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Through-the-wall radar imaging (TWRI) is receiving a considerable attention recently due to its diverse applications. One of the impinging challenges is the multipath propagation from the surrounding environment and even targets themselves. Multipath propagation produces ghost targets which populate the scene and not only create confusion with genuine targets but deteriorate the performance of compressive...
Direction of arrival (DOA) estimation has many applications in beam-steering to improve signal reception and interference suppression. The number of sources in the scene of interest is usually very small. Thus, sparse reconstruction becomes a good candidate to work with reduced data sets. Recently, coprime arrays have been proposed for source localization. In this paper, a moving coprime array configuration...
Through-wall radar imaging (TWRI) is the technology that enables imaging obstructed objects using radio frequency (RF) antennas. Due to its vast applications, TWRI received considerable attentions in the past decade. Several modeling, algorithms, methodologies, and propositions were developed to advance this technology and make it more feasible. In this work, a high resolution ultra-wideband (UWB)...
The desirable characteristics of ultra-wideband (UWB) technology are challenged by formidable sampling frequency, performance degradation in the presence of multi-user interference, and complexity of the receiver due to the channel estimation process. In this paper, a low-rate-sampling technique is used to implement M-ary multiple access UWB communications, in both the detection and channel estimation...
Compressive sensing (CS) is proposed by many researchers as a solution to the formidable sampling requirements of the promising Ultra wideband technology (UWB). Previous research was evaluated by simulating the IEEE UWB channel model. This paper studies the behavior of compressive sensing for practical UWB signals and proposes approaches to enhance the signal reconstruction performance. Four practically-based...
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