Direction-of-Arrival Estimation Using Deep Learning with Covariance Matrix Reconstruction under Limited Snapshots

Direction-of-Arrival Estimation Using Deep Learning with Covariance Matrix Reconstruction under Limited Snapshots | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL Electronics Letters This is a preprint and has not been peer reviewed. Data may be preliminary. 18 April 2025 V1 Latest version Share on Direction-of-Arrival Estimation Using Deep Learning with Covariance Matrix Reconstruction under Limited Snapshots Authors : Yonghong Zhao 0009-0004-4229-5780 , JIsong Liu , Xiumei Fan [email protected] , and Hongbo Cao 0000-0002-7819-7427 Authors Info & Affiliations https://doi.org/10.22541/au.174494714.45223393/v1 Published Electronics Letters Version of record Peer review timeline 468 views 262 downloads Contents Abstract Supplementary Material Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract Under low snapshot conditions, a novel DOA estimation method that integrates covariance matrix reconstruction with deep learning is proposed in this letter. We reconstruct a structured covariance matrix using a reference-auxiliary subarray model combined with diagonal loading. The reconstructed matrix is transformed into a two-channel input and fed into the proposed squeeze-and-excitation multi-scale deep convolutional network (SE-MSDCN). DOA estimates are obtained via a sub-grid peak detection strategy. Simulation results demonstrate that the proposed approach significantly outperforms traditional methods and existing deep learning techniques in terms of accuracy and resolution, particularly under low snapshot and SNR conditions. Supplementary Material File (direction-of-arrival estimation using deep learning with covariance matrix reconstruction under limited snapshots.docx) Download 1.83 MB File (direction-of-arrival estimation using deep learning with covariance matrix reconstruction under limited snapshots.pdf) Download 602.14 KB Information & Authors Information Version history V1 Version 1 18 April 2025 Peer review timeline Published Electronics Letters Version of Record 7 Aug 2025 Published Copyright This work is licensed under a Non Exclusive No Reuse License. Collection Electronics Letters Keywords array signal processing direction-of-arrival estimation neural nets Authors Affiliations Yonghong Zhao 0009-0004-4229-5780 School of Automation and Information Engineering, Xi’an University of Technology View all articles by this author JIsong Liu School of Automation and Information Engineering, Xi’an University of Technology View all articles by this author Xiumei Fan [email protected] School of Automation and Information Engineering, Xi’an University of Technology View all articles by this author Hongbo Cao 0000-0002-7819-7427 School of Automation and Information Engineering, Xi’an University of Technology View all articles by this author Metrics & Citations Metrics Article Usage 468 views 262 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Yonghong Zhao, JIsong Liu, Xiumei Fan, et al. Direction-of-Arrival Estimation Using Deep Learning with Covariance Matrix Reconstruction under Limited Snapshots. Authorea . 18 April 2025. DOI: https://doi.org/10.22541/au.174494714.45223393/v1 If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download. For more information or tips please see 'Downloading to a citation manager' in the Help menu . Format Please select one from the list RIS (ProCite, Reference Manager) EndNote BibTex Medlars RefWorks Direct import Tips for downloading citations document.getElementById('citMgrHelpLink').addEventListener('click', function() { popupHelp(this.href); return false; }); $(".js__slcInclude").on("change", function(e){ if ($(this).val() == 'refworks') $('#direct').prop("checked", false); $('#direct').prop("disabled", ($(this).val() == 'refworks')); }); View Options View options PDF View PDF Figures Tables Media Share Share Share article link Copy Link Copied! Copying failed. 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