Adaptive Beamforming with Sidelobe Level Control for Multiband Sparse Linear Array

Author:

Li Hongtao1ORCID,Ran Longyao1,He Cheng2,Ding Zhoupeng1,Chen Shengyao1ORCID

Affiliation:

1. School of Electronic and Optical Engineering, Nanjing University of Science and Technology, Nanjing 210094, China

2. Beijing Institute of Remote Sensing Equipment, Beijing 100005, China

Abstract

Multiband antenna arrays have the capability of effectively working in multiple frequency bands and thus significantly simplify the antenna system. To further reduce the system overhead, this paper discusses the joint design of antenna selection and adaptive beamforming for multiband antenna arrays, where the sidelobe level is also controlled so as to alleviate the effect of unknown sporadic interference. Based on the maximum signal-to-interference-plus-noise ratio (SINR) criterion and sidelobe level constraints, the proposed multiband sparse array design is formulated into a nonconvex constrained nonlinear optimization problem with an l0,2-mixed norm regularization. This problem ensures that the same antenna positions are selected at all operating frequencies while the beamformer weights of each frequency are optimized independently. By exploiting the semi-definite relaxation and the reweighted l1,∞-norm approximation, the problem is converted into a series of convex subproblems and is then effectively solved by the proposed iterative reweighted method. Numerical results show that the proposed multiband sparse array significantly reduces the sidelobe levels in all operating frequencies while maintaining the maximum SINR, so it provides superior performance of interference suppression.

Funder

National Natural Science Foundation of China

Natural Science Foundation of Jiangsu Province

Publisher

MDPI AG

Subject

General Earth and Planetary Sciences

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Robust Adaptive Beamforming with Sparse Constraint via Semidefinite Relaxation;IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium;2024-07-07

2. Deep learning based sparse array design for emitter signal isolations;Big Data VI: Learning, Analytics, and Applications;2024-06-10

3. On the 2D Beampattern Optimization of Sparse Group-Constrained Robust Capon Beamforming with Conformal Arrays;Remote Sensing;2024-01-21

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