Saeid K. Dehkordi, N. Appenrodt, J. Dickmann, C. Waldschmidt
{"title":"基于兴趣域的自适应高分辨率参数估计及其在汽车雷达中的应用","authors":"Saeid K. Dehkordi, N. Appenrodt, J. Dickmann, C. Waldschmidt","doi":"10.23919/IRS.2018.8448115","DOIUrl":null,"url":null,"abstract":"High resolution processing for automotive radar is required to enhance the probability of target detection and classification in proceeding stages of driver assistance systems. As a result of the large computational demand associated with high resolution processing of the entire data set, real-time application of such methods remains a challenge. This paper presents a computationally efficient approach to achieve this goal by only processing Regions of Interest with the capability of utilizing a multi-dimensional variable resolution to meet necessary requirements for different applications.","PeriodicalId":436201,"journal":{"name":"2018 19th International Radar Symposium (IRS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Region of Interest Based Adaptive High Resolution Parameter Estimation with Applications in Automotive Radar\",\"authors\":\"Saeid K. Dehkordi, N. Appenrodt, J. Dickmann, C. Waldschmidt\",\"doi\":\"10.23919/IRS.2018.8448115\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"High resolution processing for automotive radar is required to enhance the probability of target detection and classification in proceeding stages of driver assistance systems. As a result of the large computational demand associated with high resolution processing of the entire data set, real-time application of such methods remains a challenge. This paper presents a computationally efficient approach to achieve this goal by only processing Regions of Interest with the capability of utilizing a multi-dimensional variable resolution to meet necessary requirements for different applications.\",\"PeriodicalId\":436201,\"journal\":{\"name\":\"2018 19th International Radar Symposium (IRS)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 19th International Radar Symposium (IRS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.23919/IRS.2018.8448115\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 19th International Radar Symposium (IRS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/IRS.2018.8448115","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Region of Interest Based Adaptive High Resolution Parameter Estimation with Applications in Automotive Radar
High resolution processing for automotive radar is required to enhance the probability of target detection and classification in proceeding stages of driver assistance systems. As a result of the large computational demand associated with high resolution processing of the entire data set, real-time application of such methods remains a challenge. This paper presents a computationally efficient approach to achieve this goal by only processing Regions of Interest with the capability of utilizing a multi-dimensional variable resolution to meet necessary requirements for different applications.