采用乘性RNN的雷达HRRP目标识别

doi:10.19665/j.issn1001-2400.2021.02.007

Abstract

Abstract:

The traditional HRRP recognition methods do not consider the temporal correlation,and the azimuth sensitivity of HRRP results in the temporal variation of the samples.This paper proposes a multiplicative recurrent neural network.In this paper,HRRP samples are converted into the sequence form first,which is used to consider the correlation between range cells.In order to alleviate the mismatch between the HRRP sequence variation caused by azimuth sensitivity and the model with fixed parameters,the model adaptively selects the corresponding parameters according to the input data,and extracts robust features from the HRRP sequence.Finally,the voting strategy is adopted to fuse the information at all time steps and predict the sample categories.Experimental results with measured data show that the current model can effectively extract discriminative features and identify targets.

Key words: radar automatic target recognition, multiplicative recurrent neural network, high resolution range profile, target-aspect sensitivity, temporal correlation

CLC Number:

TN957.52

XU Bin,ZHANG Yongshun,ZHANG Qin,WANG Fuping,ZHENG Guimei. Radar HRRP target recognition based on the multiplicative RNN model[J].Journal of Xidian University, 2021, 48(2): 49-54.

Figures/Tables 6

References 13

[1]	GUO Z H, LI S H. One-dimensional Frequency-domain Features for Aircraft Recognition from Radar Range Profiles[J]. IEEE Transactions on Aerospace and Electronic Systems, 2010,46(4):1880-1892.
[2]	李志鹏, 马田香, 杜兰, 等. 在雷达HRRP识别中多特征融合多类分类器设计[J]. 西安电子科技大学学报, 2013,40(1):111-117.
	LI Zhipeng, MA Tianxiang, DU Lan, et al. Multi-class Classifier Design for Feature Fusion in Radar HRRP Recognition[J]. Journal of Xidian University, 2013,40(1):111-117.
[3]	徐丹蕾, 杜兰, 王鹏辉, 等. 采用多任务稀疏学习的雷达HRRP小样本目标识别[J]. 西安电子科技大学学报, 2016,43(2):23-28.
	XU Danlei, DU Lan, WANG Penghui, et al. Radar HRRP Target Recognition by Utilizing Multitask Sparse Learning with A Small Training Datasize[J]. Journal of Xidian University, 2016,43(2):23-28.
[4]	FENG B, CHEN B, LIU H. Radar HRRPTarget Recognition with Deep Networks[J]. Pattern Recognition, 2017,61:379-393.
[5]	DU L, WANG P, LIU H, et al. Bayesian Spatiotemporal Multitask Learning for Radar HRRP Target Recognition[J]. IEEE Transactions on Signal Processing, 2011,59(7):3182-3196.
[6]	XU B, CHEN B, WAN JW, et al. Target-aware Recurrent Attentional Network for Radar HRRP Target Recognition[J]. Signal Processing, 2019,155(2):268-280.
[7]	徐彬, 陈渤, 刘家麒, 等. 采用双向LSTM模型的雷达HRRP目标识别[J]. 西安电子科技大学学报, 2019,46(2):29-34.
	XU Bin, CHEN Bo, LIU Jiaqi, et al. Radar HRRP Target Recognition by the Bidirectional LSTM model[J]. Journal of Xidian University, 2019,46(2):29-34.
[8]	李龙, 刘铮. 采用多特征联合学习的噪声稳健HRRP识别方法[J]. 西安电子科技大学学报, 2018,45(4):57-62.
	LI Long, LIU Zheng. Noise-robust Multi-feature Joint Learning HRRP Recognition Method[J]. Journal of Xidian University. 2018,45(4):57-62.
[9]	DU C, CHEN B, XU B, et al. Factorized Discriminative Conditional Variational Auto-encoder for Radar HRRP Target Recognition[J]. Signal Processing, 2019,158(5):176-189.
[10]	WAN J W, CHEN B, XU B, et al. Convolutional Neural Networks for Radar HRRP Target Recognition and Rejection[J]. Eurasip Journal on Advances in Signal Processing, 2019,2019(1):5.
[11]	XU B, CHEN B, LIU J Q, et al. Gaussian Mixture Model-Tensor Recurrent Neural Network for HRRP Target Recognition[C]// Proceedings of the 2019 International Radar Conference. Piscataway:IEEE, 2019: 9079139.
[12]	KINGMA D P, BA J L. Adam:a Method for Stochastic Optimization[C/OL]. [2020-07-26]. https://arxiv.org/pdf/1412.6980v8.pdf.
[13]	PAN M, DU L, WANG P, et al. Multi-task Hidden Markov Modeling of Spectrogram Feature from Radar High-resolution Range Profiles[J]. Eurasip Journal on Advances in Signal Processing, 2012,2012(1):86.

