29 October 1997 Application of Bayesian field track-before-detect and peak likelihood track-after-detect trackers to shipboard infrared search and track
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Abstract
This paper describes the algorithms that Arete with support from the Office of Naval Research (ONR) is developing for shipboard infrared search and track (SIRST) detection of low-observable targets, such as subsonic, sea-skimming cruise missiles. Early detection of low signal-to-noise (SNR) targets (6 - 10 dB) is provided by Arete's Bayesian field tracker (BFT), which is a track- before-detect algorithm. Candidate detections from the BFT are used to initialize the position, velocity and likelihood of candidate tracks in a peak likelihood track-after-detect tracker. False alarm mitigation is accomplished in part by requiring the temporal evolution of a candidate track to be consistent with that of an incoming sea-skimming cruise missile. The overview of the algorithms involved in these trackers and results from both real targets and simulated targets injected into real images are presented.
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Stefano P. Merlo, Robert G. Lindgren, Philip J. Davis, "Application of Bayesian field track-before-detect and peak likelihood track-after-detect trackers to shipboard infrared search and track", Proc. SPIE 3163, Signal and Data Processing of Small Targets 1997, (29 October 1997); doi: 10.1117/12.283974; https://doi.org/10.1117/12.283974
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