Efficient estimation of hybrid systems with applications to tracking

Yuzhen Xue and Thordur Runolfsson

International Journal of Systems Science, 2012, vol. 43, issue 12, 2228-2239

Abstract: Particle filtering has been recognised as a superior alternative to the traditional estimation methods as it is applicable to nonlinear/non-Gaussian system. A central issue in real-time applications of particle filtering is its high computational cost. This problem is compounded when it is used in hybrid system estimation. A new particle filtering method for nonlinear/non-Gaussian hybrid system estimation is proposed in this article. The new method integrates the high-accuracy interacting multiple model particle filtering algorithm with the computationally efficient observation and transition-based most likely modes tracking particle filtering algorithm to get high-accuracy estimation with reduced computational load. The algorithm is applied to a manoeuvring target tracking application to demonstrate its efficiency.

Date: 2012
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DOI: 10.1080/00207721.2011.566641

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