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SICE 2001. Proceedings of the 40th SICE Annual Conference. International Session Papers (IEEE Cat. No.01TH8603)
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  ., 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 baseddoi:10.1109/sice.2001.977851 fatcat:bhrrbg64zjhlnaqsuj46cwoyxm