A Combined Step Echo Cancellation Method with High Tracking Performance

Abstract

A combined step-size echo cancellation method with high tracking performance, the steps include: A, collecting far-end input signal u(n) and near-end desired signal d(n); B, inputting the discrete value u(n) of the input signal Adaptive filter to obtain the output signal y(n); C, subtract y(n) from d(n) for echo cancellation, and transmit the error signal e(n) to the far end; D, calculate the value of the adaptive filter Error vector; E, update the tap weight w(n) of the adaptive filter; as the relative strength value of the error signal at the current moment is greater than the threshold value of setting, and the absolute strength value r(n of the error signal at the previous moment 1) = log 10 (e 2 (n-1)) is less than the set threshold, then the weight error matrix trace J(n) is forcibly reset to a large initial value; F, update the weight error matrix trace J(n+1); G, Let n=n+1, repeat steps A, B, C, D, E, F until the call ends. This method has good tracking performance when the acoustic echo channel changes.

Description

technical field [0001] The invention belongs to the technical field of echo cancellation in communication. Background technique [0002] As an important branch of information technology, adaptive signal processing has been widely used in the field of communication. In the field of communication, echo cancellation is a hot spot with considerable attention and challenges. Echoes will be formed after multiple reflections of sound in a closed space, and echoes will also be formed in signal transmission due to impedance mismatch in the transmission medium. The communication echo can be eliminated by the system identification model: the identified system is an acoustic echo channel, and the output of the system identification is an estimate of the echo signal. The echo can be eliminated by subtracting the voice signal containing the echo signal and the estimate of the echo signal. This is the principle of the adaptive echo canceller. [0003] In echo cancellation applications, ...

AI Technical Summary

Problems solved by technology

However, the mixing parameters of the CSSAPA-VMP algorithm mainly depend on the variance of the input vector or echo signal composed of the input signal at the current moment and the previous few moments, while the input signal at the current moment in the input vector accounts for a relatively low proportion, and the echo at the current moment in the variance The signal ratio is also low; therefore, when the channel changes suddenly, it does not have the ability to track, and the performance will become very poor, resulting in unsatisfactory echo cancellation

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