaches: wherein obtaining the ionospheric disturbance information comprises at least one of: receiving, from a reference station or reference station system, the ionospheric disturbance information; ([0086]: “the GNSS base station receiver 30 (e.g., reference receiver) of the RTK system is configured to generate aiding information, where the base station receiver 30 (e.g., reference receiver) is located at a known location”; [0087]: “the GNSS base station receiver 30 provides correction data or aiding information to the GNSS rover receiver 12 via the wireless link such that the GNSS rover receiver 12 can mitigate errors in the carrier phase measurements.” The ‘at least one of’ in the obtaining step means the art need only teach one of the two alternatives; Zhang teaches receiving ionospheric disturbance information from a reference station.)
Zhang et al. (‘577) teaches: determining that the ionospheric disturbance information indicates an ionospheric disturbance level exceeding a threshold; ([0043]: “GNSS rover receiver 106 applies a dual (e.g., two stage) RTK algorithm with all the information it received to achieve high position accuracy without a baseline length limit and without atmospheric activity limit (e.g., Total Electron Count of ionosphere exceeding a certain threshold).”)
Zhang et al. (‘577) does not explicitly teach, but Martin et al. (‘799) teaches, for at least one NSS estimator of the NSS estimator set, performing at least one of: adapting an ionospheric noise model of the NSS estimator based on the ionospheric disturbance information; or adapting an observation noise model of the NSS estimator based on the ionospheric disturbance information. ([0107]-[0119]: the Kalman filter state vector X includes the ionospheric error B.sub.iono as a state variable, and the propagation noise matrix Q includes “q.sub.iono represents the state noise of the Markov model (1.sup.st order) of the ionospheric error after correction by the model”; [0133]: “σ.sub.iono represents the standard deviation of the ionospheric error on the axis in sight of the satellite under consideration. Its value is given by atmospheric models, depending on the inclination of the satellite axis, the latitude of the receiver and the time of day.”) Martin teaches that the ionospheric noise model parameters (q.sub.iono, σ.sub.iono) of the Kalman filter state estimator are set and adapted based on ionospheric conditions, constituting adapting an ionospheric noise model of the NSS estimator based on ionospheric disturbance information. The ‘at least one of’ language means the art need only teach one of the two alternatives.
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to combine the adaptive ionospheric error modeling system of Zhang et al. (‘577) with the Kalman-filter-based ionospheric noise model parametrization of Martin et al. (‘799). One would have been motivated to do so in order to specifically quantify and adapt the ionospheric noise model parameters of the positioning Kalman filter estimator—as taught by Martin—when ionospheric disturbance conditions are detected, thereby improving the accuracy of ionospheric error estimation and overall positioning accuracy during periods of elevated ionospheric activity ([0107]-[0119], [0133]). Zhang already employs a Kalman filter for positioning ([0095], [0132]) and an adaptive ionospheric error framework ([0120]), and Martin’s specific noise model parametrization provides the known technique for adapting the noise covariance parameters of such a filter based on atmospheric conditions, making the combination a straightforward application of known techniques with a reasonable expectation of success.
Regarding Claim 2, Zhang et al. (‘577) in view of Martin et al. (‘799) teaches the Method of claim 1.
Zhang et al. (‘577) teaches: wherein the ionospheric disturbance information comprises at least one of: ionospheric disturbance information applicable to a point on or near the surface of the Earth, said ionospheric disturbance information being hereinafter referred to as “station-specific ionospheric disturbance information”; and ionospheric disturbance information applicable to a line of sight between a point on or near the surface of the Earth and a satellite, said ionospheric disturbance information being hereinafter referred to as “satellite-specific ionospheric disturbance information”. ([0041]: “In one embodiment, atmospheric delay is in the form of a zenith delay with mapping function for each measurement. Zenith delay is the atmospheric delay experienced by a satellite signal that propagates in the zenith direction, which is a point vertically above a rover receiver or base station receiver”; [0042]: “the slant atmospheric delay represents the total propagation delay in a GNSS signal between the satellite and a receiver antenna of the rover receiver.”) Zenith delay constitutes station-specific ionospheric disturbance information applicable to a point on or near the surface of the Earth; slant delay constitutes satellite-specific ionospheric disturbance information applicable to a line of sight between a point and a satellite. The ‘at least one of’ language means the art need only teach one of the alternatives.
