Tracking and Identifying a Magnetic Spheroid Target Using Unscented Particle Filter

摘要：

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 targets track and identification.

关键词： Tracking and identification problem equivalent magnetic spheroid particle filter unscented particle filter

作者: Yang Mingming Liu Darning Lian Liting Yu Zhou

作者单位: School of Electrical and Information Engineering, Naval Univ. of Engineering, Wuhan, Hubei,430033, China

会议类型: 国际会议

会议名称: Third International Conference on Digital Image Processing(ICDIP 2011)(第三届数字图像处理国际会议)

会议地点: 成都

会议语种:英文

页码: 591-595

在线出版日期: 2011-04-15（万方平台首次上网日期，不代表论文的发表时间）