Combined step size echo cancellation method with high tracking performance

Abstract

A combined step size echo cancellation method with a high tracking performance comprises the steps of: A, collecting far-end input signals u(n) and a close-range desired signals d(n); B, inputting aninput signal discrete value u(n) into an adaptive filter to obtain output signals y(n); C, subtracting y(n) from d(n) to perform echo cancellation, and transmitting error signals e(n) to a far end; D,calculating error vectors of the adaptive filter; E, updating a tapping weight value w(n) of the adaptive filter, if the relative intensity value of the error signals at the current moment as shown in the description is larger than a set threshold value, and an absolute intensity value r(n-1)=log10(e2(n-1)) is smaller than the set threshold value, forcibly resetting a weight value error matrix track J(n) to be a large initial value; F, updating a weight value error matrix track J(n+1); and G, allowing n to be equal to n+1, and repeating the steps A, B, C, D, E and F until the conversation isfinished. The method has a good tracking performance when an acoustics echo channel is changed.

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 that attracts much attention and challenges. The sound will form an echo after multiple reflections in a closed space, and the echo will also be formed in the signal transmission due to the 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 the estimate of the echo signal. The echo can be eliminated by subtracting the speech signal containing the echo signal from the estimate of the echo signal. This is the principle of the adaptive echo canceller. [0003] In echo cancellation app...

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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