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Proceedings Paper

Radar target recognition by probabilistic filtering
Author(s): Anatoliy V. Popov; Oleksiy Pogrebnyak
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Paper Abstract

The paper presents a new method of probabilistic filtering for radar target recognition. The classical Bayesian detector/estimator suffers from the insufficient information about target signature probability distributions and their a priory appearance probabilities. If the number of radar image objects to be classified is not known exactly the appeared unknown target may be wrong classified as one of the known targets. To eliminate this type of errors one can use the known probabilistic windows matched by shape to the recognition signature distributions. The combination of the probability window with a non-linear transform of the signature space is proposed in the paper. Such a combination forms a probabilistic filter. The probabilistic filter output is proportional to the likelihood probability of how the sensed object matches to its statistical model. The theoretical background of the probabilistic filtering method and its application to real X-band radar data are presented in the paper. The proposed method reduces the amount of a priory information required for the recognition and detects well the objects of the same nature independently from their size. For example, the probabilistic filter classifies well the different type of vegetation in the radar images.

Paper Details

Date Published: 26 October 2004
PDF: 9 pages
Proc. SPIE 5542, Earth Observing Systems IX, (26 October 2004); doi: 10.1117/12.558627
Show Author Affiliations
Anatoliy V. Popov, National Aerospace Univ. (Ukraine)
Oleksiy Pogrebnyak, Instituto Politecnico Nacional (Mexico)

Published in SPIE Proceedings Vol. 5542:
Earth Observing Systems IX
William L. Barnes; James J. Butler, Editor(s)

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