K-coverage based receiver placement optimisation in passive radar network
In passive radar network (PRN), the receiver placement optimisation which has the ability to improve the coverage performance attracts much attention recently. In this study, the K-coverage performance is considered since the pre-condition of deghosting in a radar network is that the target has to b...
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doaj-c2c941b59d24459b92fb47f2345125b72021-04-02T13:07:37ZengWileyThe Journal of Engineering2051-33052019-08-0110.1049/joe.2019.0157JOE.2019.0157K-coverage based receiver placement optimisation in passive radar networkRui Xie0Xianrong Wan1Kai Luo2Jianxin Yi3Tao Jiang4Huazhong University of Science and Technology, School of Electronic Information and CommunicationWuhan University, School of Electronic InformationHuazhong University of Science and Technology, School of Electronic Information and CommunicationWuhan University, School of Electronic InformationHuazhong University of Science and Technology, School of Electronic Information and CommunicationIn passive radar network (PRN), the receiver placement optimisation which has the ability to improve the coverage performance attracts much attention recently. In this study, the K-coverage performance is considered since the pre-condition of deghosting in a radar network is that the target has to be covered by [inline-formula] bistatic pairs. Thus, a K-coverage-based receiver placement optimisation is formulated, in which a weighted M-centre model and the required radar cross section (RCS) for target detection are involved. Moreover, in order to solve this high dimensional optimisation problem, an iterative method which is based on K-order Voronoi algorithm and neighbourood search is proposed. Finally, the proposed method shows its effectiveness in solving the K-coverage optimisation problem of PRN via simulations. Specially, the probability of K-coverage is up to 99.8% with the optimal placement.https://digital-library.theiet.org/content/journals/10.1049/joe.2019.0157object detectionradar receiverscomputational geometryprobabilitypassive radaroptimisationiterative methodsradar cross-sectionsradar signal processingcoverage performancehigh dimensional optimisation problempassive radar networkK-coverage based receiver placement optimisationK-order Voronoi algorithmtarget detectioniterative method |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Rui Xie Xianrong Wan Kai Luo Jianxin Yi Tao Jiang |
spellingShingle |
Rui Xie Xianrong Wan Kai Luo Jianxin Yi Tao Jiang K-coverage based receiver placement optimisation in passive radar network The Journal of Engineering object detection radar receivers computational geometry probability passive radar optimisation iterative methods radar cross-sections radar signal processing coverage performance high dimensional optimisation problem passive radar network K-coverage based receiver placement optimisation K-order Voronoi algorithm target detection iterative method |
author_facet |
Rui Xie Xianrong Wan Kai Luo Jianxin Yi Tao Jiang |
author_sort |
Rui Xie |
title |
K-coverage based receiver placement optimisation in passive radar network |
title_short |
K-coverage based receiver placement optimisation in passive radar network |
title_full |
K-coverage based receiver placement optimisation in passive radar network |
title_fullStr |
K-coverage based receiver placement optimisation in passive radar network |
title_full_unstemmed |
K-coverage based receiver placement optimisation in passive radar network |
title_sort |
k-coverage based receiver placement optimisation in passive radar network |
publisher |
Wiley |
series |
The Journal of Engineering |
issn |
2051-3305 |
publishDate |
2019-08-01 |
description |
In passive radar network (PRN), the receiver placement optimisation which has the ability to improve the coverage performance attracts much attention recently. In this study, the K-coverage performance is considered since the pre-condition of deghosting in a radar network is that the target has to be covered by [inline-formula] bistatic pairs. Thus, a K-coverage-based receiver placement optimisation is formulated, in which a weighted M-centre model and the required radar cross section (RCS) for target detection are involved. Moreover, in order to solve this high dimensional optimisation problem, an iterative method which is based on K-order Voronoi algorithm and neighbourood search is proposed. Finally, the proposed method shows its effectiveness in solving the K-coverage optimisation problem of PRN via simulations. Specially, the probability of K-coverage is up to 99.8% with the optimal placement. |
topic |
object detection radar receivers computational geometry probability passive radar optimisation iterative methods radar cross-sections radar signal processing coverage performance high dimensional optimisation problem passive radar network K-coverage based receiver placement optimisation K-order Voronoi algorithm target detection iterative method |
url |
https://digital-library.theiet.org/content/journals/10.1049/joe.2019.0157 |
work_keys_str_mv |
AT ruixie kcoveragebasedreceiverplacementoptimisationinpassiveradarnetwork AT xianrongwan kcoveragebasedreceiverplacementoptimisationinpassiveradarnetwork AT kailuo kcoveragebasedreceiverplacementoptimisationinpassiveradarnetwork AT jianxinyi kcoveragebasedreceiverplacementoptimisationinpassiveradarnetwork AT taojiang kcoveragebasedreceiverplacementoptimisationinpassiveradarnetwork |
_version_ |
1721566350753660928 |