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Adaptive Waveform Design for Cognitive Radar in Multiple Targets Situation

In this paper, the problem of cognitive radar (CR) waveform optimization design for target detection and estimation in multiple extended targets situations is investigated. This problem is analyzed in signal-dependent interference, as well as additive channel noise for extended targets with unknown...

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Detalles Bibliográficos
Autores principales: Zhang, Xiaowen, Liu, Xingzhao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7512607/
https://www.ncbi.nlm.nih.gov/pubmed/33265205
http://dx.doi.org/10.3390/e20020114
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author Zhang, Xiaowen
Liu, Xingzhao
author_facet Zhang, Xiaowen
Liu, Xingzhao
author_sort Zhang, Xiaowen
collection PubMed
description In this paper, the problem of cognitive radar (CR) waveform optimization design for target detection and estimation in multiple extended targets situations is investigated. This problem is analyzed in signal-dependent interference, as well as additive channel noise for extended targets with unknown target impulse response (TIR). To address this problem, an improved algorithm is employed for target detection by maximizing the detection probability of the received echo on the promise of ensuring the TIR estimation precision. In this algorithm, an additional weight vector is introduced to achieve a trade-off among different targets. Both the estimate of TIR and transmit waveform can be updated at each step based on the previous step. Under the same constraint on waveform energy and bandwidth, the information theoretical approach is also considered. In addition, the relationship between the waveforms that are designed based on the two criteria is discussed. Unlike most existing works that only consider single target with temporally correlated characteristics, waveform design for multiple extended targets is considered in this method. Simulation results demonstrate that compared with linear frequency modulated (LFM) signal, waveforms designed based on maximum detection probability and maximum mutual information (MI) criteria can make radar echoes contain more multiple-target information and improve radar performance as a result.
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spelling pubmed-75126072020-11-09 Adaptive Waveform Design for Cognitive Radar in Multiple Targets Situation Zhang, Xiaowen Liu, Xingzhao Entropy (Basel) Article In this paper, the problem of cognitive radar (CR) waveform optimization design for target detection and estimation in multiple extended targets situations is investigated. This problem is analyzed in signal-dependent interference, as well as additive channel noise for extended targets with unknown target impulse response (TIR). To address this problem, an improved algorithm is employed for target detection by maximizing the detection probability of the received echo on the promise of ensuring the TIR estimation precision. In this algorithm, an additional weight vector is introduced to achieve a trade-off among different targets. Both the estimate of TIR and transmit waveform can be updated at each step based on the previous step. Under the same constraint on waveform energy and bandwidth, the information theoretical approach is also considered. In addition, the relationship between the waveforms that are designed based on the two criteria is discussed. Unlike most existing works that only consider single target with temporally correlated characteristics, waveform design for multiple extended targets is considered in this method. Simulation results demonstrate that compared with linear frequency modulated (LFM) signal, waveforms designed based on maximum detection probability and maximum mutual information (MI) criteria can make radar echoes contain more multiple-target information and improve radar performance as a result. MDPI 2018-02-09 /pmc/articles/PMC7512607/ /pubmed/33265205 http://dx.doi.org/10.3390/e20020114 Text en © 2018 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 Article
Zhang, Xiaowen
Liu, Xingzhao
Adaptive Waveform Design for Cognitive Radar in Multiple Targets Situation
title Adaptive Waveform Design for Cognitive Radar in Multiple Targets Situation
title_full Adaptive Waveform Design for Cognitive Radar in Multiple Targets Situation
title_fullStr Adaptive Waveform Design for Cognitive Radar in Multiple Targets Situation
title_full_unstemmed Adaptive Waveform Design for Cognitive Radar in Multiple Targets Situation
title_short Adaptive Waveform Design for Cognitive Radar in Multiple Targets Situation
title_sort adaptive waveform design for cognitive radar in multiple targets situation
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7512607/
https://www.ncbi.nlm.nih.gov/pubmed/33265205
http://dx.doi.org/10.3390/e20020114
work_keys_str_mv AT zhangxiaowen adaptivewaveformdesignforcognitiveradarinmultipletargetssituation
AT liuxingzhao adaptivewaveformdesignforcognitiveradarinmultipletargetssituation