DocumentCode :
2172604
Title :
Algorithm of Adaptive Fading Memory UKF in Bearings-Only Target Tracking
Author :
Gu, Xiao-Dong ; Yuan, Zhi-Yong ; Qiu, Zhi-Ming
Author_Institution :
Dept. of weaponry Eng., Naval Univ. of Eng., Wuhan, China
fYear :
2009
fDate :
17-19 Oct. 2009
Firstpage :
1
Lastpage :
4
Abstract :
The traditional algorithms applied in bearings-only target tracking have some shortages or disadvantages such as biased, slow convergence or divergence. The UKF algorithm improves the linearization error of system, but it doesn´t amend the robustness of system obviously. In this paper, a new AFMUKF (adaptive fading memory UKF) algorithm is proposed. The AFMUKF algorithm improves the robustness by using a fading factor and effective controls the bad influences of the model errors by using the adaptive factor. The simulation results show that the AFMUKF has better performance than EKF and UKF algorithms in precision, stability and convergence time.
Keywords :
Kalman filters; target tracking; AFMUKF algorithm; adaptive factor; adaptive fading memory UKF; bearings-only target tracking; fading factor; linearization error; unscented Kalman filter; Adaptive control; Convergence; Error correction; Fading; Least squares approximation; Maximum likelihood estimation; Programmable control; Random variables; Stability; Target tracking;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image and Signal Processing, 2009. CISP '09. 2nd International Congress on
Conference_Location :
Tianjin
Print_ISBN :
978-1-4244-4129-7
Electronic_ISBN :
978-1-4244-4131-0
Type :
conf
DOI :
10.1109/CISP.2009.5304730
Filename :
5304730
Link To Document :
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