DETAILED ACTION
This Office Action is in response to Applicant's response to application filed on 10 February 2025. Currently, claims 1-30 are pending. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
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 1-30 are clearly drawn to at least one of the four categories of patent eligible subject matter recited in 35 U.S.C. 101 (system, method and non-transitory computer readable medium). Claims 1-30 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more. Claims 1, 11 and 21 recites the abstract idea of identifying a launch window for a launch vehicle by receiving constraint data associated with launch operations, the constraint data comprising at least one of terrestrial, atmospheric, orbital, or operational constraints derived from monitoring systems, historical records, or predictive models and normalizing the received constraint data into a standardized format by performing operations comprising resolving inconsistencies, aligning measurement units to a common scale, and structuring data for computational analysis into numerical, categorical, or vectorized representations and generating a constraint graph based on the standardized constraint data, the constraint graph comprising nodes representing individual constraints and edges representing interdependencies between the constraints and identifying a plurality of time intervals from the constraint graph, wherein each time interval is associated with a computed metric indicating constraint overlap across the time interval and computing a confidence score for each identified time interval based on a statistical analysis of historical launch outcomes, monitoring data, and predictions generated by models trained to evaluate constraint variability and operational feasibility and selecting a launch window from the identified time intervals based on the confidence scores, wherein the selected launch window corresponds to the time interval with the highest confidence score and satisfies predefined launch criteria associated with safety, resource availability, and regulatory compliance and adjusting at least one operational parameter associated with the launch based on the selected launch window, wherein the adjustment comprises modifying a trajectory profile, rescheduling ground operations, or reallocating resources at the launch site to align with the selected window. The claims are directed to a type of adjusting parameters based on received data which is analyzed and computed upon. Under prong 1 of Step 2A, these claims are considered abstract because the claims are concepts performed in the mind including observation, evaluation and opinion and mathematical concepts and relationships. Applicant’s claims are concepts performed in the mind including observation, evaluation and opinion because the claims are analyzing data and generating graphs to make an observation or evaluation over related parameters. The claims also are mathematical concepts because the claims are generating a constraint graph based on received data to compute a confidence score and make adjustments to a parameter. Under prong 2 of Step 2A, the judicial exception is not integrated into a practical application because the claims (the judicial exception and any additional elements individually or in combination such as a space launch service platform (SLSP) computing system, comprising: a processing system comprising one or more processors configured to perform steps and computer-implemented method and real-time monitoring system, machine learning models and non-transitory processor-readable storage medium having stored thereon processor-executable instructions configured to cause a processing system in a computing device to perform operations) are not an improvement to a computer or a technology, the claims do not apply the judicial exception with a particular machine, the claims do not effect a transformation or reduction of a particular article to a different state or thing nor do the claims apply the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment such that the claims as a whole is more than a drafting effort designed to monopolize the exception. These limitations at best are merely implementing an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.05(f). Under Step 2B, the claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements individually or in combination such as a space launch service platform (SLSP) computing system, comprising: a processing system comprising one or more processors configured to perform steps and computer-implemented method and real-time monitoring system, machine learning models and non-transitory processor-readable storage medium having stored thereon processor-executable instructions configured to cause a processing system in a computing device to perform operations (as evidenced by para [0055]-[0079], [0113]-[0119], [0204], [0422-[0425], [0696]-[0706] of applicant’s own specification) are well understood, routine and conventional in the field. Dependent claims 2-3, 5, 7-9, 12-13, 15 17, 19, 22-23, 25, 27-29 also do not include additional elements that integrate the judicial exception into a practical application because the additional elements either individually or in combination are merely an extension of the abstract idea itself by further showing generating a launch readiness report comprising the selected launch window, adjusted operational parameters, and an evaluation of constraint satisfaction and wherein receiving the constraint data further comprises aggregating terrestrial object data, orbital object data, weather data, upper atmospheric data, and operational data from multiple sources, including real-time monitoring systems, historical databases, and