Regarding Claim 3, Zhang et al. (‘577) in view of Martin et al. (‘799) teaches the Method of claim 1.
Zhang et al. (‘577) teaches: wherein the ionospheric disturbance information comprises ionospheric scintillation information comprising at least one of: ionospheric amplitude scintillation information, and ionospheric phase scintillation information. ([0003]: “Scintillation refers to propagation of electromagnetic signals that are subject to frequency-dependent fluctuations in amplitude and phase”; [0093]: “the RTK engine, data processor 159 or GNSS rover receiver 12 is configured to model ionospheric properties … ionospheric amplitude shifts in the received carrier signal of a respective satellite, ionospheric phase shifts in the received carrier signal of a respective satellite.”) The ‘at least one of’ language means the art need only teach one of the alternatives. Zhang explicitly teaches both ionospheric amplitude and phase shift information.
Regarding Claim 4, Zhang et al. (‘577) in view of Martin et al. (‘799) teaches the Method according to claim 1.
Zhang et al. (‘577) does not explicitly teach, but Martin et al. (‘799) teaches: wherein adapting an ionospheric noise model comprises applying at least one of a scale factor and an additive value to the ionospheric noise model. ([0107]-[0119]: the Kalman filter Q matrix includes “q.sub.iono represents the state noise of the Markov model (1.sup.st order) of the ionospheric error” (an additive value applied to the ionospheric noise model); [0133]: “σ.sub.iono represents the standard deviation of the ionospheric error on the axis in sight of the satellite under consideration. Its value is given by atmospheric models, depending on the inclination of the satellite axis, the latitude of the receiver and the time of day” (a scale factor applied to the ionospheric noise model). The ‘at least one of’ language means the art need only teach one of the alternatives.)
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to combine the adaptive ionospheric error modeling of Zhang et al. (‘577) with the Kalman filter noise model parametrization of Martin et al. (‘799). One would have been motivated to do so in order to use well-known scale factor and additive value parametrization techniques to quantify the ionospheric noise model adaptation within Zhang’s positioning filter, thereby achieving a more precise and controllable ionospheric noise model adaptation ([0107]-[0119], [0133]).
Regarding Claim 5, Zhang et al. (‘577) in view of Martin et al. (‘799) teaches the Method according to claim 1.
Zhang et al. (‘577) does not explicitly teach, but Martin et al. (‘799) teaches: wherein the ionospheric noise model is or comprises an ionospheric delay state noise model. ([0111]-[0112]: “B.sub.iono represents the ionospheric error at a frequency (for example at the frequency Fa) after correction by the model (residual)”; Q matrix includes “q.sub.iono represents the state noise of the Markov model (1.sup.st order) of the ionospheric error after correction by the model.”) The Kalman filter state includes the ionospheric delay as a state variable, and q.sub.iono is the corresponding state noise — the ionospheric delay state noise model. The ‘is or comprises’ language means the art need only show the noise model constitutes or includes an ionospheric delay state noise model.)
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to combine the adaptive ionospheric error modeling of Zhang et al. (‘577) with the ionospheric delay state noise model of Martin et al. (‘799). One would have been motivated to do so in order to explicitly represent the ionospheric delay as a state variable in the positioning filter and assign a corresponding state noise, enabling more accurate and systematic tracking of ionospheric delay residuals within the Kalman filter framework of Zhang ([0111]-[0112]).
Regarding Claim 6, Zhang et al. (‘577) in view of Martin et al. (‘799) teaches the Method according to claim 1.
Zhang et al. (‘577) teaches: wherein the ionospheric noise model is or comprises an ionospheric noise model specific to a NSS satellite. ([0132]: “In step S206, for each channel of any satellite, a GNSS receiver, data processor 159 or its filter is configured to filter a selected ionosphere model for ionospheric delay estimation”; [0093]: “In step 205, the RTK engine, data processor 159 or GNSS rover receiver 12 is configured to model ionospheric properties associated with a given propagation path between any satellite and the rover receiver 12”) Zhang teaches per-satellite ionospheric modeling, i.e., an ionospheric noise model specific to each NSS satellite.
Regarding Claim 7, Zhang et al. (‘577) in view of Martin et al. (‘799) teaches the Method according to claim 1.
