This letter proposes a dictionary learning algorithm for solving the grid mismatch problem in
direction of arrival (DOA) estimation from both the array sensor data and from the sign of the …

In this letter, we propose a new accurate approach for target localization in multiple-input
multiple-output (MIMO) radars, which exploits the sparse spatial distribution of targets to …

In order to realize the advantages of the massive MIMO systems, the channel state
information must be obtained at the base station (BS). However, it is a challenging task in …

We propose a new inverse scattering technique based on sparsity for the application of
microwave imaging. The underdetermined inverse problem appeared in the distorted born …

Recovering low-rank and sparse components from missing observations is an essential
problem in various fields. In this paper, we have proposed a method to address the missing …

In this paper, we investigate the problem of non-linear time-varying regression in a wireless
sensor network system. A field over an area is estimated using a number of fixed sensors …

In this paper, a Block Iterative Method with Adaptive Thresholding for Sparse Recovery
(BIMATSR) is proposed to recover the received signal in an under-sampled distributed …

Copy‐move forgery (CMF) detection is one of the most practical problems in image
forensics. The authenticity of the image becomes more crucial when the images are used in …

In Massive multiple-input multiple-output (MIMO) systems, channel estimation is crucial. The
large size of the antennas causes a significant pilot and feedback overhead, making it …

Direction of arrival (DOA) estimation is an essential task in the array signal processing. In
this study, the authors attempt to address the off‐grid issue for the two‐dimensional (2D) …