基于DCNN的弹道中段目标HRRP图像识别

doi:10.3969/j.issn.1001-506X.2020.11.03

Abstract

Abstract:

To solve the problem of midcourse ballistic target recognition, the existing recognition methods based on high resolution range profile (HRRP) directly extract the overall features of 1-dimension HRRP (1D-HRRP), which has a weak ability to extract local features, and the expression ability of features extracted from 1D-HRRP is limited. Therefore, a recognition method for midcourse ballistic targets of HRRP images based on the deep convolutional neural network (DCNN) is proposed. Firstly, 1D-HRRP is transformed into 0-1 binary images, so that the numerical variation features are transformed into the graph structure features. Then, DCNN is constructed to extract the local and common features of HRRP images layer by layer and recognize them. Finally, Dropout and L2 regularization are combined to alleviate the over-fitting problem of DCNN, and AdaBound algorithm is used to improve the convergence speed and accuracy of DCNN training. The experimental results show that the recognition method based on HRRP images is more accurate than other 12 recognition methods based on 1D-HRRP or 2-dimension HRRP (2D-HRRP), and achieves an accuracy of 96.28% in the test dataset, verifying the effectiveness of the proposed method.

Key words: ballistic missile, target recognition, high resolution range profile (HRRP), deep convolutional neural network (DCNN), AdaBound algorithm

CLC Number:

TP391.4

Qian XIANG, Xiaodan WANG, Rui LI, Jie LAI, Guoling ZHANG. HRRP image recognition of midcourse ballistic targets based on DCNN[J]. Systems Engineering and Electronics, 2020, 42(11): 2426-2433.

Figures/Tables 9

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References 20

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目标	物理特征
弹头	平底锥,长度1.6 m,底面半径0.3 m,锥顶半径0.05 m
高仿诱饵	曲面底锥,长度1.6 m,底面半径为0.3 m,锥顶半径为0.05 m,曲面底为以0.5 m为半径的球的部分
简单诱饵	平底锥柱,长度1.6 m,底面半径0.3 m,锥顶半径0.05 m
球形诱饵	球体,半径0.5 m
母舱	圆柱体,长度0.4 m,半径0.75 m

训练算法	Fill	Nofill	Plot	Area
SGD	94.73	91.45	94.78	94.73
SGD(Nesterov)	94.78	92.17	95.39	94.67
AdaGrad	95.61	92.23	95.56	95.45
AdaBound	96.28	93.56	96.17	95.95

算法	球形诱饵	高仿诱饵	母舱	简单诱饵	弹头	总体	平均时间/μs
DT	100.00	90.77	96.67	93.01	85.94	93.23	＜100
RF	100.00	88.29	96.90	88.44	84.21	91.56	＜100
GB	100.00	81.19	97.98	93.27	84.53	91.17	＜100
MLP	100.00	92.84	98.86	96.62	87.19	94.95	140
ELM	100.00	89.24	98.82	96.00	87.37	94.11	＜100
1D-DCNN	100.00	91.76	98.87	99.42	88.63	95.61	＜100
2D-DCNN	100.00	89.68	99.14	92.18	91.76	94.56	274
IMG-DCNN (Nofill)	100.00	88.64	94.64	93.87	90.40	93.56	2 281
IMG-DCNN (Area)	100.00	94.31	97.77	95.36	92.35	95.95	2 285
IMG-DCNN (Plot)	100.00	94.63	96.73	96.70	92.74	96.17	2 968
IMG-DCNN (Fill)	100.00	94.93	99.15	96.92	90.86	96.28	2 290

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HRRP image recognition of midcourse ballistic targets based on DCNN

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