Title :
Joint Sigma-Point Kalman Filter Based Bearing-Only Tracking
Author :
Hou, Daiwen ; Yin, Fuliang ; Zhang, Liyan
Author_Institution :
Sch. of Electron. & Inf. Eng., Dalian Univ. of Technol.
Abstract :
A novel joint sigma-point Kalman filter algorithm is proposed to solve the problems of slow convergence rate and biased state estimation when systematic error exists in bearing-only target tracking. The algorithm can eliminate the effect of systematic error to the state estimation as well as reduce linearization error. The simulation results demonstrate the validity of the proposed algorithm
Keywords :
Kalman filters; state estimation; target tracking; tracking filters; bearing-only target tracking; joint sigma-point Kalman filter based bearing-only tracking; linearization error reduction; sigma-point transformation; state estimation; Acoustic measurements; Convergence; Electromagnetic measurements; Electromagnetic radiation; Filtering; Filters; Noise measurement; Radar tracking; State estimation; Target tracking; Bearing-only tracking; Kalman filter; sigma-point transformation; systematic error;
Conference_Titel :
Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on
Conference_Location :
Dalian
Print_ISBN :
1-4244-0332-4
DOI :
10.1109/WCICA.2006.1712483
