Virtual Reconstruction-Based Robust Adaptive Beamforming for Distributed Digital Subarray Antennas

Jian Lu,Jian Yang,Fengchao Zhu,Zhiyong Yu,Guangbin Liu,Bo Hou

doi:10.1155/2021/6649439

Abstract

For the distributed digital subarray antennas (DDSA), the conventional beamforming may give rise to grating lobes, high sidelobes, and other problems. In this paper, the gaps between the subarrays are filled with virtual array elements, and then the DDSA can form a virtual contiguous array. More concretely, based on the direction-of-arrival (DOA) estimation of the signal sources, the interference components of the virtual elements and the interference-plus-noise covariance matrix (INCM) of the virtual contiguous array can be reconstructed. At low signal-to-noise ratio (SNR), the DOA estimation of the desired signal is implemented by subarray adaptive beamforming. Finally, with the steering vector of the desired signal and reconstructed INCM, the weight vector of the proposed beamformer can be obtained, which must be applied to the rearranged data matrix received by the actual and virtual elements. Simulation results are provided to demonstrate the effectiveness of the proposed algorithm.

Highlights

Compared with a single antenna, the distributed digital subarray antennas (DDSA) can provide better spatial resolution, wider beam coverage, and macro diversity gain [1].e DDSA can work cooperatively as a single array, which significantly increases the output signal-to-interferenceplus-noise ratio (SINR) and achieves ultralow sidelobe performance [2, 3]
The optimal output SINR of the subarray is shown in the simulations to clearly demonstrate the advantages of the proposed beamformer
According to the minimum variance distortionless response (MVDR) criterion, the optimal output SINR is calculated by (5). e parameter ε 0.3 is used in the RAB-WCPO, and the angular sector of the desired signal is set to be Θ [θ0 − 5°, θ0 + 5°] while suppressing the sidelobe interference. e sampling grid is uniform in Θ and Θ with 0.1° increment between adjacent grid points

Summary

Introduction

E DDSA can work cooperatively as a single array, which significantly increases the output signal-to-interferenceplus-noise ratio (SINR) and achieves ultralow sidelobe performance [2, 3]. Owing to these excellent advantages, the DDSA has received a lot of interest as a new leading-edge technology for radar [4,5,6], sonar [7], wireless communication [8,9,10], and other areas. In [14], by combining the multiple signal classification (MUSIC) algorithm with sparse subarrays, the closed-form eigenstructure-based DOA estimation was proposed to eliminate ambiguity. In [17], the distributed linearly constrained minimum variance (LCMV) beamformer was proposed to suppress interference and optimize the signal-to-noise ratio

Results

Discussion

Conclusion