一种基于四阶统计量的递推LMS算法

A Recursive Least Mean Sqare Algorithm Based on Fourth-Order Statistics

  • 摘要: 提出一种基于四阶统计量一维切片的LMS算法,并且给出其递推形式.该算法能够有效地抑制相关高斯噪声的影响,性能优于传统的基于相关的LMS算法;递推形式降低了其计算复杂度,能够满足实时处理的要求.采用相关高斯色噪声进行数值仿真,结果表明该方法的有效性.该算法可在雷达、声纳及通信系统中用于多径系数估计.

     

    Abstract: An LMS algorithm based on one dimensional slice of fourth-order statistics is proposed and its recursive form is given. This algorithm can suppress the correlated Gaussian noises effectively, and its performance is better than the conventional autocorrelation-based LMS algorithm. The recursive form reduces the computational complexity, and it can meet the need of real-time processing. Simulation results are presented to demonstrate the effectiveness of this approach. The presented algorithm can be used to estimate multi-path coefficients in radar, sonar and communication systems.

     

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