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 .
Examiner’s Notes
In order for the currently pending claims to be disposed in the most efficient manner, it is recommended that the Applicant further defines the term “accuracy threshold” since it is not clear whether a signal strength, a number of satellites, or another factor constitutes an accuracy threshold. If it is a term of art, it is respectfully requested that the Applicant provides a convincing argument. However, BRI of the term can yield multiple meanings.
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.
Claim 20 is rejected under 35 U.S.C. 101 because the claim contains the language “computer-readable medium storing computer executable code at a user equipment (UE).” Further, paragraph 31 of the specification states “By way of example, such computer-readable media can include a random-access memory (RAM), a read-only memory (ROM), an electrically erasable programmable ROM (EEPROM), optical disk storage, magnetic disk storage, other magnetic storage devices, combinations of the types of computer-readable media, or any other medium that can be used to store computer executable code in the form of instructions or data structures that can be accessed by a computer.” Neither the claim not the specification specifically exclude transitory media.
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 1-3, 6, 9-12, 15-17, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Lou et al (Publication number: US 2022/0283314) in view of Zampetti (Publication number: US 2022/0283316).
Consider Claim 1, Lou et al shows an apparatus for wireless communication at a user equipment (UE) (see figure 1), comprising:
(a) At least one memory; and at least one processor coupled to the at least one memory, based at least in part on stored information that is stored in the at least one memory, the at least one processor, individually or in any combination, is configured to: calibrate a set of inter/intra system/signal time biases (ISTBs) for a set of satellites to meet a first accuracy threshold (see figures 4 and 5; and paragraphs 58-60); (A centralized Kalman filter may be used to process all the baselines and resolve ambiguities (e.g., for RTK) using reference station correction data from multiple reference stations 120. More specifically, according to some embodiments, the centralized Kalman filter can be used to estimate a position (e.g., X, Y, and Z coordinates) of a mobile device, receiver clock errors from each reference station, Inter-Satellite-Type Bias (ISTB), base station tropospheric Zenith delays, and/or other ambiguities. A position determination for a mobile device 110 based on reference station correction data from multiple reference stations 120 can be more accurate and/or faster than a position determination based on reference station correction data from a single reference station 120, because of the multiple constraints included in a multiple-reference method. Additionally or alternatively, the utilization of reference station correction data from multiple reference stations 120 can provide advantages with regard to availability).
(b) Wherein at least two satellites in the set of satellites operate on different frequency bands or are associated with different satellite types; perform, based on the set of calibrated ISTBs, a detection and obtain an output of a positioning engine (PE) module based on the detection information (see figures 6 and 7; and paragraphs 28-30); (The mobile device can then use the correction data (which can include measurement data and location information of the reference station 120, or correction information derived therefrom) to enhance GNSS-based positioning by making corrections to the measured distances to each of the SVs 140. This more accurate position fix may be determined, for example, by a Precise Positioning Engine (PPE) executed by one or more processors of the mobile device 110).
However, Lou et al does not specifically show that the output detection is using solution separation (SS) receiver autonomous integrity monitoring (RAIM) based on outlier detection.
In related art, Zampetti shows that the output detection is using solution separation (SS) receiver autonomous integrity monitoring (RAIM) based on outlier detection (see paragraphs 66-67); (The complemented line of sight finding validation is outlier detection. The rejection of anomalous pseudo range residuals 720 is at least partially based on the use of parallel anomaly classifiers (e.g., path distortion classifier 702, path noise classifier 704, timing receiver autonomous integrity monitoring classifier)).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the application to incorporate the teaching of Zampetti into the teaching of Lou et al in order to achieve more stable precision local timescale (see Zampetti; paragraphs 66 and 67).
Consider Claims 15, Lou et al shows a method of wireless communication at a user equipment (UE) (see figure 1), comprising:
(a) Calibrating a set of inter/intra system/signal time biases (ISTBs) for a set of satellites to meet a first accuracy threshold, wherein at least two satellites in the set of satellites operate on different frequency bands or are associated with different satellite types (see figures 4 and 5; and paragraphs 58-60); (A centralized Kalman filter may be used to process all the baselines and resolve ambiguities (e.g., for RTK) using reference station correction data from multiple reference stations 120. More specifically, according to some embodiments, the centralized Kalman filter can be used to estimate a position (e.g., X, Y, and Z coordinates) of a mobile device, receiver clock errors from each reference station, Inter-Satellite-Type Bias (ISTB), base station tropospheric Zenith delays, and/or other ambiguities. A position determination for a mobile device 110 based on reference station correction data from multiple reference stations 120 can be more accurate and/or faster than a position determination based on reference station correction data from a single reference station 120, because of the multiple constraints included in a multiple-reference method. Additionally or alternatively, the utilization of reference station correction data from multiple reference stations 120 can provide advantages with regard to availability).
