{"title":"基于渐近阈值排序的MIMO雷达估计简化性能比较度量","authors":"Qian He, Xiongwei Wu, Rick S. Blum","doi":"10.1109/SAM.2016.7569656","DOIUrl":null,"url":null,"abstract":"For many nonlinear estimation problems, classical lower bounds such as the Cramer-Rao bound (CRB) can characterize the mean squared error (MSE) performance only in the asymptotic region. While more powerful bounds like the Ziv-Zakai bound (ZZB) can also predict the best MSE performance in the nonasymptotic region, they may complicate the computation to an unaffordable extent. In this paper, for estimators with well-defined asymptotic threshold and virtually identical CRB, we propose to compare the MSE performance using the ZZB-based asymptotic threshold ranking. This method complements the CRB and is easier to compute than the ZZB, providing an efficient tool for preliminary system design.","PeriodicalId":159236,"journal":{"name":"2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM)","volume":"92 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Simplified performance comparison metric based on asymptotic threshold ranking for MIMO radar estimation\",\"authors\":\"Qian He, Xiongwei Wu, Rick S. Blum\",\"doi\":\"10.1109/SAM.2016.7569656\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"For many nonlinear estimation problems, classical lower bounds such as the Cramer-Rao bound (CRB) can characterize the mean squared error (MSE) performance only in the asymptotic region. While more powerful bounds like the Ziv-Zakai bound (ZZB) can also predict the best MSE performance in the nonasymptotic region, they may complicate the computation to an unaffordable extent. In this paper, for estimators with well-defined asymptotic threshold and virtually identical CRB, we propose to compare the MSE performance using the ZZB-based asymptotic threshold ranking. This method complements the CRB and is easier to compute than the ZZB, providing an efficient tool for preliminary system design.\",\"PeriodicalId\":159236,\"journal\":{\"name\":\"2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM)\",\"volume\":\"92 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-09-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SAM.2016.7569656\",\"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 Sensor Array and Multichannel Signal Processing Workshop (SAM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SAM.2016.7569656","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Simplified performance comparison metric based on asymptotic threshold ranking for MIMO radar estimation
For many nonlinear estimation problems, classical lower bounds such as the Cramer-Rao bound (CRB) can characterize the mean squared error (MSE) performance only in the asymptotic region. While more powerful bounds like the Ziv-Zakai bound (ZZB) can also predict the best MSE performance in the nonasymptotic region, they may complicate the computation to an unaffordable extent. In this paper, for estimators with well-defined asymptotic threshold and virtually identical CRB, we propose to compare the MSE performance using the ZZB-based asymptotic threshold ranking. This method complements the CRB and is easier to compute than the ZZB, providing an efficient tool for preliminary system design.