Low Discrepancy Sparse Phased Array Antennas

Abstract

Sparse arrays have grating lobes in the far field pattern due to the large spacing of elements residing in a rectangular or triangular grid. Random element spacing removes the grating lobes but produces large variations in element density across the aperture. In fact, some areas are so dense that the elements overlap. This paper introduces a low discrepancy sequence (LDS) for generating the element locations in sparse planar arrays without grating lobes. This nonrandom alternative finds an element layout that reduces the grating lobes while keeping the elements far enough apart for practical construction. Our studies consider uniform sparse LDS arrays with 86% less elements than a fully populated array, and numerical results are presented that show these sampling techniques are capable of completely removing the grating lobes of sparse arrays. We present the mathematical formulation for implementing an LDS generated element lattice for sparse planar arrays, and present numerical results on their performance. Multiple array configurations are studied, and we show that these LDS techniques are not impacted by the type/shape of the planar array. Moreover, in comparison between the LDS techniques, we show that the Poisson disk sampling technique outperforms all other approaches and is the recommended LDS technique for sparse arrays.

Synthesis of Linear Antenna Array for Wireless Power Transmission

“…With the larger search space and better robustness than above algorithms, the IWO algorithm has been successfully applied in many fields. Additionally, the study proves that sparse arrays are more flexible and less costly than thinned arrays [23][24][25]. Therefore, the optimization problem of sparse array will also be studied in this paper.…”

MIMO Coded Generalized Reduced Dimension Fourier Algorithm for 3-D Microwave Imaging

“…This usually requires a very large number of antenna elements to satisfy the Nyquist criterion [4]. The use of sparse aperiodic phased arrays [5,6] and multistatic multiple-input multiple-output (MIMO) arrays [7,8] are two solutions provided for this issue. It has been demonstrated that the high spatial information diversity obtained by antenna arrays with a MIMO configuration can lead to an increase in the quality of reconstructed images in an imaging system [9,10].…”

An efficient synthesis method for large unequally spaced sparse linear arrays based on surrogate models of subarrays

“…The synthesis of unequally spaced sparse arrays can further reduce the weight, cost, and power consumption of the radiating device by using as less a number of antenna elements as possible without reducing the performance of the antenna array, which is of great significance for large arrays. 1 In the previous studies, spatial tapering designs, 2-3 mathematical programming methods, 4 and stochastic optimization methods [5][6][7] have been developed to synthesize unequally spaced arrays with the number of array elements fixed. In the recent years, matrix pencil methods (MPM) 8 and compressive sensing (CS)-based synthesis approaches 9,10 have been applied to reconstruct focused and shaped patterns with a reduced number of antenna array elements.…”

“…Unequally spaced arrays are widely employed in wireless communication, radar or satellite system, and other fields due to their advantages of suppressing the sidelobe and grating lobe levels. The synthesis of unequally spaced sparse arrays can further reduce the weight, cost, and power consumption of the radiating device by using as less a number of antenna elements as possible without reducing the performance of the antenna array, which is of great significance for large arrays 1 . In the previous studies, spatial tapering designs, 2–3 mathematical programming methods, 4 and stochastic optimization methods 5–7 have been developed to synthesize unequally spaced arrays with the number of array elements fixed.…”