{"title":"MIMO雷达最小统计色散波束形成","authors":"Xue Jiang, D. Bliss","doi":"10.1109/RADAR.2016.7485161","DOIUrl":null,"url":null,"abstract":"A minimum dispersion based beamformer is developed for multiple-input multiple-output (MIMO) radar. In statistics, dispersion is defined as the expectation of the pth power of the modulus of a random variable, which can be considered as a generalization of variance with p = 2. By noticing that the linear combination of the transmitted waveforms at the target location exhibits non-Gaussian property, we adopt the minimum dispersion criterion at the receiver instead of the widely used minimum variance criterion, which implicitly exploits non-Gaussianity and hence improves the performance of the beamformer. Simulation results are provided to demonstrate the robustness and accuracy of the proposed method compared with the conventional beamforming techniques.","PeriodicalId":185932,"journal":{"name":"2016 IEEE Radar Conference (RadarConf)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Minimum statistical dispersion beamforming for MIMO radar\",\"authors\":\"Xue Jiang, D. Bliss\",\"doi\":\"10.1109/RADAR.2016.7485161\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A minimum dispersion based beamformer is developed for multiple-input multiple-output (MIMO) radar. In statistics, dispersion is defined as the expectation of the pth power of the modulus of a random variable, which can be considered as a generalization of variance with p = 2. By noticing that the linear combination of the transmitted waveforms at the target location exhibits non-Gaussian property, we adopt the minimum dispersion criterion at the receiver instead of the widely used minimum variance criterion, which implicitly exploits non-Gaussianity and hence improves the performance of the beamformer. Simulation results are provided to demonstrate the robustness and accuracy of the proposed method compared with the conventional beamforming techniques.\",\"PeriodicalId\":185932,\"journal\":{\"name\":\"2016 IEEE Radar Conference (RadarConf)\",\"volume\":\"3 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-05-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 IEEE Radar Conference (RadarConf)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/RADAR.2016.7485161\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE Radar Conference (RadarConf)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RADAR.2016.7485161","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Minimum statistical dispersion beamforming for MIMO radar
A minimum dispersion based beamformer is developed for multiple-input multiple-output (MIMO) radar. In statistics, dispersion is defined as the expectation of the pth power of the modulus of a random variable, which can be considered as a generalization of variance with p = 2. By noticing that the linear combination of the transmitted waveforms at the target location exhibits non-Gaussian property, we adopt the minimum dispersion criterion at the receiver instead of the widely used minimum variance criterion, which implicitly exploits non-Gaussianity and hence improves the performance of the beamformer. Simulation results are provided to demonstrate the robustness and accuracy of the proposed method compared with the conventional beamforming techniques.