基于MGMD空间的窄带雷达空中目标识别方法

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中图分类号：TN959.1 文献标志码：A DOI：10.12305/j.issn.1001-506X.2025.04.10

Abstract：To solve the problem that narrow-band radar has low performance in recognizing echoes from short-term observations （ESTO） sequence features and is susceptible to decoy interference，an aerial target recognition method is proposed based on the maximum-margin Gausian mixture distribution （MGMD） space. Firstly，the MGMD space is constructed and the class center for the categories in the library is preset. The distance between each category center is maximized and the class center corresponds to the mean value of MGMD.Secondly，a deep network containing the feature attention mechanism is built to map the ESTO sequence to the MGMD space. Then，through training，each type of deep feature is subject to MGMD，which maximizes its edge and improves the model's classification generalization performance and itsability to recognize the baits.Experimental results show that the proposed method can efectively improve the narrow-band radar classification performance of target ESTO sequences and its ability to recognize the decoy targets.

Keywords：narrow-band radar；airborne target recognition；echoes from short-term observation （ESTO）; maximum-margin Gaussian mixture distribution（MGMD）

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空域防空安全是国家安防领域的重要组成部分。（剩余16649字）