A promising nonimagining approach to the classification of radar targets is to use the frequencies and attenuation rates of the resonant modes that present during a target’s late-time response (LTR) as features. Unfortunately, the estimation of these resonance parameters is rather sensitive to noise. However, we observe that when a large number of measurements of the LTR can be taken in a short time, the probability distribution of the estimates of the parameters can be estimated and then matched against a database of such distributions. That has the potential to reduce the sensitivity of the classification problem to noise. In this article, we develop a pragmatic approach to target classification using this distribution-matching approach and demonstrate its effectiveness through physical experiments. The proposed approach is shown to be highly robust to environmental clutter and somewhat robust to target orientation.
Classification of Radar Targets via Distribution Matching of Late-Time Resonance Parameters
Mihail S. Georgiev,A. Pitcher,Timothy N. Davidson
Published 2025 in IEEE Transactions on Radar Systems
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2025
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IEEE Transactions on Radar Systems
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