应用于回声消除的精确背景噪声估计

Precise Background Noise Power Estimate for Echo Cancellation

The reconstruction of background noise from an error signal of an adaptive filter is a key is-sue for developing Variable Step-Size Normalized Least Mean Square (VSS-NLMS) algorithm in the context of Echo Cancellation (EC). The core param-eter in this algorithm is the Background Noise Pow-er (BNP ); in the estimation of BNP, the power difference between the desired signal and the filter output, statistically equaling to the error signal pow-er, has been widely used in a rough manner. In this study, a precise BNP estimate is implemented by multiplying the rough estimate with a corrective factor, taking into consideration the fact that the er-ror signal consists of background noise and mis-alignment noise. This corrective factor is obtained by subtracting half of the latest VSS value from 1 after analyzing the ratio of BNP to the misalignment noise. Based on the precise BNP estimate, the PVSS-NLMS algorithm suitable for the EC system is eventually proposed. In practice, the proposed al-gorithm exhibits a significant advantage of easier controllability application, as prior knowledge of the EC environment can be neglected. The simula-tion results support the preciseness of the BNP esti-mation and the effectiveness of the proposed algo-rithm.