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A Novel Localization System in SAR-Demining Applications Using Invariant Radar Channel Fingerprints.
Karsch, Nicholas; Schulte, Hendrik; Musch, Thomas; Baer, Christoph.
Afiliação
  • Karsch N; Faculty of Electrical Engineering and Information Technology, Institute of Electronic Circuits, Ruhr University Bochum, Universitaetsstr. 150, 44801 Bochum, Germany.
  • Schulte H; Faculty of Electrical Engineering and Information Technology, Institute of Electronic Circuits, Ruhr University Bochum, Universitaetsstr. 150, 44801 Bochum, Germany.
  • Musch T; Faculty of Electrical Engineering and Information Technology, Institute of Electronic Circuits, Ruhr University Bochum, Universitaetsstr. 150, 44801 Bochum, Germany.
  • Baer C; Faculty of Electrical Engineering and Information Technology, Institute of Electronic Circuits, Ruhr University Bochum, Universitaetsstr. 150, 44801 Bochum, Germany.
Sensors (Basel) ; 22(22)2022 Nov 10.
Article em En | MEDLINE | ID: mdl-36433287
In this paper, we present a novel two dimensional (2D) frequency-modulated continuous-wave (FMCW) localization method for handheld systems based on the extraction of distinguishable subchannel fingerprints. Compared with other concepts, only one subdivided radar source channel is needed in order to instantly map a one-dimensional measurement to higher-dimensional space coordinates. The additional information of the detected target is implemented with low-cost hardware component features, which exhibit distinguishable space-dependent fingerprint codes. Using the given a priori information of the hardware thus leads to a universally applicable extension for low-cost synthetic aperture radar (SAR)-demining purposes. In addition to the description of the system concept and its requirements, the signal processing steps and the hardware components are presented. Furthermore, the 2D localization accuracy of the system and the classification accuracy of the frequency-coded fingerprints are described in a defined test environment to proof the operational reliability of the realized setup, reaching a classification accuracy of 94.7% and an averaged localization error of 4.9 mm.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Radar / Processamento de Sinais Assistido por Computador Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Radar / Processamento de Sinais Assistido por Computador Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2022 Tipo de documento: Article