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Compressive sensing for multipolarization through-the-wall radar imaging

Chapter


Abstract


  • Discrimination of targets can be improved significantly by analyzing the polarization of scattered electromagnetic waves. In radar imaging, the target image can be enhanced by combining measurements from different polarizations. In this chapter, we propose a joint image formation and fusion approach for multipolarization through-the-wall radar imaging, using compressive sensing (CS). The measurements from different polarization channels are processed jointly using the multiple measurement vector (MMV) model to produce several images of the scene, each corresponding to a polarization channel. Furthermore, the measurement vectors are fused together to form a composite measurement vector, which yields a composite image of the scene. The advantage of fusing themeasurement vectors before image formation is that themeasurement noise is reduced and the target information is enhanced, which leads to a more informative composite image. The MMV model enforces the same sparsity support for all formed images by reinforcing target information across channels and attenuating noise. Experimental results are presented using simulated and real data.

Publication Date


  • 2017

Citation


  • Bouzerdoum, A., Yang, J., & Tivive, F. H. C. (2017). Compressive sensing for multipolarization through-the-wall radar imaging. In Compressive Sensing for Urban Radar (pp. 231-250). doi:10.1201/b17252

International Standard Book Number (isbn) 13


  • 9781466597846

Scopus Eid


  • 2-s2.0-85051937985

Web Of Science Accession Number


Book Title


  • Compressive Sensing for Urban Radar

Start Page


  • 231

End Page


  • 250

Abstract


  • Discrimination of targets can be improved significantly by analyzing the polarization of scattered electromagnetic waves. In radar imaging, the target image can be enhanced by combining measurements from different polarizations. In this chapter, we propose a joint image formation and fusion approach for multipolarization through-the-wall radar imaging, using compressive sensing (CS). The measurements from different polarization channels are processed jointly using the multiple measurement vector (MMV) model to produce several images of the scene, each corresponding to a polarization channel. Furthermore, the measurement vectors are fused together to form a composite measurement vector, which yields a composite image of the scene. The advantage of fusing themeasurement vectors before image formation is that themeasurement noise is reduced and the target information is enhanced, which leads to a more informative composite image. The MMV model enforces the same sparsity support for all formed images by reinforcing target information across channels and attenuating noise. Experimental results are presented using simulated and real data.

Publication Date


  • 2017

Citation


  • Bouzerdoum, A., Yang, J., & Tivive, F. H. C. (2017). Compressive sensing for multipolarization through-the-wall radar imaging. In Compressive Sensing for Urban Radar (pp. 231-250). doi:10.1201/b17252

International Standard Book Number (isbn) 13


  • 9781466597846

Scopus Eid


  • 2-s2.0-85051937985

Web Of Science Accession Number


Book Title


  • Compressive Sensing for Urban Radar

Start Page


  • 231

End Page


  • 250