{"title":"Obstacle sensing using dechirp SAR","authors":"Zhibiao Jiang, Jian Wang, Qian Song, Zhimin Zhou","doi":"10.1109/ICSP.2016.7878067","DOIUrl":null,"url":null,"abstract":"Obstacle sensing is one of the most difficult problems in perception for unmanned ground vehicle (UGV) in outdoor environments. The regular obstacle sensors, such as stereo vision, infrared detectors and ladar, have their limited performance in unconstructed environments. In this paper, we used an ultra wideband synthetic aperture radar (SAR) to sense obstacle for UGV. The dechirp method was applied to SAR imaging to reduce the high sample rate and the system storage capacity. The ultra-wideband SAR echo model was built, and the dechirp process was reviewed. Back projection (BP) was adopted to form the two-dimensional complex image. Finally, we have conducted a field experiment on a ground covered by sparse grasses to test the obstacle sensing performance of our ultra wideband SAR, and obstacles have shown special scattering properties in scattering image.","PeriodicalId":234499,"journal":{"name":"2016 IEEE 13th International Conference on Signal Processing (ICSP)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE 13th International Conference on Signal Processing (ICSP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSP.2016.7878067","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
Obstacle sensing is one of the most difficult problems in perception for unmanned ground vehicle (UGV) in outdoor environments. The regular obstacle sensors, such as stereo vision, infrared detectors and ladar, have their limited performance in unconstructed environments. In this paper, we used an ultra wideband synthetic aperture radar (SAR) to sense obstacle for UGV. The dechirp method was applied to SAR imaging to reduce the high sample rate and the system storage capacity. The ultra-wideband SAR echo model was built, and the dechirp process was reviewed. Back projection (BP) was adopted to form the two-dimensional complex image. Finally, we have conducted a field experiment on a ground covered by sparse grasses to test the obstacle sensing performance of our ultra wideband SAR, and obstacles have shown special scattering properties in scattering image.