Synthesis of planar sparse arrays by perturbed compressive sampling framework

Abstract

Recently, compressive sensing (CS) theory has been applied for synthesising maximally sparse arrays, in which the best subset of sampling element locations is chosen to compose a sparse array for matching a desired radiation pattern. However, their performances are strongly depended on the proper setting of the initial sampling locations, which are typically obtained by gridding the continuous array aperture. Such a setting is usually hard to handle for large planar array synthesis. To address this problem, a precision and effective method based on the perturbed compressive sampling (PCS) is proposed. Position perturbation variables are augmented to the traditional CS‐based model, which allow continuous element placement. Then, a joint sparse recovery approach is used to optimise the excitations and position perturbations of the elements simultaneously. Moreover, the authors implement an extended PCS model with a secondary grid strategy to reduce the modelling error and the computational cost. The proposed design problem is solved with a general sparse recovery solver, named FOCal under‐determined system solver. Numerical results show that the method yields a higher array sparsity, a faster computational speed and a better pattern matching accuracy than the existing CS‐based methods.

Pattern Synthesis of Time-Modulated Sparse Array by an OPM-CVX Algorithm

“…Compared with the array with uniform spacing of half wavelength, 58% of the array elements were saved. Shen [8] and Yan [9] both constrained the aperture of sparse array and synthesized flat top beam and pencil beam. Shen [8] used the unitary matrix pencil method to solve the excitation and element position of linear array, which improves the matching accuracy of shaped beam and reduces the computational complexity.…”

“…However, the dynamic range ratio (DRR) was still greater than 10. Yan [9] adopted the perturbed compressive sampling (PCS) algorithm to optimize the excitation and element position at the same time, which improves the matching accuracy of pattern and obtains a large DRR too. A lot of achievements have been made in the pattern synthesis of sparse arrays.…”

Synthesis of sparse planar antenna arrays with multiple constraints

“…Pattern synthesis of antenna arrays is one of the most important research areas in the design of antenna arrays . In order to reduce the sidelobe levels of radiation patterns, the excitation amplitudes, phases, and positions of the array elements can be optimized.…”

“…Pattern synthesis of nonuniform antenna arrays is a complicated nonlinear optimization problem . Only the element positions of the antenna arrays are optimized to reduce the peak sidelobe level (PSLL) of the radiation patterns.…”

“…Thinned array is to remove some elements from a uniform antenna array . Sparse antenna array is that the array elements are placed on the array aperture randomly . Usually, sparse antenna array can obtain better optimization results than thinned array.…”