The performance analysis of three-dimensional track-before-detect algorithm based on Fisher-Tippett-Gnedenko theorem

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The dim moving target tracking from the infrared image sequence in the presence of high clutter and noise has been recently under intensive investigation. The track-before-detect (TBD) algorithm processing the image sequence over a number of frames before decisions on the target track and existence is known to be especially attractive in very low SNR environments (<= 3 dB). In this paper, we shortly present a three-dimensional (3-D) TBD with dynamic programming (TBD-DP) algorithm using multiple IR image sensors. Since traditional two-dimensional TBD algorithm cannot track and detect the along the viewing direction, we use 3-D TBD with multiple sensors and also strictly analyze the detection performance (false alarm and detection probabilities) based on Fisher-Tippett-Gnedenko theorem. The 3-D TBD-DP algorithm which does not require a separate image registration step uses the pixel intensity values jointly read off from multiple image frames to compute the merit function required in the DP process. Therefore, we also establish the relationship between the pixel coordinates of image frame and the reference coordinates. (C) 2016 Elsevier B.V. All rights reserved
Publisher
ELSEVIER SCIENCE BV
Issue Date
2016-09
Language
English
Article Type
Article
Keywords

TARGET DETECTION

Citation

INFRARED PHYSICS &amp; TECHNOLOGY, v.78, pp.241 - 248

ISSN
1350-4495
DOI
10.1016/j.infrared.2016.07.022
URI
http://hdl.handle.net/10203/214473
Appears in Collection
EE-Journal Papers(저널논문)
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