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  4. Radar Band Fusion Using Frame-Based Compressed Sensing
 
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2023
Journal Article
Title

Radar Band Fusion Using Frame-Based Compressed Sensing

Abstract
Existing compressed sensing algorithms fail when applied to radar target detection in the presence of a large gap in the frequency band, i.e., presence of signals in separate, discontinuous bands. A new algorithm based on a subdivision-fusion scheme is proposed to solve this problem. The main goal is to use a structured sensing matrix based on radar signals to an advantage and obtain a good range resolution in spite of high coherence. Parameters influencing the performance of the algorithm are discussed. Simulative examples and results based on real measurement data are presented. The results show superior performance of the proposed method in the presence of band gaps.
Author(s)
Guha, Sanhita
Fraunhofer-Institut für Hochfrequenzphysik und Radartechnik FHR  
Bathelt, Andreas
Fraunhofer-Institut für Hochfrequenzphysik und Radartechnik FHR  
Heredia Conde, Miguel Heredia
Ender, Joachim  
Fraunhofer-Institut für Hochfrequenzphysik und Radartechnik FHR  
Journal
IEEE journal of selected topics in signal processing  
Open Access
DOI
10.1109/JSTSP.2022.3220403
Language
English
Fraunhofer-Institut für Hochfrequenzphysik und Radartechnik FHR  
Keyword(s)
  • Coherence

  • coherence minimization

  • Compressed Sensing

  • fusion

  • Mathematical models

  • Radar

  • radar

  • Radar detection

  • range resolution

  • Reflectivity

  • Sensors

  • Signal processing algorithms

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