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Waveform Design for Multi-Target Detection Based on Two-Stage Information Criterion

Parameter estimation accuracy and average sample number (ASN) reduction are important to improving target detection performance in sequential hypothesis tests. Multiple-input multiple-output (MIMO) radar can balance between parameter estimation accuracy and ASN reduction through waveform diversity....

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Detalles Bibliográficos
Autores principales: Xiao, Yu, Hu, Xiaoxiang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9407354/
https://www.ncbi.nlm.nih.gov/pubmed/36010739
http://dx.doi.org/10.3390/e24081075
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author Xiao, Yu
Hu, Xiaoxiang
author_facet Xiao, Yu
Hu, Xiaoxiang
author_sort Xiao, Yu
collection PubMed
description Parameter estimation accuracy and average sample number (ASN) reduction are important to improving target detection performance in sequential hypothesis tests. Multiple-input multiple-output (MIMO) radar can balance between parameter estimation accuracy and ASN reduction through waveform diversity. In this study, we propose a waveform design method based on a two-stage information criterion to improve multi-target detection performance. In the first stage, the waveform is designed to estimate the target parameters based on the criterion of single-hypothesis mutual information (MI) maximization under the constraint of the signal-to-noise ratio (SNR). In the second stage, the objective function is designed based on the criterion of MI minimization and Kullback–Leibler divergence (KLD) maximization between multi-hypothesis posterior probabilities, and the waveform is chosen from the waveform library of the first-stage parameter estimation. Furthermore, an adaptive waveform design algorithm framework for multi-target detection is proposed. The simulation results reveal that the waveform design based on the two-stage information criterion can rapidly detect the target direction. In addition, the waveform design based on the criterion of dual-hypothesis MI minimization can improve the parameter estimation performance, whereas the design based on the criterion of dual-hypothesis KLD maximization can improve the target detection performance.
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spelling pubmed-94073542022-08-26 Waveform Design for Multi-Target Detection Based on Two-Stage Information Criterion Xiao, Yu Hu, Xiaoxiang Entropy (Basel) Article Parameter estimation accuracy and average sample number (ASN) reduction are important to improving target detection performance in sequential hypothesis tests. Multiple-input multiple-output (MIMO) radar can balance between parameter estimation accuracy and ASN reduction through waveform diversity. In this study, we propose a waveform design method based on a two-stage information criterion to improve multi-target detection performance. In the first stage, the waveform is designed to estimate the target parameters based on the criterion of single-hypothesis mutual information (MI) maximization under the constraint of the signal-to-noise ratio (SNR). In the second stage, the objective function is designed based on the criterion of MI minimization and Kullback–Leibler divergence (KLD) maximization between multi-hypothesis posterior probabilities, and the waveform is chosen from the waveform library of the first-stage parameter estimation. Furthermore, an adaptive waveform design algorithm framework for multi-target detection is proposed. The simulation results reveal that the waveform design based on the two-stage information criterion can rapidly detect the target direction. In addition, the waveform design based on the criterion of dual-hypothesis MI minimization can improve the parameter estimation performance, whereas the design based on the criterion of dual-hypothesis KLD maximization can improve the target detection performance. MDPI 2022-08-03 /pmc/articles/PMC9407354/ /pubmed/36010739 http://dx.doi.org/10.3390/e24081075 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/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 (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Xiao, Yu
Hu, Xiaoxiang
Waveform Design for Multi-Target Detection Based on Two-Stage Information Criterion
title Waveform Design for Multi-Target Detection Based on Two-Stage Information Criterion
title_full Waveform Design for Multi-Target Detection Based on Two-Stage Information Criterion
title_fullStr Waveform Design for Multi-Target Detection Based on Two-Stage Information Criterion
title_full_unstemmed Waveform Design for Multi-Target Detection Based on Two-Stage Information Criterion
title_short Waveform Design for Multi-Target Detection Based on Two-Stage Information Criterion
title_sort waveform design for multi-target detection based on two-stage information criterion
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9407354/
https://www.ncbi.nlm.nih.gov/pubmed/36010739
http://dx.doi.org/10.3390/e24081075
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