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Proceedings Paper

Wavelet radar target classification
Author(s): Pankaj N. Topiwala; Chojan S. Teng
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Paper Abstract

Ground-based S-band radars with center frequencies in the 3 GHz range, and bandwidths of about 2 MHz, are currently being considered for the classification/identification of targets in the 50 - 250 km range (low signal-to-noise (SNR) environment). Its main drawback is that it is time and computation intensive, and, for targets at long range, it usually requires a number of looks before an ID decision is made. This leaves open the possibility of alternative approaches to S-band radar target classification. In this paper, we propose a method of classification based on correlation in a nonlinear feature space; our features are generated by a combination of wavelet transform (WT) processing and compression, and Fourier transform (FT)-based methods. The classification itself can be done explicitly by metric criteria, e.g., nearest neighbor or matched-filtering schemes, or implicitly using artificial neural networks; our simulation tests show successful classification with simple matched-filtering in our feature space. While our proposed method could be used to build an entirely different approach to target classification, it makes more sense to incorporate it into the existing classification structure. Since the frequency-domain processing required here is already performed by the existing algorithms, our method would add a minimum of extra computational burden, while opening the possibility of an earlier decision.

Paper Details

Date Published: 6 April 1995
PDF: 9 pages
Proc. SPIE 2491, Wavelet Applications II, (6 April 1995); doi: 10.1117/12.205407
Show Author Affiliations
Pankaj N. Topiwala, MITRE Corp. (United States)
Chojan S. Teng, MITRE Corp. (United States)


Published in SPIE Proceedings Vol. 2491:
Wavelet Applications II
Harold H. Szu, Editor(s)

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