February Fourier Talks 2016

Mansour Hassan

Mitsubishi Electric Research Laboratories (MERL)


Multipath Removal by Online Blind Deconvolution in Through-the-Wall-Imaging


We propose an online radar imaging scheme that recovers a sparse scene and removes the multipath ringing induced by the front wall in a Through-the-Wall-Imaging (TWI) system without prior knowledge of the wall parameters. Our approach uses online measurements obtained from individual transmitter-receiver pairs to incrementally build the primary response of targets behind the front wall and find a corresponding delay convolution operator that generates the multi-path reflections available in the received signal. In order to perform online sparse imaging while removing wall clutter reflections, we developed a deconvolution extension of the Sparse Randomized Kaczmarz (SRK) algorithm that finds sparse solutions to under- and over-determined linear systems of equations. Our scheme allows for imaging with nonuniformly spaced antennas by building an explicit delay-and-sum imaging operator for each new measurement. Moreover, the active memory requirements remain small even for large scale MIMO systems since the imaging operators are only constructed for individual transmitter-receiver pairs. We test our approach on a simple FDTD simulated room with internal targets and demonstrate that our method successfully eliminates multipath reflections while correctly locating the targets. Joint work with Ulugbek S. Kamilov.

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