Quasi tightly coupled GNSS-INS integration process
원문보기
IPC분류정보
국가/구분
United States(US) Patent
등록
국제특허분류(IPC7판)
G01C-021/16
G01S-019/39
G01S-019/47
출원번호
US-0691735
(2012-11-30)
등록번호
US-8825396
(2014-09-02)
발명자
/ 주소
Scherzinger, Bruno M.
출원인 / 주소
Applanix Corporation
대리인 / 주소
Kirk, James F.
인용정보
피인용 횟수 :
0인용 특허 :
10
초록▼
A quasi tightly coupled (QTC) aided INS (AINS) process has an inertial navigator system with a loosely-coupled AINS Kalman filter that constructs INS-GNSS position measurements, a GNSS position engine that computes a position fix from observables and an externally provided a priori position and posi
A quasi tightly coupled (QTC) aided INS (AINS) process has an inertial navigator system with a loosely-coupled AINS Kalman filter that constructs INS-GNSS position measurements, a GNSS position engine that computes a position fix from observables and an externally provided a priori position and position VCV matrix. An INS position seeding process in which the externally provided a priori position to the GNSS position engine is an antenna position computed from the INS position and attitude solution. An observable subspace constraint (OSC) process computes an OCS matrix that suppress the components of the GNSS position error due to a poor geometry in the GNSS position solution in the IG position measurement constructed by the AINS Kalman filter and that multiplies the OSC matrix and the IG position measurement and measurement model matrix to suppress uncorrected component of the GNSS position error in the IG position measurement and measurement model.
대표청구항▼
1. A quasi tightly coupled aided INS (QTC AINS) comprising: a. an inertial navigator (21) mechanization providing an a priori INS position and attitude solution of the antenna (24),b. a loosely-coupled AINS with an AINS Kalman filter (20) that computes an IG position measurement and measurement mode
1. A quasi tightly coupled aided INS (QTC AINS) comprising: a. an inertial navigator (21) mechanization providing an a priori INS position and attitude solution of the antenna (24),b. a loosely-coupled AINS with an AINS Kalman filter (20) that computes an IG position measurement and measurement model and thereby constructs INS-GNSS position measurements and provides an a priori position VCV matrix (23),c. a GNSS position engine (26) that computes a GNSS position fix solution, the GNSS position fix solution having an uncorrected component of a GNSS position error due to an insufficient number of satellites, the GNSS position fix solution using observables from a plurality of satellites provided by a GNSS receiver (22, 25) the externally provided a priori antenna position and the a priori position VCV matrix, the GNSS position engine providing a GNSS antenna position and position variance to the AINS Kalman filter, the AINS Kalman filter providing updated IG-GNSS position measurement and measurement model components,d. an INS position seeding process in which the externally provided a priori antenna position to the GNSS position engine (26) is an antenna position computed from the INS position and attitude solution,e. an observable subspace constraint (OSC) process that i. computes an OSC matrix, having rows and having columns, that suppresses the uncorrected component of the GNSS position error in the GNSS position fix solution in the IG-GNSS position measurement constructed by the AINS Kalman filter, andii. multiplies the OSC matrix and the IG position measurement and measurement model to suppress the uncorrected component of the GNSS position error in the IG position measurement and measurement model. 2. The QTC AINS described in claim 1 in which the AINS is a closed-loop configuration in which the AINS Kalman filter provides estimated INS errors from the AINS Kalman filter that are used to correct the inertial navigator mechanization. 3. The QTC AINS described in claim 1 in which the AINS is a feedforward configuration in which the Kalman filter provides estimated INS errors from the AINS Kalman filter that are used to correct the navigation solution output from the inertial navigator mechanization. 4. The QTC AINS described in claim 1 in which the a priori position VCV matrix to the GNSS position engine is computed from the a priori position VCV matrix. 5. The QTC AINS described in claim 1 in which a kernel or null space of the OSC matrix is the kernel or null space of a satellite-differenced range measurement model matrix Hd as given by a satellite differenced range measurement model matrix, as characterized in Hd=[-Δu_1T⋮-Δu_m-1T]. 6. The QTC AINS described in claim 5 in which the rows of the OSC matrix are transposed right singular vectors corresponding to zero singular values obtained from a singular value decomposition (SVD) of Hd as characterized in Hd=[h_1Th_2Th_3Th_4T].