DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the
first inventor to file provisions of the AIA .
Response to Amendments
The amendment filed 06/04/2026 has been entered.
Claims 1, 11, 21, and 28 are amended.
Claims 4-6, 14-16, and 24-26 were previously cancelled.
Claims 1-3, 7-13, 17-23, and 27-30 are pending.
Claim Rejections - 35 USC § 103
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 (i.e., changing from AIA to pre-AIA ) 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.
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 1-2, 8-10, 11-12, 18-22, and 28-29 are rejected under 35 U.S.C. 103 as being unpatentable over Lie (US 2017/0299728) in view of Dai (US 2009/0102708) and Ford (US 6,664,923).
Regarding Claim 1, Lie teaches:
A positioning method for a mobile device ([0004]), comprising:
obtaining a pseudorange observation for a positioning epoch and a carrier phase observation for the positioning epoch based on measurements of global navigation satellite system (GNSS) signals transmitted by one or more space vehicles (SVs) of a GNSS constellation ([0004]: "a real-time kinematic (RTK) mode"; "relative position mode"; [0027]: "pseudo-range and integrated carrier phase"; [0040]: "constellation of satellites");
generating a differential carrier phase observation for the positioning epoch based on the carrier phase observation for the positioning epoch and a determination that real-time kinematic (RTK) correction data associated with the GNSS constellation is unavailable ([0004]: "Upon loss of the RTK correction signal, the navigation positioning estimator or controller switches to a relative position mode"; "The relative position estimator determines an estimated relative position based on time-differenced phase measurements"; [0035]; [0050]: "extended RTK mode"); and
generating a position, velocity, … observation of the mobile device for the positioning epoch, according to a … Kalman filter … based positioning model, based on the differential carrier phase observation for the positioning epoch ([0004]: "estimated relative position"; [0044]: "the precise clock solutions or clock biases in the correction data 16 can be used to estimate the precise position, attitude, or velocity (e.g., solution) of the mobile receiver 12."; [0065]; [0171]: “the relative position estimator 124 or any of the bias estimators may comprise a Kalman filter”; [0172]).
Lie does not explicitly teach:
generating a position, velocity, and time (PVT) observation;
an extended Kalman filter (EKF)-based positioning model; or
wherein an estimation state vector for the EKF-based positioning model of the positioning epoch corresponding to a current epoch is predicted based on a state vector for a preceding positioning epoch and a state transition matrix, and simultaneously comprises at least one of: both a current epoch position term and a previous epoch position term, or both a current epoch clock term and a previous epoch clock term.
However, Dai is in the field of satellite navigation positioning (Dai [Abstract]) teaches:
generating a position, velocity, and time (PVT) observation (Dai [0012]: “the position, velocity and time (PVT)”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Lie to generate a position, velocity, and time (PVT) observation, as taught by Dai, with a reasonable expectation of success. In GNSS applications, position and velocity estimates must be associated with a time in order to provide an accurate navigation solution, and including a time observation with position and velocity observations is beneficial for enhancing position and velocity measurements and enabling additional applications, such as timestamping.
Furthermore, Ford is in the field of GNSS positioning (Ford [Abstract]) and teaches:
an extended Kalman filter (EKF)-based positioning model (Ford [col. 2]: “Kalman filter”; Examiner note: although Ford does not explicitly state that the Kalman filter is an extended Kalman filter, the equations for the filter in Ford [col. 3, lines 37-40] are equivalent to equations 3 and 4 in Applicant’s specification [0066]); and
wherein an estimation state vector for the EKF-based positioning model of the positioning epoch corresponding to a current epoch is predicted based on a state vector for a preceding positioning epoch and a state transition matrix (Ford [col. 3, lines 37-40]: “The Kalman filter propagates a State vector X and a variance covariance matrix P as: State: x t(−)=Φxt−1(+)”; “Φ is the state transition matrix”), and simultaneously comprises at least one of: both a current epoch position term and a previous epoch position term, or both a current epoch clock term and a previous epoch clock term (Ford [Abstract]: “Using both the current and the previous position related information in the filter”; [col. 6, lines 60-67]: “current position error vector”; “previous position error vector”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Lie and use an EKF-based positioning model wherein an estimation state vector for the EKF-based positioning model of the positioning epoch corresponding to a current epoch is predicted based on a state vector for a preceding positioning epoch and a state transition matrix, and simultaneously comprises at least one of: both a current epoch position term and a previous epoch position term, or both a current epoch clock term and a previous epoch clock term, as taught by Ford, with a reasonable expectation of success. Applying Ford’s EKF-based positioning technique to Lie’s navigation system yields the predictable result of providing an accurate positioning solutions with reduced noise (Ford [col. 2, lines 20-23]).