predictive modeling systems, and to categorize the received constraint data into structured datasets corresponding to predefined categories for terrestrial, atmospheric, orbital, and operational parameters and wherein generating the constraint graph comprises mapping temporal relationships between airspace availability, maritime clearance zones, weather conditions, and orbital conjunction risks, wherein the constraint graph encodes interdependencies among constraints to enhance the accuracy of launch feasibility assessments and wherein selecting the launch window further comprises generating a ranked list of alternative launch windows, each associated with a respective confidence score, to provide contingency options in response to real-time changes in constraint conditions and modifying a planned trajectory of the launch vehicle based on real-time updates to constraint data to remain in compliance with airspace, maritime, and orbital clearance regulations. Dependent claims 4, 6, 10, 14, 16, 18-20, 24, 26-30 does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements individually or in combination such as wherein normalizing the received constraint data further comprises applying an artificial intelligence model configured to correct inconsistencies, fill missing values, and classify the constraint data into predefined categories and wherein computing the confidence score for each identified time interval comprises executing a machine learning model trained on historical launch schedules, atmospheric conditions, mission outcomes, and real-time constraint variability to predict the likelihood of satisfying operational criteria and monitoring real-time updates to constraint data; and dynamically adjusting the selected launch window to accommodate changes in constraint conditions and maintain compliance with predefined operational requirements and in response to real-time changes and executing a reinforcement learning model to iteratively refine the launch window selection by incorporating feedback from prior launches and updating machine learning parameters based on historical and real-time performance data (as evidenced by para [0055]-[0079], [0113]-[0119], [0204], [0422-[0425], [0696]-[0706] of applicant’s own specification) are well understood, routine and conventional in the field.
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.
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 1-2, 7-8, 11-12, 17-18, 21-22, 27-28 are rejected under 35 U.S.C. 103 as being unpatentable over Catledge et al. (US 2020/0377234 A1), (hereinafter Catledge) in view of Rothschild (US 2019/0297456 A1) in view of Anand (US 10,152,349 B1).
Claims 1, 11 and 21:
Catledge, as shown, discloses the following limitations of claims 1, 11 and 21:
A space launch service platform (SLSP) computing system (and corresponding method and non-transitory computer readable medium - see para [0089]-[0092], showing equivalent computing functionality and components), comprising: a processing system comprising one or more processors (see para [0002], "The systems, methods, devices, and non-transitory media of the various embodiments provide a dynamic space launch opportunity determination and coordination system that provides space launch customers and authorities with a live indication when a given space launch is both safe and compliant with launch objectives, dynamic launch window criteria. For ease of reference the system that receives data inputs and determines when safe and compliant launch windows are available is referred to herein as a “space launch service platform,” which is not to be confused with a physical platform." And see para [0089]-[0092], showing equivalent computing functionality and components ) configured to: receive constraint data associated with launch operations, the constraint data comprising at least one of terrestrial, atmospheric, orbital, or operational constraints derived from real-time monitoring systems, historical records, or predictive models (see para [0003], ", the space launch service platform may receive data feeds from various static and dynamic data sources including, for example, satellite and orbital debris catalogs, airspace tracking systems, maritime tracking systems, weather monitoring systems, and range monitoring systems. In various embodiments, the space launch service platform may receive monitoring data from various launch site and launch vehicle sensors, such as frequency and global positioning system data, telemetry data, optics and surveillance data, and data from technicians at the launch site. In various embodiments, the space launch service platform may combine the data feeds and monitoring data and apply condition-based launch criteria to the combined data to dynamically determine launch windows and/or provide go/no-go decisions for a launch opportunity to a launch provide" and see para [0057], "Various embodiments may provide Air/Sea/Orbit Surveillance and Coordination type services that provide coordination tools necessary to ensure safe flight while operating in the air/sea/space domains. In various embodiments, surveillance and coordination services may provide the coordination tools necessary to ensure safe flight while operating in the air/sea/space domains. Air Surveillance and Coordination may be provided by data feeds from flight tracking tools, such as those provided by FlightAware of Texas. Data evaluating and aggregating over 10,000 aircraft position messages per second may be processed and fused into a global flight data feed providing position and flight status data during all phases of the flight. Sea Surveillance and Coordination may track vessels on the ocean providing vessel positions, journey data, port calls, schedules, and higher order intelligence delivered timely and efficiently to satisfy our customer's needs and the company is a global ship tracking intelligence service.");
