Bayesian approach to avoiding track seduction

David J. Salmond; Nicholas O. Everett

doi:10.1117/12.478523

7 August 2002 Bayesian approach to avoiding track seduction

Proceedings Volume 4728, Signal and Data Processing of Small Targets 2002; (2002) https://doi.org/10.1117/12.478523
Event: AeroSense 2002, 2002, Orlando, FL, United States

Abstract

The problem of maintaining track on a primary target in the presence spurious objects is addressed. Recursive and batch filtering approaches are developed. For the recursive approach, a Bayesian track splitting filter is derived which spawns candidate tracks if there is a possibility of measurement misassociation. The filter evaluates the probability of each candidate track being associated with the primary target. The batch filter is a Markov-chain Monte Carlo (MCMC) algorithm which fits the observed data sequence to models of target dynamics and measurement-track association. Simulation results are presented.

Citation Download Citation

David J. Salmond and Nicholas O. Everett "Bayesian approach to avoiding track seduction", Proc. SPIE 4728, Signal and Data Processing of Small Targets 2002, (7 August 2002); https://doi.org/10.1117/12.478523

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