Blind separation method for mobile source signal aliasing

Abstract

The invention discloses a blind separation method for mobile source signal aliasing. In real life, an acquired aliasing signal has certain variability, an aliasing filter is time-varying, and comparedwith the process of a traditional time-invariant aliasing filter, the separation process of a source signal becomes more difficult. Aiming at the aliasing condition of the time variation, a robust blind separation algorithm is provided. The method includes the steps of locating a source signal through a time difference estimation algorithm, and providing strict mathematical theory derivation; reconstructing the aliasing filter, updating model parameters by utilizing an expectation maximization algorithm, and separating a source signal by utilizing a Wiener filtering method; and finally, verifying the effectiveness of the proposed algorithm through a simulation experiment, and comparing with a robust mobile source signal aliasing blind separation algorithm (Full-rank algorithm) to prove that the algorithm provided by the invention has better robustness for mobile source signal aliasing blind separation.

Description

technical field [0001] The invention relates to the technical field of blind signal separation, in particular to a blind separation method for mobile source signal aliasing. Background technique [0002] In the classic cocktail party problem, the acquisition of aliased sounds is complicated by the movement of people at the party. How to recover the original signal only from the received aliased signal, while the aliased channel is unknown, this source signal separation process is called "blind separation". In recent years, blind separation technology has been fully applied in speech signal processing. However, most of the research work is limited to the immobile source signal, that is, the time-invariant aliasing signal, and there are relatively few studies on the time-varying aliasing signal. [0003] In the prior art, the document N.Q.K.Duong, E.Vincent, Under-determined reverberant audio source separation using a full-rank spatial covariance model, IEEETrans.Audio Speec...

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Problems solved by technology

However, most of the research work is limited to the source signal is not moving, that is, the time-invariant aliasing signal, relatively little research on the time-varying aliasing signal

[0003] In the prior art, the document N.Q.K.Duong, E.Vincent, Under-determined reverberant audio source separation using a full-rank spatial covariance model, IEEETrans.Audio Speech Lang.Process.18(7)(2010)1830-1840. proposes a The Full-rank algorithm is robust to the aliasing blind separation of moving source signals, but the effect is average. The main reason is that when the source signal moves, the aliasing filter also changes, resulting in the blind separation of aliasing signals. more difficult process

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