Adaptive Tracking Algorithm Based on Modified Strong Tracking Filter

Author

You, He ; Qiang, Song ; Yun-long, Dong ; Jian, Yang

Author_Institution

Res. Inst. of Inf. Fusion, Naval Aeronaut. Eng. Inst., Yantai

fYear

2006

fDate

16-19 Oct. 2006

Firstpage

1

Lastpage

4

Abstract

The strong tracking filter (STF) can reduce adaptively estimate bias and thus has ability to track maneuvering target in nonlinear systems. However, STF achieves the perfect performance in maneuvering segment at a cost of the precision in non-maneuvering segment. So based on the strong tracking filter, a new adaptive tracking algorithm (modified strong tracking filter, MSTF) is derived in this paper, which is also suitable for tracking maneuvering target and has improved the precision of STF in non-maneuvering segment as well as maneuvering segment. The Monte-Carlo simulation results show that the MSTF algorithm has a more excellent performance than STF and can estimate efficiently

Keywords

Monte Carlo methods; adaptive filters; nonlinear systems; target tracking; tracking filters; MSTF; Monte-Carlo simulation; adaptive tracking algorithm; maneuvering target tracking; modified strong tracking filter; nonlinear system; Adaptive filters; Costs; Covariance matrix; Gaussian noise; Gaussian processes; Nonlinear systems; Robustness; State estimation; Target tracking; White noise; Strong Tracking Filter; extended Kalman filter; target tracking;

fLanguage

English

Publisher

ieee

Conference_Titel

Radar, 2006. CIE '06. International Conference on

Conference_Location

Shanghai

Print_ISBN

0-7803-9582-4

Electronic_ISBN

0-7803-9583-2

Type

conf

DOI

10.1109/ICR.2006.343192

Filename

4148298