机型	RNN			MRNN
机型	安-26	奖状	雅克-42	安-26	奖状	雅克-42
安-26	0.925	0.246	0.017	0.919	0.101	0.010
奖状	0.026	0.746	0.015	0.047	0.894	0.003
雅克-42	0.049	0.008	0.968	0.034	0.005	0.987
平均识别率	0.883			0.933

[1]	ZHAN Keyu,SUN Yue,LI Ying. Video super-resolution based on multi-scale 3D convolution [J]. Journal of Xidian University, 2021, 48(5): 8-14.
[2]	GUO Zekun,TIAN Long,HAN Ning,WANG Penghui,LIU Hongwei,CHEN Bo. Radar HRRP based few-shot target recognition with CNN-SSD [J]. Journal of Xidian University, 2021, 48(2): 7-14.
[3]	XU Bin,CHEN Bo,LIU Jiaqi,WANG Penghui,LIU Hongwei. Radar HRRP target recognition by the bidirectional LSTM model [J]. Journal of Xidian University, 2019, 46(2): 29-34.
[4]	LI Long;LIU Zheng. Noise-robust multi-feature joint learning HRRP recognition method [J]. Journal of Xidian University, 2018, 45(4): 57-62.
[5]	JIN Biao;SU Tao;LI Yanyan;ZHANG Long. Multi-target tracking algorithm aided by a high resolution range profile [J]. J4, 2016, 43(1): 1-6+29.
[6]	LI Fei;JIU Bo;WANG Yinghua;LUO Tao;LIU Hongwei. Novel method for attributed feature extraction from SAR imagery [J]. J4, 2015, 42(3): 15-21+89.
[7]	LIU Hongchao;JIU Bo;LIU Hongwei;BAO Zheng. High resolution range profile compensation algorithm for the space target with uniform acceleration [J]. J4, 2012, 39(4): 81-86.
[8]	WANG Penghui;DU Lan;LIU Hongwei;LI Yanbing;WU Zhaoping. New frame segmentation method for radar HRRPs [J]. J4, 2011, 38(6): 22-29.
[9]	XU Shu-wen;SHUI Peng-lang. New method for improving the performance of range-spread target detection [J]. J4, 2010, 37(6): 1053-1058.
[10]	XIA Yu-yin;FENG Da-zheng;LI Tao. Novel detection method for HRRP data [J]. J4, 2010, 37(2): 260-266+284.
[11]	LI Tao;FENG Da-zheng;XIA Yu-yin. Non-coherent integration algorithm based on HRRP data [J]. J4, 2010, 37(2): 267-272.
[12]	CHEN Feng;DU Lan;BAO Zheng. Modified KNN rule with its application in radar HRRP target recognition [J]. J4, 2007, 34(5): 681-686.
[13]	DU Lan;LIU Hong-wei;BAO Zheng;ZHANG Jun-ying. A weighted feature reduction method for the power spectrum of radar HRRP [J]. J4, 2006, 33(2): 173-177.
[14]	SONG Bin(1);ZHOU Ning-zhao(1);CHANG Yi-lin(1);LUO Zhong(2). A novel fast intra prediction algorithm in H.264/AVC [J]. J4, 2006, 33(1): 15-182.
[15]	CHEN Bo;LIU Hong-wei;BAO Zheng. An HRRP recognition method based on zero phase representation [J]. J4, 2005, 32(5): 657-662.

Radar HRRP target recognition based on the multiplicative RNN model

RichHTML

PDF (PC)

Like

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 6

References 13

Related Articles 15

Metrics

Comments

Recommended 10