select a launch window from the identified time intervals based on the confidence scores, wherein the selected launch window corresponds to the time interval with the highest confidence score and satisfies predefined launch criteria associated with safety, resource availability, and regulatory compliance (see para [0052], "The space launch service platform 606 may combine the monitoring data 604 and/or data feeds 602 into combined launch data and may apply condition-based launch criteria to the combined launch data to determine whether a launch opportunity is present or not. In some embodiments, the space launch service platform 606 may indicate a launch opportunity in response to the condition-based launch criteria being met. For example, the space launch service platform 606 may indicate a go decision to a launch provider 608 in response to the condition-based launch criteria being met. In some embodiments, the space launch service platform 606 may indicate a no-go decision in response to the condition-based launch criteria not being met. In various embodiments the indication of a launch opportunity may be human readable, such as a visual message or icon displayed on a screen, and/or may be machine readable. Machine readable indications may support automated launch procedures in various embodiments. In various embodiments, the space launch service platform 606 may be configured to display at least a portion of the combined data in a graphical user interface, such as via a web portal and/or IPTV feed provided to a computing device of a launch provider 608 or other users."); and
adjust at least one operational parameter associated with the launch based on the selected launch window, wherein the adjustment comprises modifying a trajectory profile, rescheduling ground operations, or reallocating resources at the launch site to align with the selected window (see para [0066]-[0070], showing such data is applied to launch criteria to determine the launch window dynamically)
Catledge does not specifically disclose normalize the received constraint data into a standardized format by performing operations comprising resolving inconsistencies, aligning measurement units to a common scale, and structuring data for computational analysis into numerical, categorical, or vectorized representation. In analogous art, Rothschild discloses the following limitations:
normalize the received constraint data into a standardized format by performing operations comprising resolving inconsistencies, aligning measurement units to a common scale, and structuring data for computational analysis into numerical, categorical, or vectorized representations (see para [0055], "Subsequently to collecting location information 46, the processor (i) selects at least some of the interval-area pairs, (ii) normalizes those weights 48 corresponding to the selected interval-area pairs, such as to yield a plurality of normalized weights 52, and then (iii) constructs a respective one-dimensional or two-dimensional location-history vector 50 for each of the tracked subjects, by assigning, to the vector, those normalized weights 52 that correspond to the subject (i.e., that correspond to respective combinations of the subject with the selected interval-area pairs). In other words, the processor constructs, for each of the tracked subjects, a vector 50 of normalized weights 52, where each normalized weight 52 corresponds to a different respective selected interval-area pair. For example, FIG. 2 shows, for Subject A, a normalized weight of 12,345 for the interval-area pair (Interval 1, Area 1), indicated in FIG. 2 by the notation “(I1, A1).” The paragraphs below provide further description with regards to the construction of vectors 50.");
compute a confidence score for each identified time interval based on a statistical analysis of historical launch outcomes, real-time monitoring data, and predictions generated by machine learning models trained to evaluate constraint variability and operational feasibility (see para [0053], "Typically, each of the weights is calculated in response to the percentage of the time interval during which the subject was located in the geographic area that is indicated by the tracking data. Alternatively or additionally, the processor may calculate a level of confidence that the tracking data indicate that the subject was located in the geographic area during the time interval, and then calculate the weight responsively to the level of confidence. For example, a particular tracking signal received by the processor may indicate the location of the subject with relatively little precision, such that the signal effectively specifies a range of possible locations for the subject, spanning a plurality of geographic areas. In such a case, the processor may calculate a respective level of confidence for each of the geographic areas, responsively to the percentage of the range that is included within the geographic area. The processor may then calculate the respective weights for the geographic areas, based on these levels of confidence." where it is obvious to one of ordinary skill in the art that the confidence for each interval could be for launch outcomes which is another type of data that is monitored just like location of subjects);
It would have been obvious to one or ordinary skill in the art at the time of the invention to combine the teachings of Rothschild with Catledge because including such normalization of data enables more effective analysis to be made of data dependent on geospatial ranges (see Rothschild, para [0001]-[0007]).
