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Volume 27 Issue 6
Jun.  2005
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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.

A Robust Extended Kalman Filter Based on Transforming State Space

  • Received Date: 2004-02-06
  • Rev Recd Date: 2004-09-17
  • Publish Date: 2005-06-19
  • 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.
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  • 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-
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