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Permanent link (DOI): https://doi.org/10.7939/R3DN4031G

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Detecting targets hidden in random forests. Open Access

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Author or creator
Kouritzin, Michael
Luo, Dandan
Newton, Fraser
Wu, Biao
Additional contributors
Subject/Keyword
correlation structure
particle filter
random weighting
target detection
Type of item
Conference/workshop Presentation
Language
English
Place
Time
Description
Military tanks, cargo or troop carriers, missile carriers or rocket launchers often hide themselves from detection in the forests. This plagues the detection problem of locating these hidden targets. An electro-optic camera mounted on a surveillance aircraft or unmanned aerial vehicle is used to capture the images of the forests with possible hidden targets, e.g., rocket launchers. We consider random forests of longitudinal and latitudinal correlations. Specifically, foliage coverage is encoded with a binary representation (i.e., foliage or no foliage), and is correlated in adjacent regions. We address the detection problem of camouflaged targets hidden in random forests by building memory into the observations. In particular, we propose an efficient algorithm to generate random forests, ground, and camouflage of hidden targets with two dimensional correlations. The observations are a sequence of snapshots consisting of foliage-obscured ground or target. Theoretically, detection is possible because there are subtle differences in the correlations of the ground and camouflage of the rocket launcher. However, these differences are well beyond human perception. To detect the presence of hidden targets automatically, we develop a Markov representation for these sequences and modify the classical filtering equations to allow the Markov chain observation. Particle filters are used to estimate the position of the targets in combination with a novel random weighting technique. Furthermore, we give positive proof-of-concept simulations.
Date created
2009
DOI
doi:10.7939/R3DN4031G
License information
Rights
Copyright 2009 Society of Photo Optical Instrumentation Engineers. One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.
Citation for previous publication
M. A. Kouritzin, D. Luo, F. Newton, B. Wu (2009), "Detecting targets hidden in random forests", Proceedings of SPIE International Society for Optical Engineering, 7336, 73360N. doi:10.1117/12.817502
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