回声抵消的相关函数RLS算法

RLS Algorithm Based on Correlation Function for Echo Canceling

在自适应回声抵消领域中,传统自适应滤波算法在双方对讲情况下需停止调节滤波器系数。为克服上述缺点,在相关函数分析的基础上,为提高通信质量,提出结合时变遗忘因子和基于平方根卡尔曼滤波的递推最小二乘(Recursive LeastSquare,RLS)算法。对相关函数分析克服了双方对讲情况下需停止滤波器系数更新。同时,由于遗忘因子的时变特性,使得算法收敛速度和跟踪性能均得到了明显的改善。而平方根卡尔曼滤波方法的引入也降低了算法对计算设备精度的要求。借助标准数据进行仿真,结果表明,算法在双方对讲情况下具有良好的回声抵消效果。

In the field of adaptive echo cancellation,the tap adaptations can not be continued under double - talk by using the traditional algorithm.Combined with variable forgetting factor and the square root Kalman,a new RLS algorithm based on correlation function is presented in this paper.By using the algorithm,the tap adaptations can be continued under double - talk.Besides,the performance of the convergence and the track have been improved by varying forgetting factor.The method of square root Kalman also reduces the requirement of equipment for accuracy.The result of computer simulation shows that the better characteristics for echo cancellation can be achieved.