Robust Adaptive Kalman Filtering – a method based on quasi-accurate detection and plant noise variance–covariance matrix tuning

In this paper, we propose an algorithm for tuning both the kinematic and measurement noise Variance–Covariance (VCV) matrices to produce a more robust and adaptive Kalman filter. The proposed algorithm simultaneously considers both observation outliers and abrupt changes. This algorithm may be divided into two basic parts: 1. Robust estimation, from which the position components of the filtering estimates and the equivalent weight factor matrix can be obtained; and 2. Adaptive estimation, from which the adaptive kinematic noise VCV tuning matrix is calculated. To demonstrate the efficiency of our algorithm, we process a set of kinematic Global Positioning System (GPS) data received from a rover mounted on an aeroplane. The processing results are found to be very satisfactory, with observation outliers and abrupt changes detected and dealt with accordingly. The detailed calculation procedure for the adaptive VCV tuning matrix is also described.

[1]  Yuanxi Yang,et al.  Comparison of Adaptive Factors in Kalman Filters on Navigation Results , 2005 .

[2]  Dengping Duan,et al.  Adaptive robust Kalman filter for relative navigation using global position system , 2013 .

[3]  Cui,et al.  Adaptively robust filtering with classified adaptive factors , 2006 .

[4]  Jinling Wang,et al.  Adaptive estimation of multiple fading factors in Kalman filter for navigation applications , 2008 .

[5]  Qin Zhang,et al.  Insar Unwrapping Error Correction Based on Quasi-Accurate Detection of Gross Errors (quad) , 2018 .

[6]  A. Jazwinski.  Stochastic Processes and Filtering Theory , 1970 .

[7]  P.J.G. Teunissen.  Quality control in integrated navigation systems , 1990, IEEE Symposium on Position Location and Navigation. A Decade of Excellence in the Navigation Sciences.

[8]  Halil Ersin Soken,et al.  Robust Adaptive Kalman Filter for estimation of UAV dynamics in the presence of sensor/actuator faults , 2013 .

[9]  Yuanxi Yang,et al.  An Optimal Adaptive Kalman Filter , 2006 .

[10]  Yuanxi Yang,et al.  Robust Kalman filter for rank deficient observation models , 1998 .

[11]  Jikun Ou,et al.  Quasi-Accurate Detection of Outliers for Correlated Observations , 2007 .

[12]  P.J.G. Teunissen,et al.  Quality control in integrated navigation systems , 1990, IEEE Aerospace and Electronic Systems Magazine.

[13]  Yuanxi Yang,et al.  Adaptively robust filtering for kinematic geodetic positioning , 2001 .

[14]  A.H. Haddad,et al.  Applied optimal estimation , 1976, Proceedings of the IEEE.

[15]  W. Baarda,et al.  A testing procedure for use in geodetic networks. , 1968 .

[16]  Wei Li,et al.  Robust adaptive filtering method for SINS/SAR integrated navigation system , 2011 .

[17]  Fredrik Gustafsson,et al.  Adaptive filtering and change detection , 2000 .