Regarding Claim 11, Lie teaches:
A positioning apparatus for a mobile device, comprising:
a global navigation satellite system (GNSS) receiver ([0004]: “satellite navigation receiver”);
a memory ([0026]: “data storage devices”); and
one or more processors communicatively coupled with the GNSS receiver and the memory ([0026]: “data processors”), wherein the one or more processors are configured to:
obtain a pseudorange observation for a positioning epoch and a carrier phase observation for the positioning epoch based on measurements of GNSS signals transmitted by one or more space vehicles (SVs) of a GNSS constellation ([0004]; [0027]; [0040]);
generate a differential carrier phase observation for the positioning epoch based on the carrier phase observation for the positioning epoch and a determination that real-time kinematic (RTK) correction data associated with the GNSS constellation is unavailable ([0004]; [0035]; [0050]); and
generate a position, velocity, … observation of the mobile devices, according to an … Kalman filter … based positioning model, for the positioning epoch based on the differential carrier phase observation for the positioning epoch ([0004]; [0044]; [0065]; [0171-0172]).
Lie does not explicitly teach:
generating a position, velocity, and time (PVT) observation;
an extended Kalman filter (EKF)-based positioning model; or
wherein an estimation state vector for the EKF-based positioning model of the positioning epoch corresponding to a current epoch is predicted based on a state vector for a preceding positioning epoch and a state transition matrix, and simultaneously comprises at least one of: both a current epoch position term and a previous epoch position term, or both a current epoch clock term and a previous epoch clock term.
However, Dai is in the field of satellite navigation positioning (Dai [Abstract]) teaches:
generating a position, velocity, and time (PVT) observation (Dai [0012]: “the position, velocity and time (PVT)”).
The rationale to modify Lie with the teachings of Dai persists from Claim 1.
Furthermore, Ford is in the field of GNSS positioning (Ford [Abstract]) and teaches:
an extended Kalman filter (EKF)-based positioning model (Ford [col. 2]: “Kalman filter”; Examiner note: although Ford does not explicitly state that the Kalman filter is an extended Kalman filter, the equations for the filter in Ford [col. 3, lines 37-40] are equivalent to equations 3 and 4 in Applicant’s specification [0066]); and
wherein an estimation state vector for the EKF-based positioning model of the positioning epoch corresponding to a current epoch is predicted based on a state vector for a preceding positioning epoch and a state transition matrix (Ford [col. 3, lines 37-40]: “The Kalman filter propagates a State vector X and a variance covariance matrix P as: State: x t(−)=Φxt−1(+)”; “Φ is the state transition matrix”), and simultaneously comprises at least one of: both a current epoch position term and a previous epoch position term, or both a current epoch clock term and a previous epoch clock term (Ford [Abstract]: “Using both the current and the previous position related information in the filter”; [col. 6, lines 60-67]: “current position error vector”; “previous position error vector”).
The rationale to modify Lie with the teachings of Ford persists from Claim 1.
Regarding Claim 21, Lie teaches:
A non-transitory computer-readable medium storing instructions for positioning for a mobile device ([0004]; [0026]), the instructions comprising code for:
obtaining a pseudorange observation for a positioning epoch and a carrier phase observation for the positioning epoch based on measurements of global navigation satellite system (GNSS) signals transmitted by one or more space vehicles (SVs) of a GNSS constellation ([0004]; [0027]; [0040]);
generating a differential carrier phase observation for the positioning epoch based on the carrier phase observation for the positioning epoch and a determination that real-time kinematic (RTK) correction data associated with the GNSS constellation is unavailable ([0004]; [0035]; [0050]); and
generating a position, velocity, … observation of the mobile device for the positioning epoch, according to an … Kalman filter … based positioning model, based on the differential carrier phase observation for the positioning epoch ([0004]; [0044]; [0065]; [0171-0172]).
