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  4. Track Evaluation of GSM based Passive Radar: Model vs. Real-World Results
 
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2024
Conference Paper
Title

Track Evaluation of GSM based Passive Radar: Model vs. Real-World Results

Abstract
Closing the feedback loop has proven essential for performance improvement and enhancing system reliability in a number of applications. Track evaluation addresses these goals by investigating system influences and analyzing discrepancies between expected and actual operation. Developing a model of a passive radar system which approximates its operational capabilities is therefore not only essential for performance prediction and pre-operational analysis but offers the opportunity for further system improvement. In the following, we assess the fit of a passive radar model to real-world data to investigate if it provides a reasonable representation of the observed results. There, we show that the detection probability model as well as the estimated lower bound on achievable estimation accuracy, where we utilize the Cramér-Rao Lower Bound (CRLB), give a reasonable approximation of real-world results collected by a passive radar system which utilizes Global System for Mobile Communications (GSM) signals.
Author(s)
Handke, Sebastian Thomas  
Fraunhofer-Institut für Kommunikation, Informationsverarbeitung und Ergonomie FKIE  
Brötje, Martina  
Fraunhofer-Institut für Kommunikation, Informationsverarbeitung und Ergonomie FKIE  
Steffes, Christian  
Fraunhofer-Institut für Kommunikation, Informationsverarbeitung und Ergonomie FKIE  
Koch, Wolfgang
Fraunhofer-Institut für Kommunikation, Informationsverarbeitung und Ergonomie FKIE  
Mainwork
27th International Conference on Information Fusion, FUSION 2024  
Conference
International Conference on Information Fusion 2024  
DOI
10.23919/FUSION59988.2024.10706434
Language
English
Fraunhofer-Institut für Kommunikation, Informationsverarbeitung und Ergonomie FKIE  
Keyword(s)
  • Cramér-Rao lower bound

  • mobile communication based PCL

  • multistatic radar

  • passive radar

  • performance prediction

  • Track evaluation

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