26 November 2001 Efficient one-scan-back PDAF for target tracking in clutter
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In this paper we present an efficient one-scan-back Probabilistic Data Filter (PDAF). Regarding the general case of an N-scan-back PDAF, it has been noted in the literature that with each additional scan back, there is a considerable increase in computational load while the amount of improvement in tracking performance diminishes. We therefore have designed a filter that aims to benefit at a minimal increase in computational cost from the one-scan-back architecture that effectively rules out unlikely measurement pairings. In this filter, we use the measurements in previous scan only to produce better weights for the measurements in the present scan. Thus, as compared to a "full" one-scan-back PDAF, we considerably reduce the number of updating and merging steps each scan. For the proposed filter, and the closely related "standard" (zero-scan-back) PDAF and "full" one-scan-back PDAF, we provide the theoretical background, numerical implementation, and simulation results.
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Jitse H. Zwaga, Jitse H. Zwaga, Hans Driessen, Hans Driessen, } "Efficient one-scan-back PDAF for target tracking in clutter", Proc. SPIE 4473, Signal and Data Processing of Small Targets 2001, (26 November 2001); doi: 10.1117/12.492778; https://doi.org/10.1117/12.492778

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