NDLI: SAR multi-target interactive motion recognition based on convolutional neural networks

Content Provider	IET Digital Library
Author	Huan, Ruo Hong Ge, Luo Qi Yang, Peng Xie, Chao Jie Chi, Kai Kai Mao, Ke Ji Pan, Yun
Abstract	Synthetic aperture radar (SAR) multi-target interactive motion recognition classifies the type of interactive motion and generates descriptions of the interactive motions at the semantic level by considering the relevance of multi-target motions. A method for SAR multi-target interactive motion recognition is proposed, which includes moving target detection, target type recognition, interactive motion feature extraction, and multi-target interactive motion type recognition. Wavelet thresholding denoising combined with a convolutional neural network (CNN) is proposed for target type recognition. The method performs wavelet thresholding denoising on SAR target images and then uses an eight-layer CNN named EilNet to achieve target recognition. After target type recognition, a multi-target interactive motion type recognition method is proposed. A motion feature matrix is constructed for recognition and a four-layer CNN named FolNet is designed to perform interactive motion type recognition. A motion simulation dataset based on the MSTAR dataset is built, which includes four kinds of interactive motions by two moving targets. The experimental results show that the recognition performance of the authors’ Wavelet + EilNet method for target type recognition and FolNet for multi-target interactive motion type recognition are both better than other methods. Thus, the proposed method is an effective method for SAR multi-target interactive motion recognition.
Starting Page	2567
Ending Page	2578
Page Count	12
ISSN	17519659
Volume Number	14
e-ISSN	17519667
Issue Number	Issue 11, Sep (2020)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-ipr/14/11
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2019.0861
Journal	IET Image Processing
Publisher Date	2020-04-29
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Computer Vision And Image Processing Technique Feature Extraction Image Denoising Image Recognition Interactive Motion Feature Extraction Multitarget Interactive Motion Type Recognition Method Multitarget Motions Neural Computing Technique Neural Nets Object Detection Object Recognition Optical, Image And Video Signal Processing Radar Equipment Radar Imaging Radar Target Recognition SAR Multitarget Interactive Motion Recognition SAR Target Image Signal Denoising Synthetic Aperture Radar Synthetic Aperture Radar Multitarget System And Application Target Recognition Target Tracking Target Type Recognition Wavelet Transform
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software

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