Smart Target Tracking Using Sensor Scheduling and Particle Filter

摘要：

This paper addresses the problem of tracking a “smart target,wherein the issue of the observers concealment against the target should be taken into account,as a smart target is able to detect when it is under surveillance and react in a manner that makes future surveillance more difficult.This work proposes a sensor scheduling strategy (SSS),which balances the tracking performance and the concealing quality of the observer.This SSS uses an approach known as covariance control,to reduce the use of the active sensor whilst guaranteeing the estimation accuracy.A robust unscented particle filtering (UPF) method is utilized to deal with the nonlinear and non-Gaussian problem.Meanwhile,a Rao-Blackwellised technique is adopted to improve the estimation performance and reduce the computational burdens.Results based on experiments with synthetic data are reported.

作者: Bin Liu Xiaochuan Ma Chaohuan Hou

作者单位: Graduate University,Chinese Academy of Sciences;Institute of Acoustics,Chinese Academy of Sciences Institute of Acoustics,Chinese Academy of Sciences

会议类型: 国际会议

会议名称: 9th International Conference on Signal Processing(第九届国际信号处理学术会议)(ICSP08)

会议地点: 北京

会议语种:英文

在线出版日期: 2008-10-26（万方平台首次上网日期，不代表论文的发表时间）