A BOT algorithm based on sliding window n-step forward prediction

Author

Chunshi, Ma ; Hongqi, Fan ; Zaiqi, Lu

Author_Institution

ATR Lab., Nat. Univ. of Defense Technol., Changsha, China

Volume

2

fYear

2011

fDate

24-27 Oct. 2011

Firstpage

1045

Lastpage

1049

Abstract

Bearing-only tracking (BOT) involves nonlinearity. Extended Kalman filter (EKF) is usually employed for the advantages of efficient computation and real time operation. However, the observability badly declines at a high observation rate, which degrades the filtering performance. In order to address this issue, a BOT algorithm based on sliding window n-step forward prediction is proposed. It enhances the observability effectively, and improves the performance of BOT filter at a high observation rate. Target tracking experiments under different scenarios show that the proposed algorithm has good accuracy and stability, and is suitable for application at a high observation rate.

Keywords

Kalman filters; nonlinear filters; observability; radar tracking; target tracking; bearing-only tracking; extended Kalman filter; observability; observation rate; sliding window n-step forward prediction; target tracking; Accuracy; Estimation error; Filtering; Observability; Prediction algorithms; Target tracking; extended Kalman filter; forward prediction; high observation rate; passive localization; target tracking;

fLanguage

English

Publisher

ieee

Conference_Titel

Radar (Radar), 2011 IEEE CIE International Conference on

Conference_Location

Chengdu

Print_ISBN

978-1-4244-8444-7

Type

conf

DOI

10.1109/CIE-Radar.2011.6159731

Filename

6159731