一种变换状态空间的稳定卡尔曼滤波算法
A Robust Extended Kalman Filter Based on Transforming State Space
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摘要: 该文在分析了扩展卡尔曼滤波中两种线性化误差的产生原因及其对滤波影响的基础上,针对线性状态方程和非线性观测方程这一类系统,提出了采用一组新的状态量代替原来的状态量,使得观测方程为线性方程,从而避免了因为观测方程线性化导致的观测空间和状态空间的映射关系改变,提高了扩展卡尔曼滤波的稳定性和状态估计的精度。通过一个无源定位与跟踪的计算机仿真试验验证了这种方法的优点。Abstract: 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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