(35) 7. A quasi tightly coupled (QTC) aided INS (AINS) comprising a. an inertial navigator (21) mechanization providing an a priori INS position and attitude solution of an antenna,b. a loosely-coupled AINS Kalman filter (20) that computes an IG position measurement and measurement model and thereby constructs INS-GNSS position measurements and provides an a priori position VCV matrix (23),c. a GNSS position engine (26) that computes a GNSS position fix solution, the GNSS position fix solution having an uncorrected component of a GNSS position error due to a poor geometry of satellites as viewed from the GNSS position, the GNSS position fix solution from observables from a plurality of satellites provided by a GNSS receiver, the externally provided a priori antenna position and the a priori position VCV matrix,d. an INS position seeding process in which the externally provided a priori position to the GNSS position engine is an antenna position computed from the INS position and attitude solution,e. an observable subspace constraint (OSC) process that i. computes an OSC matrix, having rows and having columns, that suppresses the approximately uncorrected component of the GNSS position error in the GNSS position solution in the IG position measurement constructed by the AINS Kalman filter, andii. multiplies the OSC matrix and the IG position measurement and measurement model to suppress the approximately uncorrected component of the GNSS position error in the IG position measurement and measurement model. 8. The QTC AINS described in claim 7 in which the AINS is a closed-loop configuration in which the AINS Kalman filter provides estimated INS errors that are used to correct the inertial navigator mechanization. 9. The QTC AINS described in claim 7 in which the AINS is a feedforward configuration in which the AINS Kalman filter provides estimated INS errors that are used to correct the navigation solution output from the inertial navigator mechanization. 10. The QTC AINS described in claim 7 in which the a priori position VCV matrix to the GNSS position engine is computed from the AINS Kalman filter a priori position VCV matrix. 11. The QTC AINS described in claim 7 in which the kernel or null space of the OSC matrix is the approximate kernel or null space of a satellite differenced range measurement model matrix Hd when it is close to column rank deficiency as determined by a smallest singular value of Hd being smaller than a specified threshold for nearness to column rank deficiency. 12. The QTC AINS described in claim 11 which Hd is defined to be close to rank deficiency when the dilution of precision (DOP) computed as the square root of the sum of diagonal elements of (HdTHd)−1 exceeds a large DOP threshold. 13. The QTC AINS described in claim 12 in which the large singular value threshold for a large singular value is the inverse of the large DOP threshold. 14. The QTC AINS described in claim 11 in which the rows of the OSC matrix are the transposed right singular vectors corresponding to the large singular values obtained from a singular value decomposition (SVD) of Hd. 15. The QTC AINS described in claim 11 in which a singular value is defined to be large if it equals or exceeds a large singular value threshold. 16. A quasi tightly coupled GNSS-INS Integration Process (a QTC Process) for use in a GNSS-INS system for constraining the use of GNSS receiver data derived from observables from m satellites, as the receiver data quality falls to a marginal quality, the QTC process selectively constrains the use of GNSS receiver data to data having a quality that is equal to that which exceeds a predetermined threshold, the QTC process comprising: a GNSS position engine (26) coupled to receive a-priori position VCV data from an AINS Kalman Filter (20), an a-priori position data from an INS (21), and observables from m satellites via a GNSS receiver (22), the GNSS position engine (26) implements a GNSS positioning algorithm to compute a GNSS antenna position fix (28) and an estimation variance-covariance (VCV) matrix,an AINS Kalman filter IG position measurement function (29) coupled to the GNSS position engine to calculate and receive the GNSS antenna position fix (28) and an estimation variance-covariance (VCV matrix) to construct an INS-GNSS (IG) position measurement difference IG data matrix and a measurement model data matrix HIG (30) and transfers the INS-GNSS (IG) position measurement difference IG data matrix and a measurement model data matrix HIG to an OSC process (31),the OSC process uses the INS-GNSS (IG) position measurement difference IG data matrix and a measurement model data matrix HIG to compute the satellite differenced range measurement model matrix Hd, and an SVD of the Hd matrix (41),an OSC constraint test process (47) then uses a portion of the SVD to determine if a number of observables from the m satellites were equal to or greater than a predetermined limit for acceptable quality, the constraint test process allowing the use of GNSS receiver data received within an epoch subject to the GNSS receiver data that is to be used being equal to or exceeding a predetermined quality test limit.
연구과제 타임라인
LOADING...
LOADING...
LOADING...
LOADING...
LOADING...
이 특허에 인용된 특허 (10)
Scherzinger, Bruno; Reid, Blake; Lithopoulos, Erik, AINS land surveyor system with reprocessing, AINS-LSSRP.
※ AI-Helper는 부적절한 답변을 할 수 있습니다.