Moreover, it would have been obvious to one of ordinary skill in the art at the time of the invention to include the method for identifying associated subjects from location histories as taught by Rothschild in the system of identification of launch opportunities of Catledge, since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
Catledge and Rothschild, however, do not specifically disclose generate a constraint graph based on the standardized constraint data, the constraint graph comprising nodes representing individual constraints and edges representing interdependencies between the constrains. In analogous art, Anand discloses the following limitations:
generate a constraint graph based on the standardized constraint data, the constraint graph comprising nodes representing individual constraints and edges representing interdependencies between the constraints (col 3, lin3 4-33, "(10) FIGS. 1A-1D are diagrams of an overview of an example implementation 100 described herein. As shown in FIG. 1A, and by reference number 110, a network device (e.g., a kernel of a network device) may receive and store information that identifies a set of tasks to be executed and precedence constraints associated with the set of tasks. For example, the network device may store the set of tasks (e.g., tasks associated with routing protocol processes, interface processes, security processes, etc.) in the form of a DAG. For example, the DAG may include a set of nodes, where nodes represent tasks and edges represent precedence constraints. That is, the directed edge from “Task A” to “Task B” indicates that “Task A” is to be executed before “Task B” (e.g., “Task B” may depend on “Task A” for a computational result). Additionally, as an example, the directed edges from “Task B,” “Task C,” and “Task D” to “Task E” indicate that “Task E” depends on computational results of “Task B,” “Task C,” and “Task D.” As shown in FIG. 1B, and by reference number 120, the network device may determine a set of paths based on the information that identifies the set of tasks and precedence constraints associated with the set of tasks. For example, a path may include a set of nodes that are ordered based on precedence constraints. As shown, “Paths 1, 2, and 3” may share a common entry node (e.g., “Task A”), and may share a common exit node (e.g., “Task E”). That is, an entry node may include a node that does not include a parent node, and an exit node may include a node that does not include a child node. As further shown, “Paths 1, 2, and 3” include different intermediate nodes (e.g., “Tasks B, C, and D,” respectively).");
identify a plurality of time intervals from the constraint graph, wherein each time interval is associated with a computed metric indicating constraint overlap across the time interval (col 1, line 23 to col 2, line 8, "The one or more processors may determine a set of paths based on the information that identifies the set of tasks and the precedence constraints associated with the set of tasks. Each path, of the set of paths, may include particular tasks of the set of tasks. The one or more processors may determine a set of path execution times, for the set of paths, based on an artificial intelligence technique. The one or more processors may determine a critical path, of the set of paths, based on the set of path execution times. The one or more processors may determine an execution priority of the set of tasks based on the critical path. The one or more processors may provide the set of tasks for execution based on the execution priority. According to some possible implementations, a non-transitory computer-readable medium may store one or more instructions that, when executed by one or more processors of a device, cause the one or more processors to receive information that identifies a set of tasks to be executed and precedence constraints associated with the set of tasks. The one or more instructions may cause the one or more processors to store the information that identifies the set of tasks and the precedence constraints in a form of a directed acyclic graph. The one or more instructions may cause the one or more processors to determine, based on the directed acyclic graph, a set of paths. The one or more instructions may cause the one or more processors to determine a set of path execution times for the set of paths. The one or more instructions may cause the one or more processors to determine a critical path of the set of paths based on the set of path execution times. The one or more instructions may cause the one or more processors to determine an execution priority of the set of tasks based on the critical path. The one or more instructions may cause the one or more processors to provide the set of tasks for execution based on the execution priority. According to some possible implementations, a method may include receiving, by a device, information that identifies a set of tasks to be executed and precedence constraints associated with the set of tasks. The method may include storing, by the device and based on the precedence constraints, the information that identifies the set of tasks in association with a directed acyclic graph. The method may include determining, by the device, a set of paths based on the directed acyclic graph. The method may include determining, by the device, a set of path execution times, for the set of paths, based on an artificial intelligence technique. The method may include determining, by the device, a critical path, of the set of paths, based on the set of path execution times. The method may include determining, by the device, an execution priority of the set of tasks based on the critical path. The method may include providing, by the device and to one or more processing units of the device, the set of tasks for execution based on the execution priority.");
It would have been obvious to one or ordinary skill in the art at the time of the invention to combine the teachings of Anand with Catledge and Rothschild because including a constraint graphs enhances the ability to assign resources to complete the tasks (see Anand, col 1, line 7-35).
