Robust Adaptive Beamforming Algorithm for Sparse Subarray Antenna Array Based on Hierarchical Weighting

Micromachines

Yuwei Tu¹  Jian Yang¹  Xinxin Liu¹  Weixing Li² 

[1] School of Engineering, Rocket Force University of Engineering, Xi’an 710025, China;Science and Technology on Automatic Target Recognition Laboratory, National University of Defense Technology, Changsha 410073, China;

关键词: array antenna;    sparse subarray;    digital beamforming;    Covariance Matrix reconstruction;   

DOI  :  10.3390/mi13060859

来源: DOAJ

【 摘 要 】

Sparse antenna arrays based on subarrays have more and more broad application prospects for the limitation of array space, real-time algorithm and hardware costs. Aiming at the beamforming technology of sparse antenna arrays based on subarrays, this paper proposes a robust adaptive beamforming algorithm based on hierarchical weighting. The algorithm performs conventional beamforming to calculate the weights of each element in the subarray, then the synthetic signals output by each subarray are used as sparse array metadata. The Interference-plus-Noise Covariance Matrix (INCM) is reconstructed by integration in two-dimensional space, and a convex optimization model of a multi-constraint array containing the signal pointing error was established to estimate the real guide vector. Finally, using the reconstructed INCM and the estimation of the guide vector, we obtain a weighted vector between the subarrays and output signal for the whole array. The simulation results show that the proposed algorithm has better Signal-to-Interference-and-Noise Ratio (SINR) and robustness compared with other algorithms for sparse subarray antenna array beamforming.

【 授权许可】

Unknown