{"title":"Bias phenomenon and analysis of a nonlinear transformation in a mobile passive sensor network","authors":"Z. Ding, H. Leung","doi":"10.1109/CISDA.2009.5356558","DOIUrl":null,"url":null,"abstract":"In this article, we consider the bias issue in a passive tracking system which utilizes a mobile passive sensor network, where bearing-only sensors such as Inferred or ESM are used. Biases due to nonlinear transformations have already been recognized, but have not been studied for this particular case of converted pseudo measurements in a mobile passive sensor network. Based on the Taylor series, the bias equations for a network of two passive sensors are derived. Monte Carlo simulation is used for analysis. There are two other non-linear transformations which are related to this study: 1. range/azimuth to X/Y; 2. range/azimuth to latitude/longitude. Insightful studies with explicit expressions are available for the first nonlinear transformation, but not for the second and the new nonlinear transformations. This article will provide an approximate solution and simulation study for the new nonlinear transformation.","PeriodicalId":6407,"journal":{"name":"2009 IEEE Symposium on Computational Intelligence for Security and Defense Applications","volume":"97 1","pages":"1-5"},"PeriodicalIF":0.0000,"publicationDate":"2009-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 IEEE Symposium on Computational Intelligence for Security and Defense Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CISDA.2009.5356558","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
In this article, we consider the bias issue in a passive tracking system which utilizes a mobile passive sensor network, where bearing-only sensors such as Inferred or ESM are used. Biases due to nonlinear transformations have already been recognized, but have not been studied for this particular case of converted pseudo measurements in a mobile passive sensor network. Based on the Taylor series, the bias equations for a network of two passive sensors are derived. Monte Carlo simulation is used for analysis. There are two other non-linear transformations which are related to this study: 1. range/azimuth to X/Y; 2. range/azimuth to latitude/longitude. Insightful studies with explicit expressions are available for the first nonlinear transformation, but not for the second and the new nonlinear transformations. This article will provide an approximate solution and simulation study for the new nonlinear transformation.
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