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IEEE Transactions on Antennas and Propagation
Volume 48 Number 12, December 2000

Table of Contents for this issue

Complete paper in PDF format

Efficient Radar Target Classification Using Adaptive Joint Time-Frequency Processing

Kyung-Tae Kim, In-Sik Choi and Hyo-Tae Kim

Page 1789.

Abstract:

This paper presents a new target recognition scheme via adaptive Gaussian representation, which uses adaptive joint time-frequency processing techniques. The feature extraction stage of the proposed scheme utilizes the geometrical moments of the adaptive spectrogram. For this purpose, we have derived exact and closed form expressions of geometrical moments of the adaptive spectrogram in the time, frequency, and joint time-frequency domains. Features obtained by this method can provide substantial savings of computational resources,preserving as much essential information for classifying targets as possible. Next, a principal component analysis is used to further reduce the dimension of feature space, and the resulting feature vectors are passed to the classifier stage based on the multilayer perceptron neural network. To demonstrate the performance of the proposed scheme, various thin-wire targets are identified. The results show that the proposed technique has a significant potential for use in target recognition.

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