31 May 1996 Retrodiction for Bayesian multiple-hypothesis/multiple-target tracking in densely cluttered environment
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Abstract
Sensor data processing in a dense target/dense clutter environment is inevitably confronted with data association conflicts which correspond with the multiple hypothesis character of many modern approaches (MHT: multiple hypothesis tracking). In this paper we analyze the efficiency of retrodictive techniques that generalize standard fixed interval smoothing to MHT applications. 'Delayed estimation' based on retrodiction provides uniquely interpretable and accurate trajectories from ambiguous MHT output if a certain time delay is tolerated. In a Bayesian framework the theoretical background of retrodiction and its intimate relation to Bayesian MHT is sketched. By a simulated example with two closely-spaced targets, relatively low detection probabilities, and rather high false return densities, we demonstrate the benefits of retrodiction and quantitatively discuss the achievable track accuracies and the time delays involved for typical radar parameters.
© (1996) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Wolfgang Koch, Wolfgang Koch, } "Retrodiction for Bayesian multiple-hypothesis/multiple-target tracking in densely cluttered environment", Proc. SPIE 2759, Signal and Data Processing of Small Targets 1996, (31 May 1996); doi: 10.1117/12.241204; https://doi.org/10.1117/12.241204
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