Sparsity-Based Optimization of the Sensors Positions in Radar Networks with Separated Transmit and Receive Nodes

A sparsity-based approach for the joint optimization of the transmit and the receive nodes positions in the radar network with widely distributed antennas is proposed in this paper. The optimization problem is formulated as minimization of the number of radars that meet fixed target localization req...

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Main Authors: I. M. Ivashko, O. A. Krasnov, A. G. Yarovoy
Format: Article
Language:English
Published: SAGE Publishing 2016-02-01
Series:International Journal of Distributed Sensor Networks
Online Access:https://doi.org/10.1155/2016/9437602
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spelling doaj-0158eef2e1334a6a94bcf44965a296002020-11-25T03:39:18ZengSAGE PublishingInternational Journal of Distributed Sensor Networks1550-14772016-02-011210.1155/2016/94376029437602Sparsity-Based Optimization of the Sensors Positions in Radar Networks with Separated Transmit and Receive NodesI. M. IvashkoO. A. KrasnovA. G. YarovoyA sparsity-based approach for the joint optimization of the transmit and the receive nodes positions in the radar network with widely distributed antennas is proposed in this paper. The optimization problem is formulated as minimization of the number of radars that meet fixed target localization requirements over the surveillance area. We demonstrated that this type of the problem is different from the problem of the monostatic radar network topology optimization and implies the bilinear matrix inequality (BMI) problem. To tackle it, we propose to use the relaxation technique, which allows for joint selection of the positions for transmit and receive radar nodes. Provided numerical analysis shows that, in order to satisfy the same requirements to the target localization accuracy, the radar network with bistatic radars requires less number of the nodes than the one with monostatic radars.https://doi.org/10.1155/2016/9437602
collection DOAJ
language English
format Article
sources DOAJ
author I. M. Ivashko
O. A. Krasnov
A. G. Yarovoy
spellingShingle I. M. Ivashko
O. A. Krasnov
A. G. Yarovoy
Sparsity-Based Optimization of the Sensors Positions in Radar Networks with Separated Transmit and Receive Nodes
International Journal of Distributed Sensor Networks
author_facet I. M. Ivashko
O. A. Krasnov
A. G. Yarovoy
author_sort I. M. Ivashko
title Sparsity-Based Optimization of the Sensors Positions in Radar Networks with Separated Transmit and Receive Nodes
title_short Sparsity-Based Optimization of the Sensors Positions in Radar Networks with Separated Transmit and Receive Nodes
title_full Sparsity-Based Optimization of the Sensors Positions in Radar Networks with Separated Transmit and Receive Nodes
title_fullStr Sparsity-Based Optimization of the Sensors Positions in Radar Networks with Separated Transmit and Receive Nodes
title_full_unstemmed Sparsity-Based Optimization of the Sensors Positions in Radar Networks with Separated Transmit and Receive Nodes
title_sort sparsity-based optimization of the sensors positions in radar networks with separated transmit and receive nodes
publisher SAGE Publishing
series International Journal of Distributed Sensor Networks
issn 1550-1477
publishDate 2016-02-01
description A sparsity-based approach for the joint optimization of the transmit and the receive nodes positions in the radar network with widely distributed antennas is proposed in this paper. The optimization problem is formulated as minimization of the number of radars that meet fixed target localization requirements over the surveillance area. We demonstrated that this type of the problem is different from the problem of the monostatic radar network topology optimization and implies the bilinear matrix inequality (BMI) problem. To tackle it, we propose to use the relaxation technique, which allows for joint selection of the positions for transmit and receive radar nodes. Provided numerical analysis shows that, in order to satisfy the same requirements to the target localization accuracy, the radar network with bistatic radars requires less number of the nodes than the one with monostatic radars.
url https://doi.org/10.1155/2016/9437602
work_keys_str_mv AT imivashko sparsitybasedoptimizationofthesensorspositionsinradarnetworkswithseparatedtransmitandreceivenodes
AT oakrasnov sparsitybasedoptimizationofthesensorspositionsinradarnetworkswithseparatedtransmitandreceivenodes
AT agyarovoy sparsitybasedoptimizationofthesensorspositionsinradarnetworkswithseparatedtransmitandreceivenodes
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