Zhang et al. (‘577) does not explicitly teach, but Martin et al. (‘799) teaches: wherein the ionospheric noise model is or comprises a Gauss-Markov noise model. ([0115]-[0116]: “λ.sub.iono represents the attenuation factor of the Markov model of the ionospheric error. λ.sub.iono=1−ΔT/τ [0116] ΔT represents the adjustment period for the filter and τ represents the time constant of the Markov model (1.sup.st order) of the ionospheric error after correction by the model.”) Martin explicitly teaches that the ionospheric error state in the Kalman filter is modeled using a first-order Markov (Gauss-Markov) model.)
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to combine the adaptive ionospheric error modeling of Zhang et al. (‘577) with the Gauss-Markov ionospheric noise model of Martin et al. (‘799). One would have been motivated to do so in order to employ a well-established stochastic model for ionospheric error dynamics within Zhang’s positioning Kalman filter, as the Gauss-Markov model is a known and widely-used approach that provides a principled mathematical framework for modeling the temporal correlation of ionospheric errors ([0115]-[0116]).
Regarding Claim 8, Zhang et al. (‘577) in view of Martin et al. (‘799) teaches the Method of claim 7.
Zhang et al. (‘577) does not explicitly teach, but Martin et al. (‘799) teaches: wherein the Gauss-Markov noise model is parametrized by a correlated noise and a correlation time, ([0115]-[0123]: “q.sub.iono represents the state noise of the Markov model (1.sup.st order) of the ionospheric error after correction by the model” (correlated noise); “λ.sub.iono represents the attenuation factor of the Markov model of the ionospheric error.”)
Zhang et al. (‘577) does not explicitly teach, but Martin et al. (‘799) teaches: and adapting the ionospheric noise model comprises modifying at least one of: the correlated noise and the correlation time. ([0133]: “σ.sub.iono represents the standard deviation of the ionospheric error on the axis in sight of the satellite under consideration. Its value is given by atmospheric models, depending on the inclination of the satellite axis, the latitude of the receiver and the time of day”) Martin teaches that the ionospheric noise model parameters (including correlated noise q.sub.iono and the correlation time tau of the Markov model) are set based on atmospheric conditions, constituting adapting the Gauss-Markov noise model by modifying its parameters. The ‘at least one of’ language means the art need only teach modification of one of the two parameters. This element is contingent on the Gauss-Markov parametrization above; per MPEP guidance on contingent limitations, because the Gauss-Markov model is taught, this limitation follows directly.)
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to combine the adaptive ionospheric error modeling of Zhang et al. (‘577) with the Gauss-Markov parametrization of Martin et al. (‘799). One would have been motivated to do so in order to adapt the specific correlated noise and correlation time parameters of the Gauss-Markov ionospheric noise model in Zhang’s positioning filter based on detected ionospheric conditions, thereby enabling the filter to respond more accurately to varying ionospheric disturbance levels ([0115]-[0116], [0133]).
Regarding Claim 9, Zhang et al. (‘577) in view of Martin et al. (‘799) teaches the Method of claim 8.
Zhang et al. (‘577) does not explicitly teach, but Martin et al. (‘799) teaches: wherein adapting the ionospheric noise model comprises at least one of: increasing the correlated noise; and decreasing the correlation time. ([0133]: “σ.sub.iono represents the standard deviation of the ionospheric error on the axis in sight of the satellite under consideration. Its value is given by atmospheric models, depending on the inclination of the satellite axis, the latitude of the receiver and the time of day”) This element is contingent on the Gauss-Markov parametrization of claim 8. Per MPEP guidance on contingent limitations, because Martin teaches adapting q.sub.iono and tau based on atmospheric conditions, increasing the correlated noise or decreasing the correlation time when ionospheric disturbance is elevated would have been obvious to a POSITA as a natural consequence of the adaptive noise model teaching. The ‘at least one of’ language means the art need only teach one of the two alternatives.)
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to combine the adaptive ionospheric error modeling of Zhang et al. (‘577) with the Gauss-Markov noise model of Martin et al. (‘799). One would have been motivated to do so in order to increase the correlated noise or decrease the correlation time when elevated ionospheric disturbance is detected, allowing the positioning filter to respond more quickly to rapidly changing ionospheric conditions and thereby maintaining positioning accuracy during scintillation events ([0133]).
