Title :
Lyapunov stability of a tracking filter with the uncertainty of measurement origin
Author :
Kim, Yong-Shik ; Hong, Keum-Shik
Author_Institution :
Dept. of Mech. & Intelligent Syst. Eng., Pusan Nat. Univ., South Korea
Abstract :
The probabilistic data association filter (PDAF) is known to provide better tracking performance than the standard Kalman filter (KF) in a cluttered environment. In this paper, the stability of the PDAF of Fortmann et al. (1985), in the presence of uncertainties with regard to the origin of measurement, is investigated. The modified Riccati equation derived by approximating two random terms with their expectations is used to evaluate the stability of the PDAF. A new Lyapunov function based approach, which is different from the quantitative evaluation of Li and Bar-Shalom (1991), is pursued. With the assumption that the system and observation noises are bounded, specific tracking error bounds are established
Keywords :
Lyapunov matrix equations; Riccati equations; filtering theory; noise; stability; state estimation; target tracking; Kalman filter; Lyapunov stability; PDAF; bounded observation noises; bounded system; cluttered environment; measurement origin uncertainty; modified Riccati equation; probabilistic data association filter; tracking error bounds; tracking filter; Convergence; Filters; Lyapunov method; Measurement uncertainty; Riccati equations; Signal processing algorithms; Stability analysis; State estimation; Steady-state; Target tracking;
Conference_Titel :
SICE 2001. Proceedings of the 40th SICE Annual Conference. International Session Papers
Conference_Location :
Nagoya
Print_ISBN :
0-7803-7306-5
DOI :
10.1109/SICE.2001.977851
