This paper provides a concise overview of recent developments in sparse antenna arrays,
with a specific focus on techniques for reducing mutual coupling. It explores the concept and …

Sparse arrays are widely employed in array signal processing due to their obvious
advantages in array element distribution and uniform degrees of freedom (uDOFs). In this …

For direction-of-arrival (DOA) estimation problems in a sparse domain, sparse Bayesian
learning (SBL) is highly favored by researchers owing to its excellent estimation …

Coprime and nested sparse arrays are two widely researched sparse arrays. These arrays,
requiring fewer sensors compared to full uniform linear arrays (ULAs), still have a high …

In correlation-based processing, sparse arrays offer the capacity to resolve a greater number
of uncorrelated sources than physical sensors due to the considerable breadth of their …

To solve the dilemma that the existing sparse arrays only limitedly enhance the array degree
of freedom (DOF) for noncircular sources, a novel nested array with graded spacing (GSNA) …

The spatial smoothing‐based and matrix reconstruction‐based decorrelation algorithms are
widely used to realize the accurate direction‐of‐arrival (DOA) estimation with the …

To reduce mutual coupling of an improved nested array (INA), the authors propose an
augmented improved nested array (AINA) by splitting the dense subarray of the INA into two …

In this paper, we propose a new sparse linear array (SLA) that enjoys a hole-free difference
co-array (DCA) and closed-form expressions for its sensor positions. The proposed …

For range, velocity and angle measurements, radar is a common technique to use, be it in
the automotive industry, defense industry, or for medical purposes. Radars can achieve …