Lie does not explicitly teach:
generating a position, velocity, and time (PVT) observation;
an extended Kalman filter (EKF)-based positioning model; or
wherein an estimation state vector for the EKF-based positioning model of the positioning epoch corresponding to a current epoch is predicted based on a state vector for a preceding positioning epoch and a state transition matrix, and simultaneously comprises at least one of: both a current epoch position term and a previous epoch position term, or both a current epoch clock term and a previous epoch clock term.
However, Dai is in the field of satellite navigation positioning (Dai [Abstract]) teaches:
generating a position, velocity, and time (PVT) observation (Dai [0012]: “the position, velocity and time (PVT)”).
The rationale to modify Lie with the teachings of Dai persists from Claim 1.
Furthermore, Ford is in the field of GNSS positioning (Ford [Abstract]) and teaches:
an extended Kalman filter (EKF)-based positioning model (Ford [col. 2]: “Kalman filter”; Examiner note: although Ford does not explicitly state that the Kalman filter is an extended Kalman filter, the equations for the filter in Ford [col. 3, lines 37-40] are equivalent to equations 3 and 4 in Applicant’s specification [0066]); and
wherein an estimation state vector for the EKF-based positioning model of the positioning epoch corresponding to a current epoch is predicted based on a state vector for a preceding positioning epoch and a state transition matrix (Ford [col. 3, lines 37-40]: “The Kalman filter propagates a State vector X and a variance covariance matrix P as: State: x t(−)=Φxt−1(+)”; “Φ is the state transition matrix”), and simultaneously comprises at least one of: both a current epoch position term and a previous epoch position term, or both a current epoch clock term and a previous epoch clock term (Ford [Abstract]: “Using both the current and the previous position related information in the filter”; [col. 6, lines 60-67]: “current position error vector”; “previous position error vector”).
The rationale to modify Lie with the teachings of Ford persists from Claim 1.
Regarding Claim 28, Lie teaches:
A positioning apparatus for a mobile device ([0004]; [0026]), comprising:
means for obtaining a pseudorange observation for a positioning epoch and a carrier phase observation for the positioning epoch based on measurements of global navigation satellite system (GNSS) signals transmitted by one or more space vehicles (SVs) of a GNSS constellation ([0004]; [0027]; [0040]);
means for generating a differential carrier phase observation for the positioning epoch based on the carrier phase observation for the positioning epoch and a determination that real-time kinematic (RTK) correction data associated with the GNSS constellation is unavailable ([0004]; [0035]; [0050]); and
means for generating a position, velocity, … observation of the mobile device for the positioning epoch, according to an … Kalman filter … based positioning model, based on the differential carrier phase observation for the positioning epoch ([0004]; [0044]; [0065]; [0171-0172]).
Lie does not explicitly teach:
generating a position, velocity, and time (PVT) observation;
an extended Kalman filter (EKF)-based positioning model; or
wherein an estimation state vector for the EKF-based positioning model of the positioning epoch corresponding to a current epoch is predicted based on a state vector for a preceding positioning epoch and a state transition matrix, and simultaneously comprises at least one of: both a current epoch position term and a previous epoch position term, or both a current epoch clock term and a previous epoch clock term.
However, Dai is in the field of satellite navigation positioning (Dai [Abstract]) teaches:
generating a position, velocity, and time (PVT) observation (Dai [0012]: “the position, velocity and time (PVT)”).
The rationale to modify Lie with the teachings of Dai persists from Claim 1.
Furthermore, Ford is in the field of GNSS positioning (Ford [Abstract]) and teaches:
an extended Kalman filter (EKF)-based positioning model (Ford [col. 2]: “Kalman filter”; Examiner note: although Ford does not explicitly state that the Kalman filter is an extended Kalman filter, the equations for the filter in Ford [col. 3, lines 37-40] are equivalent to equations 3 and 4 in Applicant’s specification [0066]); and
wherein an estimation state vector for the EKF-based positioning model of the positioning epoch corresponding to a current epoch is predicted based on a state vector for a preceding positioning epoch and a state transition matrix (Ford [col. 3, lines 37-40]: “The Kalman filter propagates a State vector X and a variance covariance matrix P as: State: x t(−)=Φxt−1(+)”; “Φ is the state transition matrix”), and simultaneously comprises at least one of: both a current epoch position term and a previous epoch position term, or both a current epoch clock term and a previous epoch clock term (Ford [Abstract]: “Using both the current and the previous position related information in the filter”; [col. 6, lines 60-67]: “current position error vector”; “previous position error vector”).
