Adaptive beamforming using sparse arrays can alleviate system burden with a sub-Nyquist
sampling rate while achieving high resolution. To process multi-dimensional signals without …

Adaptive beamforming plays an increasingly vital role in various applications, including
radar, sonar, telecommunications, and many other related fields. In this paper, we present …

Direction-of-arrival (DOA) estimation using sub-Nyquist tensor signals benefits from
enhanced performance by extracting structural angular information with multi-dimensional …

We recently extended the degrees of freedom for the bistatic multiple-input multiple-output
(MIMO) radar by exploiting sparse array motion at the receiver part, and considered the …

The integration of digital twin technology and the Metaverse has attracted widespread
attention in the field of consumer health. Meanwhile, the immersive virtual world, Metaverse …

A three-dimensional (3-D) near-field (NF) source localization method is introduced for a
bistatic multiple-input multiple-output (MIMO) radar system equipped with arbitrary …

Compared with the traditional subspace-based methods, sparse signal recovery (SSR)
based methods have obvious advantages in performing the direction of arrival (DOA) …

We consider signal source localization from range-difference measurements. First, we give
some readily-checked conditions on measurement noises and sensor deployment to …

Compared with the commonly used Cramér-Rao bound, the Ziv-Zakai bound (ZZB) is a
global tight lower bound for evaluating the performance of parameter estimators. However …

Many real-life signal-based applications use the Tucker decomposition of a high
dimensional/order tensor. A well-known problem with the Tucker model is that its number of …