修正共轭梯度恒模阵列算法研究

Study of MCG-CMA Algorithm Based on Conjugate Gradient Method

提出一种基于修正共轭梯度算法的恒模(MCG-CMA)盲干扰抑制算法,该算法将修正共轭梯度方法引入到恒模算法中,克服了传统恒模算法收敛缓慢、LS-CMA运算量大的缺点,保留了较好的计算复杂度和数值稳定性,理论推导了算法失调量的显式表达式。仿真结果表明该算法不需要波达方向估计,与传统的LS-CMA算法、SCG-CMA算法相比,具有较好的收敛性能和输出信干噪比(SINR)。

This paper presents and analyzes a constant modulus algorithm （CMA） adaptive beamforming algorithm which is based on conjugate gradient method. This algorithm focuses on a new technique for data block modificatory method with conjugate gradient, and overcomes the shortcoming of traditional CMA algorithms, such as slow convergence speed or vast complexity. An analysis is given to fred the misadjustments performance in MCG-CMA algorithm with different sampling length. Computer simulations show that the algorithm has better convergence performance and better signal to interference plus noise ratio （SINR） capability than LS-CMA and SCG-CMA algorithm.