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 difference coarrays, originating from variations in the locations ...

Dual-function radar and communications (DFRC) systems based on multiple-input multiple-output (MIMO) arrays have received considerable attention in recent years due to their excellent ability to alleviate spectrum congestion. The MIMO DFRC ...

• The joint design of precoding and antenna selection for MIMO DFRC is proposed.
• The indirect precoding method is proposed to address the joint optimization problem.
• The direct precoding method is proposed to directly optimize the ...

Signal processing via subspace-based methods require subspace estimates taken from either the eigenvectors of the sample covariance matrix or the principal singular vectors of the received data matrix. The subspaces spanned by the singular ...

• Decomposition of received array data matrix provides zeroth-order perturbed subspace basis.
• Second-order perturbation analysis increases optimality of noise-free subspace estimation.
• Second-order subspace optimality depends on ...

Sparse arrays possess attractive features compared to uniform linear arrays (ULAs) with increased degrees of freedom (DOFs), reduced mutual coupling, and enlarged array aperture, which improves the estimation performance of arrays. Recently, ...

• A fragmented coprime array concept is introduced to enlarge array aperture.
• Provide the location of holes in the difference coarray of FCAs.
• Two missing interlayer subarrays fills the holes in the difference coarray of FCAs.
• ...

Photoacoustic computed tomography (PACT) is a non-invasive biomedical imaging technology that has developed rapidly in recent decades, especially has shown potential for small animal studies and early diagnosis of human ...

• The adaptive machine learning model (AMLM) improves photoacoustic image quality under sparse array sampling condition.
• AMLM predicts and completes the sampling data and suppresses artifacts in the reconstructed photoacoustic images.

In the area of direction-of-arrival (DOA) estimate research, Unknown mutual coupling (UMC) causes significant interference with the array’s localization performance. Although the sparsity of the structure of the sparse array can weaken the mutual ...

In this paper, we propose a tensor-based subspace algorithm for the two-dimensional direction of arrival (2D-DOA) estimation using a sparse array equipped with electromagnetic vector sensors (EMVS). Our approach capitalizes on the multidimensional ...

We investigate the problem of designing an unequally spaced symmetric linear array with a minimum number of elements. For unequally spaced arrays, simultaneously tuning all the elements' positions and weights leads to a non-convex ...

• Combine scaled coarrays into a synthetic virtual array with increased DOFs.
• ...

This paper presents gridless schemes for direction finding of wideband sources using sparse array with nonuniform noise. According to the frequencies relationship, we obtain multiple equivalent scaled difference coarrays, which are ...

To address the issue that existing direction-finding approaches perform poorly under impulse noise and do not work well in underdetermined scenarios, a novel sparse array direction-finding approach on the background of impulse noise is proposed in ...

The recent criteria for designing sparse arrays used in many applications are the number of degrees of freedom (DoFs) and mutual coupling. In this paper, two optimized sparse nested arrays, called OSNA-I and OSNA-II, are proposed for the ...

Recently, the design of sparse arrays for direction-of-arrival (DOA) estimation has gained considerable attention due to their ability to yield a sizeable virtual aperture, enhanced degrees-of-freedom (DOF), and high-resolution DOA ...

Currently, the covariance matrix (CM) or pseudo CM of the received signal is processed to improve the degrees of freedom (DOFs) and estimation accuracy. This is where the second-order cumulant (SOC) in the two-dimensional (2-D) direction-of-...

In the design of a sparse array with large uniform degree of freedom (uDOF) for direction finding, the minimum inter-antenna spacing is usually constrained to be no more than half-wavelength. This is not attractive for reducing antenna ...

In the present study, the generalized compressed nested array (GCNA) is proposed to improve the fourth-order cumulant-based direction of arrival (DOA) estimation performance when the small-scale array is deployed. The main objective of this study ...

Aiming at the problem that traditional Direction of Arrival (DOA) estimation methods cannot handle multi-source with high accuracy while increasing the degree of freedom, proposing a new two-dimensional DOA estimation method based on coprime array MIMO ...

• A patch target model, suitably optimized for the sensor and scene geometry, suppresses grating lobes associated with sparse imaging arrays.

In this paper, we develop a theoretical framework for short-range millimeter (mm) wave radar imaging using a sparse array of monostatic elements, and validate it via experiments. The framework is a significant departure from classical ...

The coprime array is a recently developed sparse array that is widely used in direction-of-arrival (DOA) estimation. The degree of freedom (DOF) for existing coprime arrays relies on the virtual array model, which is limited to the ...

This paper reformulates the problem of direction-of-arrival (DOA) estimation for sparse array from a variational Bayesian perspective. In this context, we propose a hierarchical prior for the signal coefficients that amounts marginally ...

High resolution three-dimensional (3D) imaging method using MIMO radar with sparse array is studied in this paper. A method based on compressive sensing (CS) is firstly given. However, the CS-based method has the off-grid problem which will reduce the ...