基于MGMD空间的窄带雷达空中目标识别方法

doi:10.12305/j.issn.1001-506X.2025.04.10

Abstract

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 Gaussian 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 its ability to recognize the baits. Experimental results show that the proposed method can effectively improve the narrow-band radar classification performance of target ESTO sequences and its ability to recognize the decoy targets.

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

CLC Number:

TN959.1

Zekun GUO, Hongfei YANG, Zheng LIU, Rong XIE, Lei RAN, Jia'nan LI. Narrow-band radar airborne target recognition method based on MGMD space[J]. Systems Engineering and Electronics, 2025, 47(4): 1136-1145.

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References 30

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算法	鉴别率/%	时间/s
SVDD^[23]	78.03	0.052
w-KNN^[24]	76.81	0.046
Deep-SVDD^[25]	91.55	0.108
SCNN^[26]	82.76	0.079
MCTR-Net	95.93	0.073

算法	分类准确率/%	时间/s
SVM	35.62	3.52
CNN-SVM^[27]	86.78	2.86
CNN-KNN	86.59	2.89
LSTM^[28]	90.16	3.23
SCNN^[26]	88.24	3.18
MCTR-Net	96.61	2.68

算法	分类准确率/%	时间/s
CNN-Softmax	87.35	3.262
CNN-FAM-Softmax	91.42	2.630
CNN-MMC	93.95	2.598
MCTR-Net (CNN-FAM-MMC)	96.61	2.677

标准差	0.1	0.5	1	2	3	4
RMSE	0.068	0.334	0.668	1.336	2.004	2.673
识别率/%	95.76	92.52	90.11	87.88	83.97	84.63

标准差	5	6	7	8	9	10
RMSE	3.341	4.009	4.670	5.345	6.013	6.681
识别率/%	83.63	82.42	83.64	83.23	84.04	82.83

标准差	12	14	16	18	20	-
RMSE	8.018	9.354	10.690	12.026	13.363	-
识别率/%	80.20	78.99	77.17	76.77	75.98	-

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[2]	Yichang CHEN, Xin XIONG, Wantian WANG. Target sortie identification method of narrow-band radar based on sparse fractional Fourier transform [J]. Systems Engineering and Electronics, 2021, 43(8): 2129-2136.
[3]	HU Xiao-wei, TONG Ning-ning, HE Xing-yu, LEI Teng, WANG Yu-chen. High-speed spinning target imaging based on narrow-band radar networks [J]. Systems Engineering and Electronics, 2016, 38(4): 792-798.

Narrow-band radar airborne target recognition method based on MGMD space

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