Title :
Stability and convergence of probabilistic data association filters
Author_Institution :
Thomson-Sintra ASM, Cagnes-sur-Mer, France
Abstract :
The author considers the recursive optimal probabilistic filter (PDAF), finds a new expression for its covariance, and analyzes stability versus false alarm density and signal detection probability, showing the relationship between asymptotical stability and practical filter accuracy. Simulation results are given for a bearing-only measurement case (passive sonar), and the PDAF is compared to a single Kalman filter
Keywords :
filtering and prediction theory; probability; signal detection; sonar; stability; bearing-only measurement; convergence; covariance; false alarm density; passive sonar; probabilistic data association filters; recursive optimal probabilistic filter; signal detection probability; stability; tracking; Convergence; Equations; Information filtering; Information filters; Passive filters; Probability; Stability analysis;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1989. ICASSP-89., 1989 International Conference on
Conference_Location :
Glasgow
DOI :
10.1109/ICASSP.1989.267024
