{"title":"Adaptive thresholding of non-homogeneity detection for STAP applications","authors":"C. M. Teixeira, J. Bergin, P. Techau","doi":"10.1109/NRC.2004.1316449","DOIUrl":null,"url":null,"abstract":"An adaptive thresholding algorithm is presented that can be used in conjunction with the multi-pass generalized inner product (GIP)-based editing method to eliminate non-homogeneities from the training data used for STAP applications, such as adaptive radars. The algorithm exploits a property of the generic structure of the ordered GIP statistic, along with a single user-specified parameter related to the type I error of incorrectly excising target-free training data, to determine adaptively the thresholds for excising target-contaminated training data. The performance of the method is demonstrated using high-fidelity site-specific simulated data, with both ideal and realistic waveforms, as well as measured data from the multi-channel airborne radar measurement (MCARM) experiment.","PeriodicalId":268965,"journal":{"name":"Proceedings of the 2004 IEEE Radar Conference (IEEE Cat. No.04CH37509)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2004-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2004 IEEE Radar Conference (IEEE Cat. No.04CH37509)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NRC.2004.1316449","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10
Abstract
An adaptive thresholding algorithm is presented that can be used in conjunction with the multi-pass generalized inner product (GIP)-based editing method to eliminate non-homogeneities from the training data used for STAP applications, such as adaptive radars. The algorithm exploits a property of the generic structure of the ordered GIP statistic, along with a single user-specified parameter related to the type I error of incorrectly excising target-free training data, to determine adaptively the thresholds for excising target-contaminated training data. The performance of the method is demonstrated using high-fidelity site-specific simulated data, with both ideal and realistic waveforms, as well as measured data from the multi-channel airborne radar measurement (MCARM) experiment.
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