The rationale to modify Lie with the teachings of Ford persists from Claim 1.
Regarding Claims 2, 12, 22, and 29, Lie as modified teaches: generating the … observation of the mobile device for the positioning epoch based on the differential carrier phase observation for the positioning epoch and a … observation of the mobile device for a preceding positioning epoch ([0004]: "based a last available RTK position."; "time-differenced"; [0073]: "estimate the position of the mobile receiver (or its antenna 17) with respect to an initial reference position (e.g., the last known RTK position)"; [0137]: "Kalman filter").
Lie as modified does not explicitly teach – but Dai teaches:
the PVT observation (Dai [0012]).
The rationale to modify Lie with the teaching of Dai persist from Claim 1.
Regarding Claims 8, 18, and 27, Lie as modified teaches:
obtaining a pseudorange observation for a second positioning epoch and a carrier phase observation for the second positioning epoch based on measurements of GNSS signals transmitted by one or more SVs of a second GNSS constellation ([0027]: "pseudo-range and integrated carrier phase"; [0059]: "one or more GNSS satellite constellations"; [0120]: "a first measurement time and a second measurement time"; [0121]: "receives a real-time kinematic (RTK) signal"; [0124]: "determines a precise position");
determining that RTK correction data associated with the second GNSS constellation is available ([0122]: "received RTK correction data"; [0126]: "if the RTK signal is not lost, interrupted, corrupted");
generating a corrected pseudorange observation and a corrected carrier phase observation based on the pseudorange observation for the second positioning epoch, the carrier phase observation for the second positioning epoch, and the RTK correction data associated with the second GNSS constellation ([0122]: "determines a real-time kinematic position for the first measurement time based on the measured carrier phase of the received satellite signals and the received RTK correction data"; [0127]: "waits an interval prior to returning to step S500 for another iteration";);
generating a differential carrier phase observation for the second positioning epoch based on the carrier phase observation for the second positioning epoch ([0120]: "carrier phase"; [0122]: "RTK"; [0124]: "precise position"); and
generating a … observation of the mobile device for the second positioning epoch … ([0044]; [0122]: "real-time kinematic position"; "RTK correction data"; [0124]: "precise position"; "precise correction data").
Lie as modified does not explicitly teach – but Dai teaches:
generating a PVT observation of the mobile device for the second positioning epoch based on the corrected pseudorange observation, the corrected carrier phase observation, and the differential carrier phase observation for the second positioning epoch (Dai [0006]: "the corrections cancel or significantly mitigate most of the noise sources in the pseudorange and/or carrier phase measurements."; [0009]: "The WADGPS techniques that employ a carrier-phase differential method can also achieve very high navigational accuracy."; [0010]: " combining the use of the standard RTK and the WADGPS navigation techniques"; [0012]: "PVT").
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Lie and generate a PVT observation of the mobile device for the second positioning epoch based on the corrected pseudorange observation, the corrected carrier phase observation, and the differential carrier phase observation for the second positioning epoch, as taught by Dai, with a reasonable expectation of success. Combining the corrected pseudorange observation, the corrected carrier phase observation, and the differential carrier phase observation to generate a PVT observation is beneficial for improving the accuracy of the PVT observations (Dai [0012]).
Regarding Claims 9 and 19, Lie as modified does not explicitly teach – but Dai teaches: generating the PVT observation of the mobile device for the second positioning epoch based on the corrected pseudorange observation, the corrected carrier phase observation, the differential carrier phase observation for the second positioning epoch, and a PVT observation of the mobile device for a positioning epoch preceding the second positioning epoch (Dai [0006]; [0009-0010]; [0012]: “After this offset has been determined, the RTK PVT outputs, adjusted by the offset, can be used subsequently to initialize the WADGPS system.").
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Lie and generate a PVT observation of the mobile device for the second positioning epoch based on the corrected pseudorange observation, the corrected carrier phase observation, the differential carrier phase observation for the second positioning epoch, and a PVT observation of the mobile device for a positioning epoch preceding the second positioning epoch, as taught by Dai, with a reasonable expectation of success. Combining the corrected pseudorange observation, the corrected carrier phase observation, the differential carrier phase observation, and a previous PVT observation to generate a PVT observation is beneficial for improving the accuracy of the PVT observations (Dai [0012]).
