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In this paper we consider the classical problem of blind deconvolution of multiple signals from its superposition, also called blind demixing and deconvolution. One is given a signal ∑ri=1 wi ∗ xi = y ∊ RL which is the superposition of r unknown source signals {xi}ri=1 and convolution kernels {wi}ri=1 The goal is to reconstruct the vectors w; and x;, which are elements of known but random subspaces...
Radar-detection metrics are assessed in outcomes of sparse-signal processing (SSP) with test statistics based on the subgradient and the dual feasibility in the SSP optimization via an approach separating false alarms (FAs) from targets. In radar, SSP is aimed for estimating a sparse solution whose FAs are fixed and whose detection of targets is optimal as in traditional detection. Existing detection...
Synthetic Aperture Radar (SAR) interferometry has been the subject of an intensive development in the last years thanks to crucial applications in the area of risk monitoring. The emergence of very high resolution X-Band sensors has increased the interest in application to urban area. Advances of SAR interferometry has been provided by the extension toward SAR tomography. By transforming classical...
The elastic net (EN) is a popular regularization and variable selection method that overcomes the shortcomings of Lasso such as poor recovery in the face of high mutual coherence. In this paper, we develop an efficient algorithm to solve the weighted EN criterion for complex-valued measurements applying the cyclic coordinate descent approach. We illustrate that usage of smartly chosen adaptive (i...
Using a compressive sensing framework, we investigate the performance of a practicable sub-Nyquist radar system, which is based on a set of parallel bandpass filters for extracting range information of sparse target objects. In particular, the system employs an equivalent measurement matrix optimized based on a sparse ruler approach known from combinatorical number theory. First, we address the connection...
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