Regarding Claim 11, Claim 11 is a system claim that is substantially similar in scope to independent method Claim 1, except for the preamble reciting a “System” rather than a “Method.” Zhang et al. (‘577) in view of Martin et al. (‘799) teaches the system of claim 11 for the same reasons set forth in the rejection of Claim 1 above, applied to the system configuration.
Zhang et al. (‘577) teaches: System comprising at least one of a navigation satellite system receiver, hereinafter abbreviated as “NSS receiver”, and a processing entity capable of receiving data from the NSS receiver, the system being for estimating parameters useful to determine a position, the NSS receiver observing NSS signals from NSS satellites, and the at least one of the NSS receiver and the processing entity capable of receiving data from the NSS receiver configured to perform steps comprising: ([0006]: “a system is disclosed for estimating position by a rover receiver in wireless communication with a base station receiver at a known location. The rover receiver and the base station receiver are capable of receiving a plurality of Global Navigation Satellite System (GNSS) signals from GNSS satellites”; [0019]: “the system, method and receiver disclosed in this document may comprise a computer-implemented system, method or receiver in which one or more data processors process, store, retrieve, and otherwise manipulate data via data buses and one or more data storage devices.”)
All remaining steps configured to be performed by the system of Claim 11 are identical in substance to those of Claim 1. For the reasons set forth for Claim 1 above, Claim 11 is unpatentable over Zhang in view of Martin for the same reasons, applied to the system configuration.
Regarding Claim 12, Zhang et al. (‘577) in view of Martin et al. (‘799) teaches the System according to claim 11.
Zhang et al. (‘577) teaches: Vehicle comprising a system according to claim 11, the vehicle preferably being at least one of: a motor vehicle, an agricultural tractor, a combine harvester, a crop sprayer, a construction equipment, a truck, a bus, a train, a motorcycle, an autonomous vehicle, a self-driving vehicle, a driverless vehicle, a robotic vehicle, a highly automated vehicle, an aircraft, and an unmanned aerial vehicle. ([0059]: “FIG. 2 shows a mobile receiver 12 that operates in the real-time kinematic mode.”) The vehicle limitation is contingent on the underlying system of claim 11. Per MPEP guidance on contingent limitations, this limitation defines a field-of-use for the system, which does not impart patentability. The use of a GNSS positioning system on any of the listed vehicles is a well-known and routine application that would have been obvious to a POSITA. The word ‘preferably’ further confirms these are non-limiting preferred uses of the system.
Regarding Claims 13 and 14, Claims 13 and 14 are grouped because, ignoring the preambles, they are essentially directed to the same subject matter: a non-transitory computer program (Claim 13) and a non-transitory computer program product or storage medium (Claim 14), each comprising instructions to carry out the method of Claim 1. Zhang et al. (‘577) in view of Martin et al. (‘799) teaches Claims 13 and 14.
Zhang et al. (‘577) teaches: Non-transitory computer program or set of non-transitory computer programs comprising computer-readable instructions configured, when executed on a computer or set of computers, to cause the computer or set of computers to carry out the method according to claim 1. ([0019]: “the system, method and receiver disclosed in this document may comprise a computer-implemented system, method or receiver in which one or more data processors process, store, retrieve, and otherwise manipulate data”; [0053]: “Software instructions and data that are stored in the data storage device 24 may be executed by the data processor 20 to implement any of the blocks, components or modules (e.g., electronic modules, software modules, or both) described in this disclosure document.”) For the same reasons set forth for Claim 1 above, Claims 13 and 14 are unpatentable because they merely require the same method steps to be implemented as software instructions on a computer, which is an obvious and routine implementation choice that does not alter the unpatentability analysis.
Regarding Claim 15, Zhang et al. (‘577) in view of Martin et al. (‘799) teaches the Method according to claim 1, wherein, for the at least one NSS estimator of the NSS estimator set:
Zhang et al. (‘577) teaches: adapting an ionospheric noise model of the NSS estimator based on the ionospheric disturbance information is not performed; ([0130]: “In step S302, the RTK engine, data processor 159 or GNSS receiver is configured to select the preset ionosphere dynamic model.”; [0140]: “In step S302, the preset ionosphere dynamic noise model is based on baseline length and elevation angle for each carrier phase measurement (or differenced carrier phase measurements).”) Zhang teaches a dual (two-stage) error model in which the preset ionosphere dynamic model is applied before ambiguities are fixed. During this stage, the ionospheric noise model is fixed (preset) and is not adapted based on ionospheric disturbance information, thereby satisfying this negative limitation.
