Bayesian Adaptative Filter For Multiple Maneuvering Target Tracking With Measurements Of Uncertain Origin

B. Tomasini; M. Gauvrit; B. Siffredi

doi:10.1117/12.960354

5 September 1989 Bayesian Adaptative Filter For Multiple Maneuvering Target Tracking With Measurements Of Uncertain Origin

B. Tomasini, M. Gauvrit, B. Siffredi

Author Affiliations +

Proceedings Volume 1096, Signal and Data Processing of Small Targets 1989; (1989) https://doi.org/10.1117/12.960354
Event: SPIE 1989 Technical Symposium on Aerospace Sensing, 1989, Orlando, FL, United States

Abstract

The Joint Probabilistic Data Association Filter (JPDAF) has been successfully used for tracking multiple targets in the presence of source uncertainty and measurement inaccuracy. In this field and using this technic, the problem of multiple manoeuvring target tracking will be considered. The aim of this paper concerns the extension of the Adaptative Probabilistic Data Association Filter (APDAF) in reference to monotarget tracking to the multitarget tracking problem. This Adaptative Joint Probabilistic Data Association Filter (AJPDAF) estimates the state of each target in a cluttered environment when the noise statistics are unknown. Simulation results on multiple manoeuvring target tracking using simulation data are presented.

Citation Download Citation

B. Tomasini, M. Gauvrit, and B. Siffredi "Bayesian Adaptative Filter For Multiple Maneuvering Target Tracking With Measurements Of Uncertain Origin", Proc. SPIE 1096, Signal and Data Processing of Small Targets 1989, (5 September 1989); https://doi.org/10.1117/12.960354

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