{"title":"Disturbance removal in passive radar via sliding extensive cancellation algorithm (ECA-S)","authors":"C. Palmarini, T. Martelli, F. Colone, P. Lombardo","doi":"10.1109/RADARCONF.2015.7411873","DOIUrl":null,"url":null,"abstract":"In this paper an advanced version of the Extensive Cancellation Algorithm (ECA) is proposed for robust disturbance cancellation and target detection in passive radar. Firstly some specific limitations of previous ECA versions are identified when dealing with a highly time-varying disturbance scenario in the presence of slowly moving targets. Specifically, the need to rapidly adapt the filter coefficients is shown to yield undesired effects on low Doppler target echoes, along with the expected partial cancellation. Therefore a sliding version of the ECA is presented which operates on partially overlapped signals batches. The proposed modification to the original ECA is shown to appropriately counteract the limitations above by taking advantage of a smooth estimate of the filter coefficients. The benefits of the proposed approach are demonstrated against experimental data sets accounting for quite different passive radar applications.","PeriodicalId":267194,"journal":{"name":"2015 IEEE Radar Conference","volume":"117 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE Radar Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RADARCONF.2015.7411873","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
In this paper an advanced version of the Extensive Cancellation Algorithm (ECA) is proposed for robust disturbance cancellation and target detection in passive radar. Firstly some specific limitations of previous ECA versions are identified when dealing with a highly time-varying disturbance scenario in the presence of slowly moving targets. Specifically, the need to rapidly adapt the filter coefficients is shown to yield undesired effects on low Doppler target echoes, along with the expected partial cancellation. Therefore a sliding version of the ECA is presented which operates on partially overlapped signals batches. The proposed modification to the original ECA is shown to appropriately counteract the limitations above by taking advantage of a smooth estimate of the filter coefficients. The benefits of the proposed approach are demonstrated against experimental data sets accounting for quite different passive radar applications.