Moreover, it would have been obvious to one of ordinary skill in the art at the time of the invention to include the system identifies a set of tasks to be executed and precedence constraints associated with the set of tasks as taught by Anand in the Catledge and Rothschild combination, since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
Claims 2, 12 and 22:
Further, Catledge discloses the following limitations:
wherein the processing system is configured to generate a launch readiness report comprising the selected launch window, adjusted operational parameters, and an evaluation of constraint satisfaction (see para [0056], "In various embodiments, the required L-COLA calculations may be performed and the results provided to the spaceport and the launch customer with a report of launch conjunction time intervals to avoid within the designated launch window.")
Claims 7-8, 17-18, 27-28:
Further, Catledge discloses the following limitations:
wherein the processing system is configured to select the launch window by generating a ranked list of alternative launch windows, each associated with a respective confidence score, to provide contingency options in response to real-time changes in constraint conditions (see para [0069]-[0073], where the different windows and opportunities and recommendations provided can be considered alternate windows which are integrated with the various real time monitoring data)
wherein the processing system is configured to: monitor real-time updates to constraint data (see para [0064-[0082], showing real time monitoring of all the condition data); and
dynamically adjust the selected launch window to: accommodate changes in constraint conditions (see para [0064]-[0082], especially para [0078], " In various embodiments, the method may be periodically repeated, such as once every minute to dynamically determine whether a launch criteria is or is not met in real-time and/or near real-time."); and
maintain compliance with predefined operational requirements (see para [0002], "The systems, methods, devices, and non-transitory media of the various embodiments provide a dynamic space launch opportunity determination and coordination system that provides space launch customers and authorities with a live indication when a given space launch is both safe and compliant with launch objectives, dynamic launch window criteria. For ease of reference the system that receives data inputs and determines when safe and compliant launch windows are available is referred to herein as a “space launch service platform,” which is not to be confused with a physical platform.")
Claims 3, 9, 13, 19, 23, 29 are rejected under 35 U.S.C. 103 as being unpatentable over Catledge, Rothschild and Anand, as applied above, and further in view of Catledge et al, (US 2021/0094703 A1) (hereinafter Catledge 2)
Claims 3, 9, 13, 19, 23, 29:
Catledge, Rothschild and Anand do not specifically disclose wherein the processing system is configured to modify a planned trajectory of the launch vehicle based on real-time updates to constraint data to remain in compliance with airspace, maritime, and orbital clearance regulations. In analogous art, Catledge 2 discloses the following limitations:
wherein the processing system is configured to receive constraint data by aggregating terrestrial object data, orbital object data, weather data, upper atmospheric data, and operational data from multiple sources, including real-time monitoring systems, historical databases, and predictive modeling systems, and to categorize the received constraint data into structured datasets corresponding to predefined categories for terrestrial, atmospheric, orbital, and operational parameters (see para [0096], "Various embodiments may include receiving known launch/recovery factors from a launch customer. The known launch/recovery factors may include orbital mission parameters, launch vehicle performance information, and pre-launch sequence and timing information. The known launch/recovery factors may be determined by the launch customer. Various embodiments may include determining predictive launch/recovery constraints. The predictive launch/recovery constraints may be determined by a space launch service platform. The predictive launch/recovery constraints may be determined by a space launch service platform may be determined based at least in part on the known launch/recovery factors. The predictive launch/recovery constraints may include aviation traffic information, marine traffic information, orbital traffic information (e.g., satellite, debris, etc. information), weather information (e.g., wind information, solar information, lightning information, moisture information, etc.), and frequency information. Various embodiments may include determining day of launch (DOL) opportunities. DOL opportunities may be determined based at least in part on evaluating, comparing, and adjusting predictive launch/recovery constraints to ensure compliance with user and regulatory requirements. In various embodiments, predictive launch/recovery constraints may forecast actual DOL opportunities using historical air, maritime, orbital traffic routes, predictive weather modeling, and frequency monitoring starting seventy-two hours prior to a goal launch time.")