Regarding Claims 10 and 20, Lie as modified teaches: obtaining the RTK correction data associated with the second GNSS constellation from one or more base stations ([0048]: "correction data (e.g., local RTK correction data) from a real-time kinematic (RTK) base station 430.").
Claims 3, 13, 23, and 30 are rejected under 35 U.S.C. 103 as being unpatentable over Lie (US 2017/0299728) in view of Dai (US 2009/0102708) and Ford (US 6,664,923), as applied to Claims 1, 11, 21, and 28 above, and further in view of Gou (US 2014/0350885).
Regarding Claims 3, 13, 23, and 30, Lie as modified teaches: discarding the pseudorange observation for the positioning epoch in response to the determination that the RTK correction data associated with the GNSS constellation is unavailable … ([0004]: "Upon loss…"; "time-differenced phase measurements").
Lie as modified does not explicitly teach: discarding the pseudorange observation for the positioning epoch in response to … a determination that a residual error associated with the pseudorange observation for the positioning epoch exceeds a threshold.
However, Gou is in the field of satellite positioning (Guo [Abstract]) and teaches: discarding the pseudorange observation for the positioning epoch in response to … a determination that a residual error associated with the pseudorange observation for the positioning epoch exceeds a threshold (Gou [0034]: "If an error between the residual pseudo-range error and the first predetermined threshold is beyond a predetermined range, the positioning data can be discarded.").
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Lie and discard the pseudorange observation for the positioning epoch in response to a determination that a residual error associated with the pseudorange observation for the positioning epoch exceeds a threshold, as taught by Gou, with a reasonable expectation of success. Discarding the pseudorange observation based on a residual error exceeding a threshold is beneficial for improving the accuracy of positioning measurements (Gou [0006]).
Claim 7 and 17 are rejected under 35 U.S.C. 103 as being unpatentable over Lie (US 2017/0299728) in view of Dai (US 2009/0102708), and Ford (US 6,664,923), as applied to Claims 1 and 11 above, and further in view of Averin (US 2024/0219577).
Regarding Claims 7 and 17, Lie as modified teaches: wherein generating the … observation of the mobile device for the positioning epoch according to the … positioning model includes conducting a differential carrier phase measurement …, wherein the differential carrier phase measurement … does not include updating a clock term ([0039]: “Single difference”; “double difference”; [0096]; [0137]).
Lie as modified does not explicitly teach:
the PVT observation;
the EKF-based positioning model; or
conducting a differential carrier phase measurement update based on a selection of a reference SV, wherein the differential carrier phase measurement update does not include updating a clock term
However, Dai teaches: the PVT observation (Dai [0012]).
The rationale to modify Lie with the teachings of Dai persists from Claim 1.
Furthermore, Ford teaches: the EKF-based positioning model (Ford [col. 2]: “Kalman filter”; [col. 3, lines 37-40]).
The rationale to modify Lie with the teachings of Ford persists from Claim 1.
Furthermore, Averin is in the field of GNSS (Averin [Abstract]) and teaches: conducting a differential carrier phase measurement update based on a selection of a reference SV, wherein the differential carrier phase measurement update does not include updating a clock term (Averin [0007]: “carrier phase”; [Claim 12]: "(vi) the external processor selects a reference GNSS satellite and computes double differences between the single difference for the reference satellite and the single differences for other satellites;").
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Lie to conduct a differential carrier phase measurement update based on a selection of a reference SV, wherein the differential carrier phase measurement update does not include updating a clock term, as taught by Averin, with a reasonable expectation of success. Updating measurements after selecting a reference SV is well-known and is beneficial for improving the accuracy of satellite receiver position measurements (Averin [0007]).
Response to Arguments
Applicant’s arguments, filed 06/04/2026, with respect to Claim Rejections under 35 U.S.C. 103 have been considered but are moot because they do not apply to the specific combination of references being used in the current rejection.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to NOAH Y. ZHU whose telephone number is (571) 270-0170. The examiner can normally be reached Monday-Friday, 8AM-4PM.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Vladimir Magloire, can be reached on (571) 270-5144. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/NOAH YI MIN ZHU/Examiner, Art Unit 3648
/BRADY W FRAZIER/Primary Examiner, Art Unit 3648
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