TARGET TRACKING WITH DISTANCE-DEPENDENT MEASUREMENT NOISE IN WIRELESS SENSOR NETWORKS

被引:0
|
作者
Hu, Xiaoqing [1 ]
Xu, Bugong [1 ]
Hu, Yu Hen [2 ]
机构
[1] South China Univ Technol, Sch Automat Sci & Engn, Guangzhou, Guangdong, Peoples R China
[2] Univ Wisconsin, Dept Elect & Comp Engn, Madison, WI 53706 USA
来源
2013 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP) | 2013年
关键词
Wireless sensor networks; extended Kalman filtering; target tracking; distance-dependent;
D O I
暂无
中图分类号
O42 [声学];
学科分类号
070206 ; 082403 ;
摘要
A distributed extended Kalman filter (EKF) algorithm is developed for tracking moving targets in a wireless sensor network equipped with distance estimating sensors. In particular, a distance-dependent measurement error of range-estimating sensors is modeled as a multiplicative noise in the observation model. A new formulation of EKF, called generalized EKE (GEKF) based on the multiplicative noise model is developed. Compared to conventional EKF formulation, it is shown that GEKF can achieve smaller estimation error than traditional EKF. Simulation results also demonstrated superior performance of GEKF.
引用
收藏
页码:5200 / 5203
页数:4
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