基于新最速下降算法的自适应波束形成  

Adaptive beamforming based on new steepest descent algorithm

作　　者：王帅 向建军[1] 彭芳[1] 唐书娟[1] 李志军 WANG Shuai;XIANG Jianjun;PENG Fang;TANG Shujuan;LI Zhijun(Aeronautics Engineering College, Air Force Engineering University, Xi’an 710038, China)

机构地区：[1]空军工程大学航空工程学院,陕西西安710038

出　　处：《系统工程与电子技术》2022年第7期2104-2111,共8页Systems Engineering and Electronics

基　　金：空军工程大学校长基金(XZJ2020099);空军工程大学航空工程学院院内项目资助课题。

摘　　要：针对阵列信号处理中自适应波束形成技术的抗干扰问题,提出一种基于新的最速下降法的波束形成算法。新的最速下降法将多元二次凸优化问题转换为一元二次问题,通过循环迭代的方式使求出的极值点向高维凸优化问题的极值点逼近,最终使结果收敛到最优解。将这种算法应用于自适应波束形成,提高自适应波束形成的收敛速度、抗干扰能力和低快拍下工作的能力。经过仿真验证,与基于最小均方算法以及改进最小均方算法的波束形成方法进行比较,所提出的波束形成算法具有抗强干扰、收敛速度快、能在低快拍条件下工作的优点。Aiming at the anti-jamming problem of adaptive beamforming technology in array signal processing,this paper proposes a new beamforming algorithm based on the steepest descent method.The new steepest descent method transforms the multivariate quadratic convex optimization problem into the univariate quadratic optimization problem,and makes the extremum point approach to the extremum point of the high-dimensional convex optimization problem by means of cyclic iteration,and finally makes the result converge to the optimal solution.This algorithm is applied to adaptive beamforming to improve the convergence speed,anti-jamming ability and the ability to work in low snapshot.The simulation results show that compared with the beamforming methods based on the least mean square(LMS)algorithm and the improved LMS algorithm,the proposed beamforming algorithm has the advantages of strong interference resistance,fast convergence speed and working under low snapshot conditions.

关 键 词：最速下降 自适应 波束形成 抗干扰 

分 类 号：TN959.73[电子电信—信号与信息处理]