(b) Wherein at least two satellites in the set of satellites operate on different frequency bands or are associated with different satellite types; perform, based on the set of calibrated ISTBs, a detection and obtain an output of a positioning engine (PE) module based on the detection information (see figures 6 and 7; and paragraphs 28-30); (The mobile device can then use the correction data (which can include measurement data and location information of the reference station 120, or correction information derived therefrom) to enhance GNSS-based positioning by making corrections to the measured distances to each of the SVs 140. This more accurate position fix may be determined, for example, by a Precise Positioning Engine (PPE) executed by one or more processors of the mobile device 110).
However, Lou et al does not specifically show that the output detection is using solution separation (SS) receiver autonomous integrity monitoring (RAIM) based on outlier detection.
In related art, Zampetti shows that the output detection is using solution separation (SS) receiver autonomous integrity monitoring (RAIM) based on outlier detection (see paragraphs 66-67); (The complemented line of sight finding validation is outlier detection. The rejection of anomalous pseudo range residuals 720 is at least partially based on the use of parallel anomaly classifiers (e.g., path distortion classifier 702, path noise classifier 704, timing receiver autonomous integrity monitoring classifier)).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the application to incorporate the teaching of Zampetti into the teaching of Lou et al in order to achieve more stable precision local timescale (see Zampetti; paragraphs 66 and 67).
Consider Claim 20, Lou et al shows a computer-readable medium storing computer executable code at a user equipment (UE) (see figure 1), the code when executed by at least one processor causes the at least one processor to:
(a) Calibrating a set of inter/intra system/signal time biases (ISTBs) for a set of satellites to meet a first accuracy threshold, wherein at least two satellites in the set of satellites operate on different frequency bands or are associated with different satellite types (see figures 4 and 5; and paragraphs 58-60); (A centralized Kalman filter may be used to process all the baselines and resolve ambiguities (e.g., for RTK) using reference station correction data from multiple reference stations 120. More specifically, according to some embodiments, the centralized Kalman filter can be used to estimate a position (e.g., X, Y, and Z coordinates) of a mobile device, receiver clock errors from each reference station, Inter-Satellite-Type Bias (ISTB), base station tropospheric Zenith delays, and/or other ambiguities. A position determination for a mobile device 110 based on reference station correction data from multiple reference stations 120 can be more accurate and/or faster than a position determination based on reference station correction data from a single reference station 120, because of the multiple constraints included in a multiple-reference method. Additionally or alternatively, the utilization of reference station correction data from multiple reference stations 120 can provide advantages with regard to availability).
(b) Wherein at least two satellites in the set of satellites operate on different frequency bands or are associated with different satellite types; perform, based on the set of calibrated ISTBs, a detection and obtain an output of a positioning engine (PE) module based on the detection information (see figures 6 and 7; and paragraphs 28-30); (The mobile device can then use the correction data (which can include measurement data and location information of the reference station 120, or correction information derived therefrom) to enhance GNSS-based positioning by making corrections to the measured distances to each of the SVs 140. This more accurate position fix may be determined, for example, by a Precise Positioning Engine (PPE) executed by one or more processors of the mobile device 110).
However, Lou et al does not specifically show that the output detection is using solution separation (SS) receiver autonomous integrity monitoring (RAIM) based on outlier detection.
In related art, Zampetti shows that the output detection is using solution separation (SS) receiver autonomous integrity monitoring (RAIM) based on outlier detection (see paragraphs 66-67); (The complemented line of sight finding validation is outlier detection. The rejection of anomalous pseudo range residuals 720 is at least partially based on the use of parallel anomaly classifiers (e.g., path distortion classifier 702, path noise classifier 704, timing receiver autonomous integrity monitoring classifier)).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the application to incorporate the teaching of Zampetti into the teaching of Lou et al in order to achieve more stable precision local timescale (see Zampetti; paragraphs 66 and 67).
