{"title":"基于稀疏建模的分布式MIMO雷达自适应设计","authors":"S. Gogineni, A. Nehorai","doi":"10.1109/WDD.2010.5592334","DOIUrl":null,"url":null,"abstract":"Multiple Input Multiple Output (MIMO) radar systems with widely separated antennas provide spatial diversity gain by viewing the targets from different angles. In this paper, we propose an approach to accurately estimate the properties (position, velocity) of multiple targets using such systems by employing sparse modeling. We also propose a new metric to analyze the performance of the radar system. We develop an adaptive mechanism for optimal energy allocation at different transmitters. We show that this adaptive mechanism outperforms MIMO radar systems that transmit fixed equal energy across all the antennas.","PeriodicalId":112343,"journal":{"name":"2010 International Waveform Diversity and Design Conference","volume":"72 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":"{\"title\":\"Adaptive design for distributed MIMO radar using sparse modeling\",\"authors\":\"S. Gogineni, A. Nehorai\",\"doi\":\"10.1109/WDD.2010.5592334\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Multiple Input Multiple Output (MIMO) radar systems with widely separated antennas provide spatial diversity gain by viewing the targets from different angles. In this paper, we propose an approach to accurately estimate the properties (position, velocity) of multiple targets using such systems by employing sparse modeling. We also propose a new metric to analyze the performance of the radar system. We develop an adaptive mechanism for optimal energy allocation at different transmitters. We show that this adaptive mechanism outperforms MIMO radar systems that transmit fixed equal energy across all the antennas.\",\"PeriodicalId\":112343,\"journal\":{\"name\":\"2010 International Waveform Diversity and Design Conference\",\"volume\":\"72 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-09-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"10\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 International Waveform Diversity and Design Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WDD.2010.5592334\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 International Waveform Diversity and Design Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WDD.2010.5592334","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Adaptive design for distributed MIMO radar using sparse modeling
Multiple Input Multiple Output (MIMO) radar systems with widely separated antennas provide spatial diversity gain by viewing the targets from different angles. In this paper, we propose an approach to accurately estimate the properties (position, velocity) of multiple targets using such systems by employing sparse modeling. We also propose a new metric to analyze the performance of the radar system. We develop an adaptive mechanism for optimal energy allocation at different transmitters. We show that this adaptive mechanism outperforms MIMO radar systems that transmit fixed equal energy across all the antennas.