Hua Chen;Junjie Li;Songjie Yang;Wei Liu;Yonina C. Eldar;Chau Yuen
{"title":"基于两个平行中心对称展开单素数阵列的三维近场源定位","authors":"Hua Chen;Junjie Li;Songjie Yang;Wei Liu;Yonina C. Eldar;Chau Yuen","doi":"10.1109/TWC.2025.3543616","DOIUrl":null,"url":null,"abstract":"Most near-field (NF) localization algorithms cannot deal with the underdetermined case, while those which can are computationally expensive due to employment of fourth-order cumulants. In this work, a low-complexity solution is provided for underdetermined three-dimensional (3-D) NF localization, by employing second-order statistics with a tailored array configuration named two parallel centrally symmetric unfold coprime (TPSC) array. Its implementation can be divided into three stages. Firstly, the proposed algorithm constructs two cross-correlation matrices based on the received array data, which eliminates the non-linear range-related information of NF signals. Secondly, covariance and vectorization operations are applied to these two cross-correlation matrices to form a virtual array with extended aperture. Finally, the two-dimensional (2-D) angle parameters are estimated by the sparse and parametric approach (SPA) and a phase retrieval operation, and then the one-dimensional (1-D) range parameter is achieved by the multiple signal classification (MUSIC) algorithm. One specific feature is that the estimated angle and range parameters are matched automatically. An analysis of the properties of the TPSC array is provided, and an optimal parameter configuration is derived, given that the total number of array elements is fixed. Simulation results demonstrate that the designed TPSC array can achieve underdetermined 3-D NF localization, and deliver enhanced estimation capabilities, surpassing those of established algorithms.","PeriodicalId":13431,"journal":{"name":"IEEE Transactions on Wireless Communications","volume":"24 6","pages":"4738-4749"},"PeriodicalIF":10.7000,"publicationDate":"2025-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Near-Field Source Localization in 3-D Using Two Parallel Centrally Symmetric Unfold Coprime Array\",\"authors\":\"Hua Chen;Junjie Li;Songjie Yang;Wei Liu;Yonina C. Eldar;Chau Yuen\",\"doi\":\"10.1109/TWC.2025.3543616\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Most near-field (NF) localization algorithms cannot deal with the underdetermined case, while those which can are computationally expensive due to employment of fourth-order cumulants. In this work, a low-complexity solution is provided for underdetermined three-dimensional (3-D) NF localization, by employing second-order statistics with a tailored array configuration named two parallel centrally symmetric unfold coprime (TPSC) array. Its implementation can be divided into three stages. Firstly, the proposed algorithm constructs two cross-correlation matrices based on the received array data, which eliminates the non-linear range-related information of NF signals. Secondly, covariance and vectorization operations are applied to these two cross-correlation matrices to form a virtual array with extended aperture. Finally, the two-dimensional (2-D) angle parameters are estimated by the sparse and parametric approach (SPA) and a phase retrieval operation, and then the one-dimensional (1-D) range parameter is achieved by the multiple signal classification (MUSIC) algorithm. One specific feature is that the estimated angle and range parameters are matched automatically. An analysis of the properties of the TPSC array is provided, and an optimal parameter configuration is derived, given that the total number of array elements is fixed. Simulation results demonstrate that the designed TPSC array can achieve underdetermined 3-D NF localization, and deliver enhanced estimation capabilities, surpassing those of established algorithms.\",\"PeriodicalId\":13431,\"journal\":{\"name\":\"IEEE Transactions on Wireless Communications\",\"volume\":\"24 6\",\"pages\":\"4738-4749\"},\"PeriodicalIF\":10.7000,\"publicationDate\":\"2025-02-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Transactions on Wireless Communications\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10906419/\",\"RegionNum\":1,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Wireless Communications","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10906419/","RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
Near-Field Source Localization in 3-D Using Two Parallel Centrally Symmetric Unfold Coprime Array
Most near-field (NF) localization algorithms cannot deal with the underdetermined case, while those which can are computationally expensive due to employment of fourth-order cumulants. In this work, a low-complexity solution is provided for underdetermined three-dimensional (3-D) NF localization, by employing second-order statistics with a tailored array configuration named two parallel centrally symmetric unfold coprime (TPSC) array. Its implementation can be divided into three stages. Firstly, the proposed algorithm constructs two cross-correlation matrices based on the received array data, which eliminates the non-linear range-related information of NF signals. Secondly, covariance and vectorization operations are applied to these two cross-correlation matrices to form a virtual array with extended aperture. Finally, the two-dimensional (2-D) angle parameters are estimated by the sparse and parametric approach (SPA) and a phase retrieval operation, and then the one-dimensional (1-D) range parameter is achieved by the multiple signal classification (MUSIC) algorithm. One specific feature is that the estimated angle and range parameters are matched automatically. An analysis of the properties of the TPSC array is provided, and an optimal parameter configuration is derived, given that the total number of array elements is fixed. Simulation results demonstrate that the designed TPSC array can achieve underdetermined 3-D NF localization, and deliver enhanced estimation capabilities, surpassing those of established algorithms.
期刊介绍:
The IEEE Transactions on Wireless Communications is a prestigious publication that showcases cutting-edge advancements in wireless communications. It welcomes both theoretical and practical contributions in various areas. The scope of the Transactions encompasses a wide range of topics, including modulation and coding, detection and estimation, propagation and channel characterization, and diversity techniques. The journal also emphasizes the physical and link layer communication aspects of network architectures and protocols.
The journal is open to papers on specific topics or non-traditional topics related to specific application areas. This includes simulation tools and methodologies, orthogonal frequency division multiplexing, MIMO systems, and wireless over optical technologies.
Overall, the IEEE Transactions on Wireless Communications serves as a platform for high-quality manuscripts that push the boundaries of wireless communications and contribute to advancements in the field.