Consider Claims 2 and 16, Lou et al shows that the at least one processor, individually or in any combination, is further configured to: re-calibrate, based on the output of the PE module, the set of calibrated ISTBs to meet a second accuracy threshold (see figures 6 and 7; and paragraphs 28-30); (The mobile device can then use the correction data (which can include measurement data and location information of the reference station 120, or correction information derived therefrom) to enhance GNSS-based positioning by making corrections to the measured distances to each of the SVs 140. This more accurate position fix may be determined, for example, by a Precise Positioning Engine (PPE) executed by one or more processors of the mobile device 110).
Consider Claims 3 and 17, Lou et al shows that the second accuracy threshold is lower than the first accuracy threshold (see figures 6 and 7; and paragraphs 28-30); (The mobile device can then use the correction data (which can include measurement data and location information of the reference station 120, or correction information derived therefrom) to enhance GNSS-based positioning by making corrections to the measured distances to each of the SVs 140. This more accurate position fix may be determined, for example, by a Precise Positioning Engine (PPE) executed by one or more processors of the mobile device 110).
Consider Claim 6, Zampetti shows that the at least one processor, individually or in any combination, is further configured to: receive first correction information from a first base station, wherein the calibration of the set of ISTBs is based on the first correction information (see paragraphs 66-67); (The complemented line of sight finding validation is outlier detection. The rejection of anomalous pseudo range residuals 720 is at least partially based on the use of parallel anomaly classifiers (e.g., path distortion classifier 702, path noise classifier 704, timing receiver autonomous integrity monitoring classifier)).
Consider Claims 9-10, Zampetti shows that to obtain the output of the PE module based on the outlier information from the outlier detection, the at least one processor, individually or in any combination, is configured to: generate the output of the PE module based on the outlier information from the outlier detection, wherein the output of the PE module corresponds to a PE solution that includes at least one of: position information, velocity information, timing information, uncertainty information, the outlier information, or integrity information (see paragraphs 66 and 67).
Consider Claim 11, Zampetti shows that to perform, based on the set of calibrated ISTBs, the outlier detection using the SS RAIM, the at least one processor, individually or in any combination, is configured to: provide, to the SS RAIM, the set of calibrated ISTBs for the outlier detection (see paragraphs 66-67); (The complemented line of sight finding validation is outlier detection. The rejection of anomalous pseudo range residuals 720 is at least partially based on the use of parallel anomaly classifiers (e.g., path distortion classifier 702, path noise classifier 704, timing receiver autonomous integrity monitoring classifier)).
Consider Claim 12, Zampetti shows that to obtain the output of the PE module based on the outlier information from the outlier detection, the at least one processor, individually or in any combination, is configured to: compute a position of the UE based on the outlier information from the outlier detection (see paragraphs 66-67); (The complemented line of sight finding validation is outlier detection. The rejection of anomalous pseudo range residuals 720 is at least partially based on the use of parallel anomaly classifiers (e.g., path distortion classifier 702, path noise classifier 704, timing receiver autonomous integrity monitoring classifier)).
Claims 13-14 are rejected under 35 U.S.C. 103 as being unpatentable over Lou et al (Publication number: US 2022/0283314) in view of Zampetti (Publication number: US 2022/0283316) in view of Farmer et al (Publication number: US 2022/0099841).
Consider Claim 13, Lou et al in view of Zampetti do not specifically show that in the at least one processor, individually or in any combination, is further configured to: provide an indication of the output of the PE module.
In related art, Farmer et al shows that in the at least one processor, individually or in any combination, is further configured to: provide an indication of the output of the PE module (see paragraphs 30 and 31).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the application to incorporate the teaching of Farmer et al into the teaching of Lou et al and Zampetti in order to provide an estimated location (see Farmer et al; paragraphs 30 and 31).
Consider claim 14, Farmer et al shows that at least one of a transceiver or an antenna coupled to the at least one processor, wherein to provide the indication of the output of the PE module, the at least one processor, individually or in any combination, is configured to: transmit, to a network entity via at least one of the transceiver or the antenna, the indication of the output of the PE module, or store the indication of the output of the PE module (see paragraphs 30 and 31).
Allowable Subject Matter
Claims 4-5, 7-8, and 18-19 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Conclusion
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/MICHAEL A FARAGALLA/Primary Examiner, Art Unit 2624 01/29/2026