Xinyuan Liu, Shunjun Wei, Jinshan Wei, Jun Shi, Xiaoling Zhang, Yuanji Li
{"title":"Non-Line-of-Sight Millimeter-Wave Radar 3-D Sparse Reconstruct via MSSTV Method","authors":"Xinyuan Liu, Shunjun Wei, Jinshan Wei, Jun Shi, Xiaoling Zhang, Yuanji Li","doi":"10.1109/MAPE53743.2022.9935195","DOIUrl":null,"url":null,"abstract":"Non-line-of-sight (NLOS) imaging technique aims to reconstruct the hidden objects from multi-path echoes, which is a promising application in urban environment perception and autonomous driving. In this paper, we propose a total variation (TV) regularization based sparse reconstruct method for the hidden targets 3-D imaging in the seeing around corner situation for millimeter-wave (mmW) radar. Firstly, the 3-D imaging model of NLOS mmW radar is presented. Secondly, for preserving contour information, an effective imaging algorithm with compressed sensing theory and mirror projection, dubbed mirror symmetry sparse total variation (MSSTV) is proposed for 3-D image reconstruction. Finally, the MSSTV algorithm is validated by an NLOS 3-D imaging mmW experimental system with different kinds of targets.","PeriodicalId":442568,"journal":{"name":"2022 IEEE 9th International Symposium on Microwave, Antenna, Propagation and EMC Technologies for Wireless Communications (MAPE)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE 9th International Symposium on Microwave, Antenna, Propagation and EMC Technologies for Wireless Communications (MAPE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MAPE53743.2022.9935195","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Non-line-of-sight (NLOS) imaging technique aims to reconstruct the hidden objects from multi-path echoes, which is a promising application in urban environment perception and autonomous driving. In this paper, we propose a total variation (TV) regularization based sparse reconstruct method for the hidden targets 3-D imaging in the seeing around corner situation for millimeter-wave (mmW) radar. Firstly, the 3-D imaging model of NLOS mmW radar is presented. Secondly, for preserving contour information, an effective imaging algorithm with compressed sensing theory and mirror projection, dubbed mirror symmetry sparse total variation (MSSTV) is proposed for 3-D image reconstruction. Finally, the MSSTV algorithm is validated by an NLOS 3-D imaging mmW experimental system with different kinds of targets.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
