{"title":"Low interactive direct position determination of radio emitters with hybrid measurements","authors":"Ming-Yi You , Lin Gao , Yun-Xia Ye , Wei Wang","doi":"10.1016/j.sigpro.2025.109987","DOIUrl":null,"url":null,"abstract":"<div><div>This paper proposes a direct position determination (DPD) method for stationary and moving non-cooperative sources. Employing an unbalanced group of measurements consisting of uncompressed measurements at the central receiver and compressed measurements from all other auxiliary receivers, the method estimates the source position directly in the hybrid measurement domain without original signal recovering, where the compressing matrix is not restricted to any specific form. A block coordinate descent (BCD)-like iterative algorithm is proposed to handle the high-dimensional optimization problem of joint position and velocity estimation for moving emitters, where a generalized cross ambiguity function (GCAF) is proposed to extract the time-differences-of-arrival (TDOA) parameters from the hybrid measurements to initialize the iteration process. In addition, the hybrid measurements-based Cramér–Rao lower bound (CRLB) for emitter position is derived for performance evaluation. Several numerical case studies are carried out to evaluate the effectiveness of the proposed DPD method as well as the proposed GCAF. The proposed method is expected to extend the applicability of compressive sensing (CS)-based DPD to cases where there is relative radial motion between the source.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"234 ","pages":"Article 109987"},"PeriodicalIF":3.4000,"publicationDate":"2025-03-11","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/S016516842500101X","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 proposes a direct position determination (DPD) method for stationary and moving non-cooperative sources. Employing an unbalanced group of measurements consisting of uncompressed measurements at the central receiver and compressed measurements from all other auxiliary receivers, the method estimates the source position directly in the hybrid measurement domain without original signal recovering, where the compressing matrix is not restricted to any specific form. A block coordinate descent (BCD)-like iterative algorithm is proposed to handle the high-dimensional optimization problem of joint position and velocity estimation for moving emitters, where a generalized cross ambiguity function (GCAF) is proposed to extract the time-differences-of-arrival (TDOA) parameters from the hybrid measurements to initialize the iteration process. In addition, the hybrid measurements-based Cramér–Rao lower bound (CRLB) for emitter position is derived for performance evaluation. Several numerical case studies are carried out to evaluate the effectiveness of the proposed DPD method as well as the proposed GCAF. The proposed method is expected to extend the applicability of compressive sensing (CS)-based DPD to cases where there is relative radial motion between the source.
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.