基于自适应CKF的恒模盲波束形成算法

Constant modulus blind beamforming algorithm based on adaptive CKF

针对均匀线阵,利用信号的恒模特性,与容积卡尔曼滤波相结合,提出一种新的盲自适应波束形成算法。通过对恒模算法的优化代价函数进行变换,使其满足系统状态空间模型。利用容积卡尔曼滤波算法进行自适应滤波,以实现抑制干扰和消除噪声。所提算法对状态空间模型中的系统噪声和过程噪声进行了自适应处理,免除滤波噪声参数的设置,增强了算法的通用性,并引入了收敛因子,加速系统的收敛速度。仿真结果表明了该算法的正确性和有效性。

A novel blind adaptive beamforming algorithm is proposed based on uniform linear array using constant modulus feature and cubature Kalman filter （CKF）. This algorithm transforms the cost function of the constant modulus algorithm （CMA） to a state space model, and cancels noise and suppresses interference using the CKF. System noise and measurement noise are processed adaptively without setting noise parameters, thus being applied to applications conveniently. A convergence factor is introduced to speed up the convergence of systems. Simulation results demonstrate its correctness and effectiveness.