wherein the processing system is configured to modify a planned trajectory of the launch vehicle based on real-time updates to constraint data to remain in compliance with airspace, maritime, and orbital clearance regulations (see para [0096], "Various embodiments may include receiving known launch/recovery factors from a launch customer. The known launch/recovery factors may include orbital mission parameters, launch vehicle performance information, and pre-launch sequence and timing information. The known launch/recovery factors may be determined by the launch customer. Various embodiments may include determining predictive launch/recovery constraints. The predictive launch/recovery constraints may be determined by a space launch service platform. The predictive launch/recovery constraints may be determined by a space launch service platform may be determined based at least in part on the known launch/recovery factors. The predictive launch/recovery constraints may include aviation traffic information, marine traffic information, orbital traffic information (e.g., satellite, debris, etc. information), weather information (e.g., wind information, solar information, lightning information, moisture information, etc.), and frequency information. Various embodiments may include determining day of launch (DOL) opportunities. DOL opportunities may be determined based at least in part on evaluating, comparing, and adjusting predictive launch/recovery constraints to ensure compliance with user and regulatory requirements. In various embodiments, predictive launch/recovery constraints may forecast actual DOL opportunities using historical air, maritime, orbital traffic routes, predictive weather modeling, and frequency monitoring starting seventy-two hours prior to a goal launch time.")
It would have been obvious to one or ordinary skill in the art at the time of the invention to combine the teachings of Catledge 2 with Catledge, Rothschild and Anand because integrating such constraints enables more safe space launches (see Catledge 2, para [0001]-[0004]).
Moreover, it would have been obvious to one of ordinary skill in the art at the time of the invention to include the system for identifying launch windows as taught by Catledge 2 in the Catledge, Rothschild and Anand combination, since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
Allowable Subject Matter
Claims 4-6, 10, 14-16, 20, 24-26, 30 would be allowable if rewritten to overcome the rejections under 35 U.S.C. 101, set forth in this Office action and to include all of the limitations of the base claim and any intervening claims.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Tanygin (US 2013/0024102 A1), a system for determining a launch window from anywhere within a specified area to avoid or minimize close approaches between a launch vehicle and orbiting space objects
Liu et al. (CN 112525001 B), a method of carrier rocket emission window where determining the launch window of the carrier rocket comprises: obtaining the orbit point of the satellite in the point of intersection point, entering the orbit moment descending point geographic longitude, the time zone geographic longitude of the emitting point, the allowable deviation value when entering the point of the intersection point and the theoretical flight time of the carrier rocket and the theoretical flight time deviation; according to the point of intersection geographic longitude and the time zone geographic longitude of the emitting point, determining the geographical time difference between the descending point of the satellite at the track entering time and the emitting point; according to the theoretical flight time and theoretical flight time deviation, determining the relative time range of carrier rocket emission and flight; according to the point of arrival at the point of intersection, geographic time difference, relative time range and allowable deviation value, determining the launch window of the carrier rocket
Yim et al. "Generation of launch windows for high-accuracy lunar trajectories", a paper on establishing in arbitrary timespan a full set of instantaneous ground launch windows for certain accurate three-dimensional asymmetric free return circumlunar trajectories tailored to human lunar missions for China, and in general propose a novel methodology useful for determining ground launch windows for other Earth-to-Moon trajectories.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to SUJAY KONERU whose telephone number is 571-270-3409. The examiner can normally be reached on Monday-Friday, 9 am to 5 pm.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Patricia Munson can be reached on 571- 270-5396. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/SUJAY KONERU/
Primary Examiner, Art Unit 3624
Prosecution Insights