Estimation of frequency-dependent parameters of unknown walls for enhanced through-the-wall imaging

Thajudeen, Christopher; Hoorfar, Ahmad; Zhang, Wenji

doi:10.1109/aps.2011.5997179

Cited by 33 publications

(16 citation statements)

References 13 publications

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“…The received signals are preprocessed by removing the strong wall returns, using background subtraction, and the common signal at each antenna location. If the background signal is not available, then the strong wall returns can be mitigated using wall parameter estimation techniques that do not require the full measurement set [25]. The received signals from each polarization channel are first processed using DS beamforming to form three images.…”

Section: Experimental Results Using Real Datamentioning

confidence: 99%

Sparsity-Aware Human Motion Indication

Bouzerdoum

Yang

Tivive

2017

Compressive Sensing for Urban Radar

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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.

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Section: Experimental Results Using Real Datamentioning

confidence: 99%

Sparsity-Aware Human Motion Indication

Bouzerdoum

Yang

Tivive

2017

Compressive Sensing for Urban Radar

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“…The estimation of wall parameters associated with single or multilayered building walls has been extensively studied in the past decade within the framework of a one-dimensional inverse scattering problem [27][28][29][30][31][32][33][34]. For a single-layer wall, radar-based closed-form estimation of the wall dielectric constant, conductivity, and thickness is given in [30,31].…”

Section: Numerical Resultsmentioning

confidence: 99%

Two- and Three-Dimensional Fast Intrawall Imaging with Microwave Tomographic Algorithm

Zhang

Hoorfar

Thajudeen

2018

International Journal of Antennas and Propagation

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A fast and efficient microwave tomographic algorithm is proposed for 2-D and 3-D real-time intrawall imaging. The exploding reflection model is utilized to simplify the imaging formulation, and the half-space Green's function is expanded in the spectral domain to facilitate the easy implementation of the imaging algorithm with the fast Fourier transform (FFT) and inverse fast Fourier transform (IFFT). The linearization of the inversion scheme and employment of FFT/IFFT in the imaging formula make the algorithm suitable for various applications pertaining to the inspection of a large probed region and allow real-time processing. Representative numerical and experimental results are presented to show the effectiveness and efficiency of the proposed algorithm for real-time intrawall characterization.

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“…Hence, τ pn can be calculated from geometric considerations [1], [2]. For a method to obtain accurated estimates of the relevant wall parameters, refer to [16].…”

Section: Signal Modelmentioning

confidence: 99%

CS based wall ringing and reverberation mitigation for through-the-wall radar imaging

Leigsnering

Ahmad

Amin

et al. 2013

2013 IEEE Radar Conference (RadarCon13)

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Wall ringing and reverberation pose a challenging problem for through-the-wall radar image formation algorithms. We propose a novel method based on compressive sensing (CS) that enables high reconstruction quality combined with efficient data collection. A joint wall reverberation and target model is developed and the reconstructed scene is obtained based on a group sparse CS approach. Thus, the wall returns can be separated from the target returns resulting in a clean image. We demonstrate the performance using simulation results.

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Estimation of frequency-dependent parameters of unknown walls for enhanced through-the-wall imaging

Cited by 33 publications

References 13 publications

Sparsity-Aware Human Motion Indication

Sparsity-Aware Human Motion Indication

Two- and Three-Dimensional Fast Intrawall Imaging with Microwave Tomographic Algorithm

CS based wall ringing and reverberation mitigation for through-the-wall radar imaging

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