Adaptive Sparse Array Beamforming Using Correntropy Induced Metric Constrained Normalized LMS Algorithm

• Published in: Applied Computational Electromagnetics Society journal Vol. 35; no. 4; p. 430
• Main Authors: Dai, Zehua, Guo, Longxiang, Yin, Jingwei, Li, Yingsong, Guo, Kun
• Format: Journal Article
• Language: English
• Published: Pisa River Publishers 01.04.2020
• Subjects: Algorithms; Antenna arrays; Antennas; Beamforming; Computer simulation; Constraints; Convergence; Cost function; Lagrange multiplier
• ISSN: 1054-4887; 1943-5711

In order to further exploit the sparseness of antenna array and speed up the convergence of constrained normalized LMS (CNLMS) algorithm, maintaining good beam pattern performance and better output signal-to-interferences-plus-noise ratio (SINR), a new method with approximation l0-norm constraint is proposed to improve CNLMS algorithm, and its derivation process is given in detail. In this newly proposed algorithm, the correntropy induced metric (CIM) is used to approximate the l0-norm, which is considered construct a new cost function to fully exploit the sparsity of the antenna array and reduced the number of active array elements. Using the CIM penalty, the proposed CIM-based CNLMS (CIM-CNLMS) algorithm is derived in detail, where the Lagrange multiplier method is utilized to solve the cost function of the proposed CIM-CNLMS algorithm, and the steepest descent principle is considered to obtain the update equation. The computer simulation results demonstrate that compared with other CLMS algorithms, the new algorithm obtains better performance, which greatly reduces the proportion of active array elements in the thinned antenna array. Simultaneously, the new algorithm has excellent beam pattern performance and better SINR performance with faster convergence speed and more stable mean square error.