Stability and convergence of probabilistic data association filters
Serge Prosperi · International Conference on Acoustics, Speech, and Signal Processing · 2003
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.>