Abstract

Through-the-wall radar imaging (TWRI) has attracted a great deal of attention in several sensitive applications, including rescue missions and military operations. Notwithstanding its broad range of applications, TWRI suffers from path-loss because distant targets experience more attenuation of signal power than those closer to the transceiver. This challenge may lead to missed targets with important information necessary for analysis and informed decision making. Responding to the challenge, we have developed a signal model with an effective path-loss compensator incorporating a free space exponent. Furthermore, multipath exploitation and compressive sensing techniques were employed to develop an effective algorithm for isolating residual clutter that may corrupt real targets. The proposed signal model integrates contributions from the front wall, multipath returns, and path-loss. Compared with the state-of-the-art model under the same experimental conditions, simulation results show that the proposed model achieves improved signal-to-clutter ratio, relative clutter peak, and probability of detection by 13.1%, 17.4% and 33.6%, respectively, suggesting that our model can represent the scene more accurately.

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