Abstract
Multipath exploitation with compressive sensing (CS) has been successfully applied in through-the-wall radar imaging (TWRI) given prior knowledge of the room geometry. However, in most practical applications and critical missions, the geometry of the room is not known. In this paper dynamic wall pursuit algorithm is proposed to simultaneously recover the room geometry and image the scene behind the wall. We demonstrate that moving targets increase the wall reconstruction accuracy. The algorithm exploits the fact that wrong wall positions populate the reconstructed image with false targets. It makes use of the moving targets in the scene to increase the certainty of the detected wall positions. Simulated results show the effectiveness of this method even at low SNR values.
Highlights
Through-the-wall radar imaging (TWRI) aims at sensing through building walls using radio frequency (RF) signals
The scene is interrogated using a Gaussian pulse of width 0.73 ns and carrier frequency of 1 GHz
Four perfect reflection point-targets are located behind the front wall in a 2.6 m × 2 m room
Summary
Through-the-wall radar imaging (TWRI) aims at sensing through building walls using radio frequency (RF) signals. If only direct path returns are considered, multipath signals will cause ghosts in the reconstructed image. When wall positions are incorrectly rebuilt in the dictionary, wrong multipath propagation delays will create ghost targets in the reconstructed image. Utilizing this fact, we propose a novel and effective reconstruction technique, that jointly estimates walls and targets and reconstructs a ghost-free image. Due to its superior performance at both low and high SNR, YALL1 is adopted for the remaining part of this work
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