Fixed-lag sequential Monte Carlo data association

Mark Briers; Arnaud Doucet; Simon R. Maskell; Paul R. Horridge

doi:10.1117/12.665684

19 May 2006 Fixed-lag sequential Monte Carlo data association

Mark Briers, Arnaud Doucet, Simon R. Maskell, Paul R. Horridge

Proceedings Volume 6236, Signal and Data Processing of Small Targets 2006; 62360S (2006) https://doi.org/10.1117/12.665684
Event: Defense and Security Symposium, 2006, Orlando (Kissimmee), Florida, United States

Abstract

The use of multiple scans of data to improve ones ability to improve target tracking performance is widespread in the tracking literature. In this paper, we introduce a novel application of a recent innovation in the SMC literature that uses multiple scans of data to improve the stochastic approximation (and so the data association ability) of a multiple target Sequential Monte Carlo based tracking system. Such an improvement is achieved by resimulating sampled variates over a fixed-lag time window by artificially extending the space of the target distribution. In doing so, the stochastic approximation is improved and so the data association ambiguity is more readily resolved.

Citation Download Citation

Mark Briers, Arnaud Doucet, Simon R. Maskell, and Paul R. Horridge "Fixed-lag sequential Monte Carlo data association", Proc. SPIE 6236, Signal and Data Processing of Small Targets 2006, 62360S (19 May 2006); https://doi.org/10.1117/12.665684

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