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An Application of the Orthogonal Matching Pursuit Algorithm in Space-Time Adaptive Processing
The article presents a new space-time adaptive processing (STAP) method for target detection in a heterogeneous and non-stationary environment. In study it was proven that it is possible to estimate the clutter covariance matrix (CCM) in STAP by using the MIMO (Multiple Input Multiple Output) radar...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7349245/ https://www.ncbi.nlm.nih.gov/pubmed/32575499 http://dx.doi.org/10.3390/s20123468 |
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author | Ślesicka, Anna Kawalec, Adam |
author_facet | Ślesicka, Anna Kawalec, Adam |
author_sort | Ślesicka, Anna |
collection | PubMed |
description | The article presents a new space-time adaptive processing (STAP) method for target detection in a heterogeneous and non-stationary environment. In study it was proven that it is possible to estimate the clutter covariance matrix (CCM) in STAP by using the MIMO (Multiple Input Multiple Output) radar geometry model and the orthogonal matching pursuit (OMP) algorithm. For the estimation of spatio-temporal spectrum of clutter and target, a model of joint sparse recovery was established. As a result, clutter suppression and target detection in a heterogeneous environment will be achieved. In addition, the proposed method uses a single snapshot of the radar data cube, which eliminates the need for access to all training cells. |
format | Online Article Text |
id | pubmed-7349245 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-73492452020-07-22 An Application of the Orthogonal Matching Pursuit Algorithm in Space-Time Adaptive Processing Ślesicka, Anna Kawalec, Adam Sensors (Basel) Letter The article presents a new space-time adaptive processing (STAP) method for target detection in a heterogeneous and non-stationary environment. In study it was proven that it is possible to estimate the clutter covariance matrix (CCM) in STAP by using the MIMO (Multiple Input Multiple Output) radar geometry model and the orthogonal matching pursuit (OMP) algorithm. For the estimation of spatio-temporal spectrum of clutter and target, a model of joint sparse recovery was established. As a result, clutter suppression and target detection in a heterogeneous environment will be achieved. In addition, the proposed method uses a single snapshot of the radar data cube, which eliminates the need for access to all training cells. MDPI 2020-06-19 /pmc/articles/PMC7349245/ /pubmed/32575499 http://dx.doi.org/10.3390/s20123468 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Letter Ślesicka, Anna Kawalec, Adam An Application of the Orthogonal Matching Pursuit Algorithm in Space-Time Adaptive Processing |
title | An Application of the Orthogonal Matching Pursuit Algorithm in Space-Time Adaptive Processing |
title_full | An Application of the Orthogonal Matching Pursuit Algorithm in Space-Time Adaptive Processing |
title_fullStr | An Application of the Orthogonal Matching Pursuit Algorithm in Space-Time Adaptive Processing |
title_full_unstemmed | An Application of the Orthogonal Matching Pursuit Algorithm in Space-Time Adaptive Processing |
title_short | An Application of the Orthogonal Matching Pursuit Algorithm in Space-Time Adaptive Processing |
title_sort | application of the orthogonal matching pursuit algorithm in space-time adaptive processing |
topic | Letter |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7349245/ https://www.ncbi.nlm.nih.gov/pubmed/32575499 http://dx.doi.org/10.3390/s20123468 |
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