Gong Xiang-yi, Zhou Liang-zhu. A Robust Extended Kalman Filter Based on Transforming State Space[J]. Journal of Electronics & Information Technology, 2005, 27(6): 896-899.
Citation:
Gong Xiang-yi, Zhou Liang-zhu. A Robust Extended Kalman Filter Based on Transforming State Space[J]. Journal of Electronics & Information Technology, 2005, 27(6): 896-899.
Gong Xiang-yi, Zhou Liang-zhu. A Robust Extended Kalman Filter Based on Transforming State Space[J]. Journal of Electronics & Information Technology, 2005, 27(6): 896-899.
Citation:
Gong Xiang-yi, Zhou Liang-zhu. A Robust Extended Kalman Filter Based on Transforming State Space[J]. Journal of Electronics & Information Technology, 2005, 27(6): 896-899.
Based on the analysis of the effect on the linearization about the measurement equation and state equation, aimed to some system with linear state equation, a new algorithm named as Transforming State Space Extended Kalman Filter (TSS-EKF) is proposed to improve the robust of EKF. Simulation in single observer passive location and tracking validates that this algorithm is robust.
Simon Haykin. Adaptive Filter Theory. Forth Edition, New Jersey:Prentice Hall, 2002, Section 10.10.[2]刘福声,罗鹏飞.统计信号处理,长沙:国防科技大学出版社,1998:6.3节.[3]孙仲康,周一宇.单多基地有源无源定位技术,北京:国防工业出版社,1996:9.2节.[4]Mahalanabis A, Farooq M. A second-order method for state estimation of non-linear dynamical systems, Int[J].J. of Control.1971, 14(4):631-[5]Kwanghee Nam, Min-Jea Tahk. A second-order stochastic filter involving coordinate transformation[J].IEEE Trans. on Automatic Control.1999, 44(3):603-[6]Einicke G A, White L B. Robust extend Kalman filtering[J].IEEE Trans. on Signal Processing.1999, 47(9):2596-