Zhang et al. (‘577) teaches: adapting an observation noise model of the NSS estimator based on the ionospheric disturbance information is performed; ([0094]: “In step S206, the RTK engine, error estimator, electronic data processor 159 or GNSS rover receiver 12 is configured to apply a positioning filter with a dual (e.g., two stage) error model or a dual (e.g., two stage) adaptive statistical model. For example, the RTK engine, error estimator, electronic data processor 159 or GNSS rover receiver 12 is configured to apply a positioning filter with a dual (e.g., two stage) error model or a dual (e.g., two stage) adaptive statistical model to estimate residual errors and to fix or to resolve carrier phase ambiguities (e.g., at a minimum target fix rate)”; [0120]: “the electronic data processor 159, the atmospheric modeling module 405, and/or dual error model comprises the adaptive error model … to predict ionospheric activity level for each measurement epoch by epoch.”) Zhang’s adaptive error model adjusts the error/noise model of the positioning filter based on observed ionospheric activity, constituting adapting an observation noise model of the estimator based on ionospheric disturbance information.
Zhang et al. (‘577) does not explicitly teach, but Martin et al. (‘799) teaches: and the following is further performed: switching the NSS estimator to ionospheric free observations. ([0141]: “The Kalman filter makes it possible to perform both carrier code smoothing and “iono-free” combination.”; [0143]: “In the case of dual-frequency measurements, “iono-free” combination of signals at two different frequencies normally allows the ionospheric error to be eliminated.”)
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to combine the dual-stage ionospheric error modeling of Zhang et al. (‘577) with the ionospheric-free observation switching of Martin et al. (‘799). One would have been motivated to do so in order to switch the estimator to ionospheric-free observations when ionospheric disturbance exceeds a threshold, thereby eliminating ionospheric error entirely through the well-known iono-free combination technique when adapting the noise model alone is insufficient to maintain positioning accuracy ([0141], [0143]).
Regarding Claim 16, Claim 16 is a system claim that recites essentially the same limitations as method Claim 15, except for the preamble reciting the System of Claim 11. Zhang et al. (‘577) in view of Martin et al. (‘799) teaches Claim 16 for the same reasons set forth for Claim 15 above, applied to the system configuration of Claim 11.
Zhang et al. (‘577) teaches: adapting an ionospheric noise model of the NSS estimator based on the ionospheric disturbance information is not performed; ([0130]: “In step S302, the RTK engine, data processor 159 or GNSS receiver is configured to select the preset ionosphere dynamic model. For example, in step S302 the preset ionosphere model will be applied before ambiguities are fixed.”)
Zhang et al. (‘577) teaches: adapting an observation noise model of the NSS estimator based on the ionospheric disturbance information is performed; ([0120]: “the atmospheric modeling module 405, and/or dual error model comprises the adaptive error model, such as a system, method or software instructions storable in the data storage device 155, to predict ionospheric activity level for each measurement epoch by epoch.”)
Zhang et al. (‘577) does not explicitly teach, but Martin et al. (‘799) teaches: and the following is further performed: switching the NSS estimator to ionospheric free observations. ([0141]: “The Kalman filter makes it possible to perform both carrier code smoothing and “iono-free” combination.”; [0143]: “In the case of dual-frequency measurements, “iono-free” combination of signals at two different frequencies normally allows the ionospheric error to be eliminated. In the method according to the invention, this method is useful when one of the two frequencies is no longer available and the measurement ends up single frequency.”) It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to combine the dual-stage ionospheric error modeling system of Zhang et al. (‘577) with the ionospheric-free observation switching of Martin et al. (‘799). One would have been motivated to do so in order to switch the system’s estimator to ionospheric-free observations when ionospheric disturbance is elevated, eliminating ionospheric error through the iono-free combination technique when noise model adaptation alone is insufficient ([0141], [0143]).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to REMASH R GUYAH whose telephone number is (571)270-0115. The examiner can normally be reached M-F 7:30-4:30.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Resha H Desai can be reached at (571) 270-7792. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/REMASH R GUYAH/Examiner, Art Unit 3648
/RESHA DESAI/Supervisory Patent Examiner, Art Unit 3648