{"title":"A Novel Radar Imaging Method Based on Random Illuminations Using FMCW Radar","authors":"Prateek Nallabolu, Changzhi Li","doi":"10.1109/WiSNeT46826.2020.9037583","DOIUrl":null,"url":null,"abstract":"Compressed Sensing (CS) has provided a viable approach to undersample a sparse signal and reconstruct it perfectly. In this paper, the simulation results of a frequency-modulated continuous-wave (FMCW) radar, which employs a CS based data acquisition and reconstruction algorithm to recover a sparse 2-D target frame using fewer number of scans are presented. A 16-element antenna array based on digital beamforming approach is used on the receiver end to obtain random spatial measurements of the target frame, which is the key to compressed sensing. A linear relationship is established between the total received FMCW beat signal for each scan and the 2-D sparse target frame using a basis transform matrix. Simulations of the proposed radar are performed in MATLAB and the reconstruction results for different noise levels are presented.","PeriodicalId":394796,"journal":{"name":"2020 IEEE Topical Conference on Wireless Sensors and Sensor Networks (WiSNeT)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE Topical Conference on Wireless Sensors and Sensor Networks (WiSNeT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WiSNeT46826.2020.9037583","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
Compressed Sensing (CS) has provided a viable approach to undersample a sparse signal and reconstruct it perfectly. In this paper, the simulation results of a frequency-modulated continuous-wave (FMCW) radar, which employs a CS based data acquisition and reconstruction algorithm to recover a sparse 2-D target frame using fewer number of scans are presented. A 16-element antenna array based on digital beamforming approach is used on the receiver end to obtain random spatial measurements of the target frame, which is the key to compressed sensing. A linear relationship is established between the total received FMCW beat signal for each scan and the 2-D sparse target frame using a basis transform matrix. Simulations of the proposed radar are performed in MATLAB and the reconstruction results for different noise levels are presented.
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
