Unscented Kalman Filters for Multiple Target Tracking With Symmetric Measurement Equations

被引:75
作者
Leven, William F. [1 ]
Lanterman, Aaron D. [1 ]
机构
[1] Georgia Inst Technol, Sch Elect & Comp Engn, Atlanta, GA 30332 USA
关键词
Extended Kalman filter; nonlinear filtering; NONLINEAR TRANSFORMATION; COVARIANCES;
D O I
10.1109/TAC.2008.2008327
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The symmetric measurement equation approach to multiple target tracking is revisited using the unscented Kalman filter. The performance of this filter is compared to the original symmetric measurement equation implementation using an extended Kalman filter. Counterintuitive results are presented and explained for two sets of symmetric measurement equations. We find that the performance of the SME approach is dependent on the interaction of the SME equations and filter used. Furthermore, an SME/unscented Kalman filter pairing is shown to have improved performance versus previous approaches while possessing simpler implementation and equivalent computational complexity.
引用
收藏
页码:370 / 375
页数:6
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