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Compressive sensing for multipolarization through-the-wall radar imaging

Chapter


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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 the measurement vectors

    before image formation is that the measurement 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.

    Analysis and comparison of experimental results demonstrate the effectiveness

    of the proposed through-the-wall radar imaging approach, especially in

    the presence of high-measurement noise.

Publication Date


  • 2014

Citation


  • A. Bouzerdoum, J. Yang & F. Tivive , "Compressive sensing for multipolarization through-the-wall radar imaging," in Compressive Sensing for Urban Radar, M. G. Amin, Ed. United States: CRC Press, 2014, pp.231-250.

Ro Full-text Url


  • http://ro.uow.edu.au/cgi/viewcontent.cgi?article=5372&context=eispapers

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers/4351

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 the measurement vectors

    before image formation is that the measurement 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.

    Analysis and comparison of experimental results demonstrate the effectiveness

    of the proposed through-the-wall radar imaging approach, especially in

    the presence of high-measurement noise.

Publication Date


  • 2014

Citation


  • A. Bouzerdoum, J. Yang & F. Tivive , "Compressive sensing for multipolarization through-the-wall radar imaging," in Compressive Sensing for Urban Radar, M. G. Amin, Ed. United States: CRC Press, 2014, pp.231-250.

Ro Full-text Url


  • http://ro.uow.edu.au/cgi/viewcontent.cgi?article=5372&context=eispapers

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers/4351

Book Title


  • Compressive Sensing for Urban Radar

Start Page


  • 231

End Page


  • 250