{"title":"Power allocation for distributed passive radar systems with occasional node failure","authors":"Omid Taghizadeh, G. Alirezaei, R. Mathar","doi":"10.1109/WiSEE.2015.7392988","DOIUrl":null,"url":null,"abstract":"In this paper, we address the optimal power allocation problem for a distributed passive radar system, where occasional node failures are taken into account. The goal of the network is to provide a reliable estimation from a target signal, by collecting and combining the individual observations from the network in a centralized node. In this regard, a minimum mean squared error (MMSE) problem is formulated for unbiased class of estimators, where a stochastical model regarding sensor failure is incorporated. As it is shown, the Karush Kuhn Tucker (KKT) conditions of optimality result in a solution algorithm with a water-filling (WF) structure, which provides an analytic optimal solution. In the end, numerical simulations illustrate the effect of the different network parameters on the resulting performance.","PeriodicalId":284692,"journal":{"name":"2015 IEEE International Conference on Wireless for Space and Extreme Environments (WiSEE)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE International Conference on Wireless for Space and Extreme Environments (WiSEE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WiSEE.2015.7392988","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
In this paper, we address the optimal power allocation problem for a distributed passive radar system, where occasional node failures are taken into account. The goal of the network is to provide a reliable estimation from a target signal, by collecting and combining the individual observations from the network in a centralized node. In this regard, a minimum mean squared error (MMSE) problem is formulated for unbiased class of estimators, where a stochastical model regarding sensor failure is incorporated. As it is shown, the Karush Kuhn Tucker (KKT) conditions of optimality result in a solution algorithm with a water-filling (WF) structure, which provides an analytic optimal solution. In the end, numerical simulations illustrate the effect of the different network parameters on the resulting performance.