Mohammad Reza Jabbari;Mohammad Reza Taban;Saeed Gazor;Mehrdad Kaimasi
{"title":"Asymptotically Efficient Moving Target Localization in Distributed Radar Networks","authors":"Mohammad Reza Jabbari;Mohammad Reza Taban;Saeed Gazor;Mehrdad Kaimasi","doi":"10.1109/TSIPN.2023.3306099","DOIUrl":null,"url":null,"abstract":"In this article, we investigate the joint estimation of the position and velocity of a moving target in distributed networks of moving radars using Time Of Arrival (TOA) and Doppler Shift (DS) measurements. In contrast to most of the existing/recent methods, we avoid the use of Nuisance Variables (NVs) by employing algebraic manipulations. We reformulate a new set of equations that are linear with respect to the target's position and velocity, resulting in a significant performance improvement. Subsequently, we propose a Two-Stage Weighted Least Squares (TSWLS) estimator and recommend two alternative algorithms to reduce computational complexity while preserving the accuracy by selecting either a transmitter or receiver as the reference sensor. We implement the proposed method over fully and partially connected networks. Our theoretical derivations and numerical simulations reveal that the proposed estimators are asymptotically efficient, i.e., they attain the CRLB, at relatively high noise levels. Moreover, the simulation results show that the proposed methods outperform state-of-the-art algorithms.","PeriodicalId":56268,"journal":{"name":"IEEE Transactions on Signal and Information Processing over Networks","volume":"9 ","pages":"569-580"},"PeriodicalIF":3.0000,"publicationDate":"2023-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Signal and Information Processing over Networks","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10223301/","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0
Abstract
In this article, we investigate the joint estimation of the position and velocity of a moving target in distributed networks of moving radars using Time Of Arrival (TOA) and Doppler Shift (DS) measurements. In contrast to most of the existing/recent methods, we avoid the use of Nuisance Variables (NVs) by employing algebraic manipulations. We reformulate a new set of equations that are linear with respect to the target's position and velocity, resulting in a significant performance improvement. Subsequently, we propose a Two-Stage Weighted Least Squares (TSWLS) estimator and recommend two alternative algorithms to reduce computational complexity while preserving the accuracy by selecting either a transmitter or receiver as the reference sensor. We implement the proposed method over fully and partially connected networks. Our theoretical derivations and numerical simulations reveal that the proposed estimators are asymptotically efficient, i.e., they attain the CRLB, at relatively high noise levels. Moreover, the simulation results show that the proposed methods outperform state-of-the-art algorithms.
期刊介绍:
The IEEE Transactions on Signal and Information Processing over Networks publishes high-quality papers that extend the classical notions of processing of signals defined over vector spaces (e.g. time and space) to processing of signals and information (data) defined over networks, potentially dynamically varying. In signal processing over networks, the topology of the network may define structural relationships in the data, or may constrain processing of the data. Topics include distributed algorithms for filtering, detection, estimation, adaptation and learning, model selection, data fusion, and diffusion or evolution of information over such networks, and applications of distributed signal processing.