{"title":"随机时移下激光雷达距离轮廓特征提取技术的稳定性评估","authors":"F. .. Baulin, E. V. Buryi","doi":"10.1109/piers55526.2022.9793215","DOIUrl":null,"url":null,"abstract":"The problem of obtaining time-shift invariant features for the LIDAR range profiles is considered. Techniques under consideration are based on the Fourier transform, complex wavelet transform, and Karhunen-Loeve transform. For each feature extraction technique, a classifier is trained and the resulting recognition error rates are estimated. These error rates are obtained for various widths of the random delay window. The comparison of provided estimates allows selecting a technique adequate to the expected ranges of the random time shift.","PeriodicalId":422383,"journal":{"name":"2022 Photonics & Electromagnetics Research Symposium (PIERS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Stability Estimates of LIDAR Range Profile Feature Extraction Techniques under Random Time Shifts\",\"authors\":\"F. .. Baulin, E. V. Buryi\",\"doi\":\"10.1109/piers55526.2022.9793215\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The problem of obtaining time-shift invariant features for the LIDAR range profiles is considered. Techniques under consideration are based on the Fourier transform, complex wavelet transform, and Karhunen-Loeve transform. For each feature extraction technique, a classifier is trained and the resulting recognition error rates are estimated. These error rates are obtained for various widths of the random delay window. The comparison of provided estimates allows selecting a technique adequate to the expected ranges of the random time shift.\",\"PeriodicalId\":422383,\"journal\":{\"name\":\"2022 Photonics & Electromagnetics Research Symposium (PIERS)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-04-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 Photonics & Electromagnetics Research Symposium (PIERS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/piers55526.2022.9793215\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 Photonics & Electromagnetics Research Symposium (PIERS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/piers55526.2022.9793215","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Stability Estimates of LIDAR Range Profile Feature Extraction Techniques under Random Time Shifts
The problem of obtaining time-shift invariant features for the LIDAR range profiles is considered. Techniques under consideration are based on the Fourier transform, complex wavelet transform, and Karhunen-Loeve transform. For each feature extraction technique, a classifier is trained and the resulting recognition error rates are estimated. These error rates are obtained for various widths of the random delay window. The comparison of provided estimates allows selecting a technique adequate to the expected ranges of the random time shift.