{"title":"分布式合成孔径无源定位及最优几何构型研究","authors":"Junhua Yang;Hao Huan;Ziming Xu;Ran Tao","doi":"10.1109/LSP.2025.3610355","DOIUrl":null,"url":null,"abstract":"Synthetic aperture passive positioning (SAPP) has gradually become a hot spot in radiation source location research. However, there are relatively few studies on three-dimensional synthetic aperture passive positioning methods. Moreover, synthetic aperture passive positioning is significantly affected by residual frequency offsets (RFO) resulting from noncooperative operation between transceivers. To address the challenges, a distributed synthetic aperture passive positioning method is proposed. Considering frequency synchronization among platforms, this method leverages the SAPP algorithm to obtain high-precision slant angles. Subsequently, it formulates positioning equations related to the 3D target position and RFO. The distributed geometric configuration is studied under certain constraints, and the analytical solutions for the optimal configuration are obtained. Space-borne simulations illustrate that the positioning accuracy of the proposed method is an order of magnitude higher compared to that of the FOA, FDOA, and DOA methods. Additionally, airborne experiments indicate that in the presence of RFO, the proposed method improves the positioning accuracy by two orders of magnitude and exhibits strong convergence properties.","PeriodicalId":13154,"journal":{"name":"IEEE Signal Processing Letters","volume":"32 ","pages":"3685-3689"},"PeriodicalIF":3.9000,"publicationDate":"2025-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Research on Distributed Synthetic Aperture Passive Positioning and Optimal Geometric Configuration\",\"authors\":\"Junhua Yang;Hao Huan;Ziming Xu;Ran Tao\",\"doi\":\"10.1109/LSP.2025.3610355\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Synthetic aperture passive positioning (SAPP) has gradually become a hot spot in radiation source location research. However, there are relatively few studies on three-dimensional synthetic aperture passive positioning methods. Moreover, synthetic aperture passive positioning is significantly affected by residual frequency offsets (RFO) resulting from noncooperative operation between transceivers. To address the challenges, a distributed synthetic aperture passive positioning method is proposed. Considering frequency synchronization among platforms, this method leverages the SAPP algorithm to obtain high-precision slant angles. Subsequently, it formulates positioning equations related to the 3D target position and RFO. The distributed geometric configuration is studied under certain constraints, and the analytical solutions for the optimal configuration are obtained. Space-borne simulations illustrate that the positioning accuracy of the proposed method is an order of magnitude higher compared to that of the FOA, FDOA, and DOA methods. Additionally, airborne experiments indicate that in the presence of RFO, the proposed method improves the positioning accuracy by two orders of magnitude and exhibits strong convergence properties.\",\"PeriodicalId\":13154,\"journal\":{\"name\":\"IEEE Signal Processing Letters\",\"volume\":\"32 \",\"pages\":\"3685-3689\"},\"PeriodicalIF\":3.9000,\"publicationDate\":\"2025-09-15\",\"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/11164561/\",\"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}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Signal Processing Letters","FirstCategoryId":"5","ListUrlMain":"https://ieeexplore.ieee.org/document/11164561/","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}
Research on Distributed Synthetic Aperture Passive Positioning and Optimal Geometric Configuration
Synthetic aperture passive positioning (SAPP) has gradually become a hot spot in radiation source location research. However, there are relatively few studies on three-dimensional synthetic aperture passive positioning methods. Moreover, synthetic aperture passive positioning is significantly affected by residual frequency offsets (RFO) resulting from noncooperative operation between transceivers. To address the challenges, a distributed synthetic aperture passive positioning method is proposed. Considering frequency synchronization among platforms, this method leverages the SAPP algorithm to obtain high-precision slant angles. Subsequently, it formulates positioning equations related to the 3D target position and RFO. The distributed geometric configuration is studied under certain constraints, and the analytical solutions for the optimal configuration are obtained. Space-borne simulations illustrate that the positioning accuracy of the proposed method is an order of magnitude higher compared to that of the FOA, FDOA, and DOA methods. Additionally, airborne experiments indicate that in the presence of RFO, the proposed method improves the positioning accuracy by two orders of magnitude and exhibits strong convergence properties.
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.