雷达小样本目标识别方法及应用分析

doi:10.12305/j.issn.1001-506X.2021.03.11

Abstract

Abstract:

Aiming at the problem of radar small shot target recognition, a comprehensive solution is proposed by combining meta learning and transfer learning, to provide appropriate model learning and classification methods according to different practical application scenarios, so as to improve the efficiency and accuracy of radar small shot target recognition. At the same time, through several groups of comparative experiments, the model performance changes of few shot learning algorithm in the actual radar target recognition scene are deeply analyzed, and two important conclusions that can effectively guide the engineering application are obtained. One is the performance of meta learning model is good when the source task information is sufficient and the difference between the source task and the target task is small, otherwise the transfer learning method is more suitable. The other one is the few shot learning model pay different attention to the external features of radar targets, so the recognition oriented radar imaging should focus on the salient features of the model requirements.

Key words: radar target recognition, few shot learning, meta learning, transfer learning

CLC Number:

TN911.73

Yuan YAN, Jun SUN, Jingming SUN, Junpeng YU. Radar few shot target recognition method and application analysis[J]. Systems Engineering and Electronics, 2021, 43(3): 684-692.

Figures/Tables 12

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References 26

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目标类型	姿态角/(°)
目标类型	15	17	30	45
BTR70(SN_C71)	196	233	-	-
BTR60	195	256	-	-
2S1	274	299	288	303
BRDM2	274	298	420	423
D7	274	299	-	-
T62	273	299	-	-
ZIL131	274	299	-	-
ZSU23/4	274	299	406	422
BMP2(SN_9563)	195	233	-	-
T72(SN_132)	196	232	-	-

参数	编号
参数	a	b	c	d	e	f	g	h	i	j	k
训练样本姿态角/(°)	15	15	15	15	15, 17	15, 17	15, 17	15, 17	15, 17	15, 17	15, 17
测试样本姿态角/(°)	15	17	30	45	15	17	30	45	15, 17	30, 45	15, 17, 30, 45
训练样本数量	200	200	200	200	200	200	200	200	400	400	400
测试样本数量	200	200	200	200	200	200	200	200	400	400	400
元学习识别率/%	97.3	97.9	82	75.26	96.7	97.9	80.4	71.8	94.7	63.5	55.2
迁移识别率/%	84.9	87.7	73.8	74.1	86.2	86.8	75.8	75	81.6	64.6	55.2

参数	炮管特征		履带特征
训练样本	有	无	有	无
测试样本	无	有	无	有
训练类别数	6	4	6	4
测试类别数	4	6	4	6
训练样本数量	400	400	400	400
测试样本数量	400	400	400	400
元学习识别率/%	83.2	84.6	94.3	86.4
迁移识别率/%	82.8	64.9	80.1	70.5

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Radar few shot target recognition method and application analysis

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