TY - GEN
T1 - The GPS/INS integrated navigation method based on adaptive SSR-SCKF cubature Kalman filter
AU - Yue, Zhe
AU - Lian, Baowang
AU - Tang, Chengkai
N1 - Publisher Copyright:
© Springer Nature Singapore Pte Ltd. 2017.
PY - 2017
Y1 - 2017
N2 - There are many methods aiming at the nonlinear problem of GPS/INS integrated navigation, such as EKF and UKF, however, these methods have low positioning accuracy and instability. On the study of SCKF and nonlinear model of GPS/INS integrated navigation, aiming at the issues that the state equation of GPS/INS is nonlinear while the measured equation is linear, and the measured noise changes owing to the changing number of visible satellites or multipath. Therefore, this paper promotes the integrated method based on adaptive SSR-SCKF, which uses the spherical simple-radial cubature rule (SSRCR) to set the cubature sampling points. We also provide a linear measured update process on the basis of singular value decomposition (SVD), and it avoids choosing the cubature sampling points. Combining the moving window method, it can adjust the covariance matrix of measurement noise in real-time. The experiment results show that the proposed method has lower computational complexity, while higher estimated accuracy, numerical stability and better adaptive ability to the changing noise than SCKF in the same conditions.
AB - There are many methods aiming at the nonlinear problem of GPS/INS integrated navigation, such as EKF and UKF, however, these methods have low positioning accuracy and instability. On the study of SCKF and nonlinear model of GPS/INS integrated navigation, aiming at the issues that the state equation of GPS/INS is nonlinear while the measured equation is linear, and the measured noise changes owing to the changing number of visible satellites or multipath. Therefore, this paper promotes the integrated method based on adaptive SSR-SCKF, which uses the spherical simple-radial cubature rule (SSRCR) to set the cubature sampling points. We also provide a linear measured update process on the basis of singular value decomposition (SVD), and it avoids choosing the cubature sampling points. Combining the moving window method, it can adjust the covariance matrix of measurement noise in real-time. The experiment results show that the proposed method has lower computational complexity, while higher estimated accuracy, numerical stability and better adaptive ability to the changing noise than SCKF in the same conditions.
KW - Adaptive
KW - GPS/INS integrated navigation
KW - Singular value decomposition
KW - SSR-SCKF
UR - https://www.scopus.com/pages/publications/85019238141
U2 - 10.1007/978-981-10-4591-2_32
DO - 10.1007/978-981-10-4591-2_32
M3 - 会议稿件
AN - SCOPUS:85019238141
SN - 9789811045905
T3 - Lecture Notes in Electrical Engineering
SP - 395
EP - 405
BT - China Satellite Navigation Conference, CSNC 2017 Proceedings
A2 - Sun, Jiadong
A2 - Yu, Wenxian
A2 - Liu, Jingnan
A2 - Yang, Yuanxi
A2 - Fan, Shiwei
PB - Springer Verlag
T2 - 8th China Satellite Navigation Conference, CSNC 2017
Y2 - 23 May 2017 through 25 May 2017
ER -