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Proceedings Paper

Tracking and identifying a magnetic spheroid target using unscented particle filter
Author(s): Mingming Yang; Daming Liu; Liting Lian; Zhou Yu
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Paper 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.

Paper Details

Date Published: 8 July 2011
PDF: 5 pages
Proc. SPIE 8009, Third International Conference on Digital Image Processing (ICDIP 2011), 800931 (8 July 2011); doi: 10.1117/12.896676
Show Author Affiliations
Mingming Yang, Naval Univ. of Engineering (China)
Daming Liu, Naval Univ. of Engineering (China)
Liting Lian, Naval Univ. of Engineering (China)
Zhou Yu, Naval Univ. of Engineering (China)

Published in SPIE Proceedings Vol. 8009:
Third International Conference on Digital Image Processing (ICDIP 2011)
Ting Zhang, Editor(s)

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