B. Jameson, D. Garmatyuk, Y. Morton, A. Curtis, R. Ewing
{"title":"基于认知OFDM雷达的室内环境目标场景重建","authors":"B. Jameson, D. Garmatyuk, Y. Morton, A. Curtis, R. Ewing","doi":"10.1109/WDD.2012.7311259","DOIUrl":null,"url":null,"abstract":"In this paper we discuss the design and experimental results associated with the software-defined ultra-wideband (UWB) orthogonal frequency division multiplexing (OFDM) system, which we aim to configure as a cognitive radar. Frequency-domain likelihood ratios (LR) are obtained via response distribution modeling and statistical parameter estimation on a per-sub-carrier basis. Then the generalized likelihood ratio test (GLRT) is performed on a composite LR. We propose to enhance this approach via adaptive selection of OFDM signal's sub-carriers to improve the detection performance; exploiting frequency diversity of the target scene by complementing the GLRT-based detection with frequency profile matching. This approach, when applied to a software-defined system, will provide for cognitive radar functionality.","PeriodicalId":102625,"journal":{"name":"2012 International Waveform Diversity & Design Conference (WDD)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"Target scene reconstruction in indoor environment with cognitive OFDM radar\",\"authors\":\"B. Jameson, D. Garmatyuk, Y. Morton, A. Curtis, R. Ewing\",\"doi\":\"10.1109/WDD.2012.7311259\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper we discuss the design and experimental results associated with the software-defined ultra-wideband (UWB) orthogonal frequency division multiplexing (OFDM) system, which we aim to configure as a cognitive radar. Frequency-domain likelihood ratios (LR) are obtained via response distribution modeling and statistical parameter estimation on a per-sub-carrier basis. Then the generalized likelihood ratio test (GLRT) is performed on a composite LR. We propose to enhance this approach via adaptive selection of OFDM signal's sub-carriers to improve the detection performance; exploiting frequency diversity of the target scene by complementing the GLRT-based detection with frequency profile matching. This approach, when applied to a software-defined system, will provide for cognitive radar functionality.\",\"PeriodicalId\":102625,\"journal\":{\"name\":\"2012 International Waveform Diversity & Design Conference (WDD)\",\"volume\":\"11 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 International Waveform Diversity & Design Conference (WDD)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WDD.2012.7311259\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 International Waveform Diversity & Design Conference (WDD)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WDD.2012.7311259","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Target scene reconstruction in indoor environment with cognitive OFDM radar
In this paper we discuss the design and experimental results associated with the software-defined ultra-wideband (UWB) orthogonal frequency division multiplexing (OFDM) system, which we aim to configure as a cognitive radar. Frequency-domain likelihood ratios (LR) are obtained via response distribution modeling and statistical parameter estimation on a per-sub-carrier basis. Then the generalized likelihood ratio test (GLRT) is performed on a composite LR. We propose to enhance this approach via adaptive selection of OFDM signal's sub-carriers to improve the detection performance; exploiting frequency diversity of the target scene by complementing the GLRT-based detection with frequency profile matching. This approach, when applied to a software-defined system, will provide for cognitive radar functionality.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
