Blind adaptive constrained constant modulus algorithms based on unscented Kalman filter for beamforming  

作　　者：QIAN Hua-ming LIU Ke JIAO Zhi-bo MA Jun-da 钱华明;刘可;焦志博;马俊达

机构地区：[1]College of Automation,Harbin Engineering University,Harbin 150001,China [2]Hainengda Communication Co.,Ltd.,Shenzhen 518000,China

出　　处：《Journal of Central South University》2017年第10期2342-2352,共11页中南大学学报（英文版）

基　　金：Project(61573113)supported by the National Natural Science Foundation of China;Project(2014RFXXJ074)supported by the Science and Technology Innovation Talents Research Fund of Harbin,China

摘　　要：This work proposes constrained constant modulus unscented Kalman filter(CCM-UKF) algorithm and its low-complexity version called reduced-rank constrained constant modulus unscented Kalman filter(RR-CCM-UKF) algorithm for blind adaptive beamforming. In the generalized sidelobe canceller(GSC) structure, the proposed algorithms are devised according to the CCM criterion. Firstly, the cost function of the constrained optimization problem is transformed to suit the Kalman filter-style state space model. Then, the optimum weight vector of the beamformer can be estimated by using the recursive formulas of UKF. In addition, the a priori parameters of UKF(system and measurement noises) are processed adaptively in the implementation. Simulation results demonstrate that the proposed algorithms outperform the existing methods in terms of convergence speeds, output signal-tointerference-plus-noise ratios(SINRs), mean-square deviations(MSDs) and robustness against steering mismatch.This work proposes constrained constant modulus unscented Kalman filter(CCM-UKF) algorithm and its low-complexity version called reduced-rank constrained constant modulus unscented Kalman filter(RR-CCM-UKF) algorithm for blind adaptive beamforming. In the generalized sidelobe canceller(GSC) structure, the proposed algorithms are devised according to the CCM criterion. Firstly, the cost function of the constrained optimization problem is transformed to suit the Kalman filter-style state space model. Then, the optimum weight vector of the beamformer can be estimated by using the recursive formulas of UKF. In addition, the a priori parameters of UKF(system and measurement noises) are processed adaptively in the implementation. Simulation results demonstrate that the proposed algorithms outperform the existing methods in terms of convergence speeds, output signal-tointerference-plus-noise ratios(SINRs), mean-square deviations(MSDs) and robustness against steering mismatch.

关 键 词：CONSTRAINED constant MODULUS criterion BLIND BEAMFORMING unscented KALMAN filter generalized SIDELOBE canceller 

分 类 号：TN713[电子电信—电路与系统] TN911.7