Active noise reduction method for automobile

Abstract

The invention relates to an active noise reduction method for an automobile and belongs to the voice signal processing technical field. The active noise reduction method guides the secondary sound source and adopts the self-adaptive algorithm for controlling the sound signal sent by the secondary sound source, and the outputted secondary sound wave after self-adaptive convergence at the noise reducing point has constant amplitude and reversal phase with the noise at the point for getting the noise reducing target. The algorithm and the method structure are improved based on the original active noise reduction method, the recursive least square method is used for replacing the least mean square algorithm as the core self-adaptive algorithm for the main path transfer function estimation and the secondary path transfer function estimation; the method has strong capability of eliminating the pulse noise and non-stationary noise and has good noise reducing error and noise reducing feed, the stability problem caused by the signal dependency is improved for the retaining signal in the automobile, the useful signal is kept while the noise is reduced and the signal to noise ratio is greatly improved.

Description

technical field [0001] The invention relates to an active noise reduction method used in automobiles, and belongs to the technical field of speech signal processing. Background technique [0002] Recently, noise control in automobiles mainly adopts traditional passive noise reduction technologies such as sound insulation, vibration isolation, noise elimination, and sound absorption. These technologies are effective in reducing medium and high-frequency noise in cars, but for Low frequency noise is less than ideal. Active noise reduction technology has attracted people's attention because of its ability to effectively reduce low-frequency noise, and has been gradually applied in reducing low-frequency noise. The principle of active noise reduction is to generate a new sound source signal with the opposite polarity and equal intensity to the source noise through an electro-acoustic system, and use this signal to superimpose the source noise signal to realize the cancellation ...

AI Technical Summary

Problems solved by technology

[0003] However, the existing method uses the minimum mean square error algorithm as the basic adaptive filter algorithm. Although the algorithm has the characteristics of low algorithm complexity and easy hardware implementation, it is affected by the secondary path effect and the algorithm convergence speed is slow and the stability is not high. The problem of inability to deal with sudden noise makes the active noise reduction method have defects in practical application

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