Tracking and identifying a magnetic spheroid target using unscented particle filter

Mingming Yang; Daming Liu; Liting Lian; Zhou Yu

doi:10.1117/12.896676

8 July 2011 Tracking and identifying a magnetic spheroid target using unscented particle filter

Mingming Yang, Daming Liu, Liting Lian, Zhou Yu

Proceedings Volume 8009, Third International Conference on Digital Image Processing (ICDIP 2011); 800931 (2011) https://doi.org/10.1117/12.896676
Event: 3rd International Conference on Digital Image Processing, 2011, Chengdu, China

Abstract

In this paper we use the recursive Bayesian estimation method to solve the tracking and identification problem of a target modeled by an equivalent magnetic spheroid. Target positions, velocity, heading, magnetic moments and size are defined as the state vector, which is estimated from noisy magnetic field measurements by a sequential Monte Carlo based method known as particle filter. In order to improve the performance of the filter, the unscented Kalman filter is applied to generate the transition prior as the proposal distribution. A simulated experiment is given to test the performance of the unscented particle filter, and the results show that the filter is suitable for magnetic target's track and identification.

Citation Download Citation

Mingming Yang, Daming Liu, Liting Lian, and Zhou Yu "Tracking and identifying a magnetic spheroid target using unscented particle filter", Proc. SPIE 8009, Third International Conference on Digital Image Processing (ICDIP 2011), 800931 (8 July 2011); https://doi.org/10.1117/12.896676

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