{"title":"STAP with angle-Doppler compensation for bistatic airborne radars","authors":"B. Himed, Yuhong Zhang, A. Hajjari","doi":"10.1109/NRC.2002.999737","DOIUrl":null,"url":null,"abstract":"We study issues associated with applying space-time adaptive processing (STAP) techniques in bistatic airborne applications. We consider the performance of several STAP approaches in different scenarios. Specific consideration is given to the effects of bistatic clutter spectral dispersion on covariance estimation and the algorithm's resulting clutter rejection capability. Our prime focus emphasizes adaptive processing methods capable of high performance with efficient utilization of training data. A deterministic two-dimensional spectral compensation is used to align the clutter spectral centers and thus enhance the performance of the proposed approaches. Algorithm performance is assessed using the output signal-to-interference-plus-noise ratio (SINR) compared to that of the matched filter with known covariance.","PeriodicalId":448055,"journal":{"name":"Proceedings of the 2002 IEEE Radar Conference (IEEE Cat. No.02CH37322)","volume":"103 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2002-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"135","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2002 IEEE Radar Conference (IEEE Cat. No.02CH37322)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NRC.2002.999737","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 135
Abstract
We study issues associated with applying space-time adaptive processing (STAP) techniques in bistatic airborne applications. We consider the performance of several STAP approaches in different scenarios. Specific consideration is given to the effects of bistatic clutter spectral dispersion on covariance estimation and the algorithm's resulting clutter rejection capability. Our prime focus emphasizes adaptive processing methods capable of high performance with efficient utilization of training data. A deterministic two-dimensional spectral compensation is used to align the clutter spectral centers and thus enhance the performance of the proposed approaches. Algorithm performance is assessed using the output signal-to-interference-plus-noise ratio (SINR) compared to that of the matched filter with known covariance.
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