{"title":"A low computational complexity and high accuracy DOA estimation method in the hybrid analog-digital system with interleaved subarrays","authors":"Guodong Wang, Yan Zhou","doi":"10.1016/j.sigpro.2025.109925","DOIUrl":null,"url":null,"abstract":"<div><div>The large-scale, partially connected phase-shifter Hybrid Analog-Digital System (HADS) has attracted significant attention due to its low hardware complexity, high reconfigurability, and robustness to failures. Direction-of-Arrival (DOA) estimation presents a critical challenge in HADS, as it directly impacts the Signal-to-Noise Ratio (SNR) and throughput. Existing DOA estimation methods in HADS, however, are hindered by high complexity, the need for sign corrections, and ambiguity. This paper proposes an accurate and unambiguous DOA estimation method for HADS with interleaved subarrays (HADSIS) under specific phase shift conditions. The method utilizes cross-correlation between signals received by adjacent subarrays to directly estimate the DOA through coherent accumulation. This approach simplifies DOA estimation and eliminates ambiguity, thereby significantly enhancing estimation efficiency. Furthermore, the sign of the cross-correlation is uniquely determined by the parity of the number of subarrays, eliminating the need for further sign corrections during signal accumulation. Finally, simulation experiments are conducted to validate the performance of the proposed method. Our approach enhances the SNR of the cross-correlation results, thereby ensuring more accurate DOA estimation. Its key features include low computational complexity and high accuracy.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"232 ","pages":"Article 109925"},"PeriodicalIF":3.4000,"publicationDate":"2025-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Signal Processing","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0165168425000404","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0
Abstract
The large-scale, partially connected phase-shifter Hybrid Analog-Digital System (HADS) has attracted significant attention due to its low hardware complexity, high reconfigurability, and robustness to failures. Direction-of-Arrival (DOA) estimation presents a critical challenge in HADS, as it directly impacts the Signal-to-Noise Ratio (SNR) and throughput. Existing DOA estimation methods in HADS, however, are hindered by high complexity, the need for sign corrections, and ambiguity. This paper proposes an accurate and unambiguous DOA estimation method for HADS with interleaved subarrays (HADSIS) under specific phase shift conditions. The method utilizes cross-correlation between signals received by adjacent subarrays to directly estimate the DOA through coherent accumulation. This approach simplifies DOA estimation and eliminates ambiguity, thereby significantly enhancing estimation efficiency. Furthermore, the sign of the cross-correlation is uniquely determined by the parity of the number of subarrays, eliminating the need for further sign corrections during signal accumulation. Finally, simulation experiments are conducted to validate the performance of the proposed method. Our approach enhances the SNR of the cross-correlation results, thereby ensuring more accurate DOA estimation. Its key features include low computational complexity and high accuracy.
期刊介绍:
Signal Processing incorporates all aspects of the theory and practice of signal processing. It features original research work, tutorial and review articles, and accounts of practical developments. It is intended for a rapid dissemination of knowledge and experience to engineers and scientists working in the research, development or practical application of signal processing.
Subject areas covered by the journal include: Signal Theory; Stochastic Processes; Detection and Estimation; Spectral Analysis; Filtering; Signal Processing Systems; Software Developments; Image Processing; Pattern Recognition; Optical Signal Processing; Digital Signal Processing; Multi-dimensional Signal Processing; Communication Signal Processing; Biomedical Signal Processing; Geophysical and Astrophysical Signal Processing; Earth Resources Signal Processing; Acoustic and Vibration Signal Processing; Data Processing; Remote Sensing; Signal Processing Technology; Radar Signal Processing; Sonar Signal Processing; Industrial Applications; New Applications.