{"title":"Cramér-Rao Bounds and Resolution Benefits of Sparse Arrays in Measurement-Dependent SNR Regimes","authors":"Sina Shahsavari;Piya Pal","doi":"10.1109/LSP.2024.3525400","DOIUrl":null,"url":null,"abstract":"This paper derives new non-asymptotic characterization of the Cramér-Rao Bound (CRB) of any sparse array as a function of the angular separation between two far-field narrowband sources in certain regimes characterized by a low Signal-to-Noise Ratio (SNR). The primary contribution is the derivation of matching upper and lower bounds on the CRB in a certain measurement-dependent SNR (MD-SNR) regime, where one can zoom into progressively lower SNR as the number of sensors increases. This tight characterization helps to establish that sparse arrays such as nested and coprime arrays provably exhibit lower CRB compared to Uniform Linear Arrays (ULAs) in the specified SNR regime.","PeriodicalId":13154,"journal":{"name":"IEEE Signal Processing Letters","volume":"32 ","pages":"601-605"},"PeriodicalIF":3.2000,"publicationDate":"2025-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Signal Processing Letters","FirstCategoryId":"5","ListUrlMain":"https://ieeexplore.ieee.org/document/10820977/","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
This paper derives new non-asymptotic characterization of the Cramér-Rao Bound (CRB) of any sparse array as a function of the angular separation between two far-field narrowband sources in certain regimes characterized by a low Signal-to-Noise Ratio (SNR). The primary contribution is the derivation of matching upper and lower bounds on the CRB in a certain measurement-dependent SNR (MD-SNR) regime, where one can zoom into progressively lower SNR as the number of sensors increases. This tight characterization helps to establish that sparse arrays such as nested and coprime arrays provably exhibit lower CRB compared to Uniform Linear Arrays (ULAs) in the specified SNR regime.
期刊介绍：
The IEEE Signal Processing Letters is a monthly, archival publication designed to provide rapid dissemination of original, cutting-edge ideas and timely, significant contributions in signal, image, speech, language and audio processing. Papers published in the Letters can be presented within one year of their appearance in signal processing conferences such as ICASSP, GlobalSIP and ICIP, and also in several workshop organized by the Signal Processing Society.
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