Synthetic aperture radar hybrid ATR system

Andrew Hauter; Kuo-Chu Chang

doi:10.1117/12.241144

24 May 1996 Synthetic aperture radar hybrid ATR system

Andrew Hauter, Kuo-Chu Chang

Proceedings Volume 2756, Automatic Object Recognition VI; (1996) https://doi.org/10.1117/12.241144
Event: Aerospace/Defense Sensing and Controls, 1996, Orlando, FL, United States

Abstract

A hybrid automatic target recognition system is presented that exploits advances in two new fields in detection theory and signal analysis. The first is in the area of Universal Classification that offers asymptotic optimal solutions to non-Gaussian properties of signals and the second is in the field of multi-resolution analysis (MRA) that uses the automatic feature isolating properties of the wavelet transform. The Universal Classifier is used as the first stage of a hybrid ATR system that efficiently shifts through large quantities of imagery locating regions of interest that contain `target-like' features. The target chips of interest are then passed through the MRA to be classified at the final stage. Wavelets are adequate to the study of unpredictable signals with both low frequency components and sharp transitions. As a result, there has been recent interest in applying this new signal processing field to the target recognition problem. But few have combined the natural feature extraction capability of time- frequency methods in the classification stage. In this approach, we utilize the sub-space `crystals' from a specific decomposition and operate a classification strategy against each crystal of the transform. The complete ATR system is presented as well as performance examples using both real synthetic aperture radar data and data generated using the Xpatch signature prediction code.

Citation Download Citation

Andrew Hauter and Kuo-Chu Chang "Synthetic aperture radar hybrid ATR system", Proc. SPIE 2756, Automatic Object Recognition VI, (24 May 1996); https://doi.org/10.1117/12.241144

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