Target localization in high-coherence multipath environment based on low-rank decomposition and sparse representation
In a multipath propagation environment, prevalent target localization methods are mainly based on the classical two-ray propagation model without considering other reflected waves. Because the received target echoes are considerably corrupted by multipath reflections in the case of complex terrain,...
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sg-ntu-dr.10356-1550762022-02-07T07:19:57Z Target localization in high-coherence multipath environment based on low-rank decomposition and sparse representation Liu, Yuan Liu, Hongwei Wang, Lu Bi, Guoan School of Electrical and Electronic Engineering Engineering::Electrical and electronic engineering Earth Radar In a multipath propagation environment, prevalent target localization methods are mainly based on the classical two-ray propagation model without considering other reflected waves. Because the received target echoes are considerably corrupted by multipath reflections in the case of complex terrain, these prevalent methods might fail to work or achieve poor performance. To solve this problem, we first consider a practical multipath propagation scenario to reveal the dynamic structural relationship of the spatial paths based on the spherical earth model. Subsequently, a target localization algorithm based on low-rank decomposition (LRD) and sparse representation (SR) framework is proposed. The proposed algorithm can effectively mitigate the effects of complex multipath interference without using any prior knowledge on the illuminated terrain and the reflecting paths. Experiments on synthetic data and real data validate the effectiveness of the proposed algorithm. This work was supported by the National Science Fund for Distinguished Young Scholars under Grant 61525105. 2022-02-07T07:19:57Z 2022-02-07T07:19:57Z 2020 Journal Article Liu, Y., Liu, H., Wang, L. & Bi, G. (2020). Target localization in high-coherence multipath environment based on low-rank decomposition and sparse representation. IEEE Transactions On Geoscience and Remote Sensing, 58(9), 6197-6209. https://dx.doi.org/10.1109/TGRS.2020.2975218 0196-2892 https://hdl.handle.net/10356/155076 10.1109/TGRS.2020.2975218 2-s2.0-85094160344 9 58 6197 6209 en IEEE Transactions on Geoscience and Remote Sensing © 2020 IEEE. All rights reserved. |
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Engineering::Electrical and electronic engineering Earth Radar Liu, Yuan Liu, Hongwei Wang, Lu Bi, Guoan Target localization in high-coherence multipath environment based on low-rank decomposition and sparse representation |
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In a multipath propagation environment, prevalent target localization methods are mainly based on the classical two-ray propagation model without considering other reflected waves. Because the received target echoes are considerably corrupted by multipath reflections in the case of complex terrain, these prevalent methods might fail to work or achieve poor performance. To solve this problem, we first consider a practical multipath propagation scenario to reveal the dynamic structural relationship of the spatial paths based on the spherical earth model. Subsequently, a target localization algorithm based on low-rank decomposition (LRD) and sparse representation (SR) framework is proposed. The proposed algorithm can effectively mitigate the effects of complex multipath interference without using any prior knowledge on the illuminated terrain and the reflecting paths. Experiments on synthetic data and real data validate the effectiveness of the proposed algorithm. |
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School of Electrical and Electronic Engineering |
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School of Electrical and Electronic Engineering Liu, Yuan Liu, Hongwei Wang, Lu Bi, Guoan |
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Article |
author |
Liu, Yuan Liu, Hongwei Wang, Lu Bi, Guoan |
author_sort |
Liu, Yuan |
title |
Target localization in high-coherence multipath environment based on low-rank decomposition and sparse representation |
title_short |
Target localization in high-coherence multipath environment based on low-rank decomposition and sparse representation |
title_full |
Target localization in high-coherence multipath environment based on low-rank decomposition and sparse representation |
title_fullStr |
Target localization in high-coherence multipath environment based on low-rank decomposition and sparse representation |
title_full_unstemmed |
Target localization in high-coherence multipath environment based on low-rank decomposition and sparse representation |
title_sort |
target localization in high-coherence multipath environment based on low-rank decomposition and sparse representation |
publishDate |
2022 |
url |
https://hdl.handle.net/10356/155076 |
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1724626848036421632 |