本文選題：聲源定位　切入點：數(shù)學(xué)形態(tài)學(xué)　出處：《電子科技大學(xué)》2014年碩士論文

【摘要】：狹小空間中的低信噪比混響環(huán)境會影響聲源定位系統(tǒng)的定位精度,嚴重時甚至?xí)率瓜到y(tǒng)無法正常工作。即使利用濾波器對噪聲進行濾波處理,聲音信號也會因被障礙物反射而存在著一定的混響,常規(guī)濾波器無法進行濾除。由此可見,提出一種能濾除混響和噪聲且定位精度高的方法十分必要。針對上面實際中遇到的問題,本文以四元T型麥克風(fēng)陣列為例,針對其接收到含有低信噪比噪聲和混響的聲音信號為研究對象,在深入分析形態(tài)濾波器濾除噪聲和信號的經(jīng)驗?zāi)B(tài)分解和重構(gòu)的基礎(chǔ)上,提出了一種適用于低信噪比混響環(huán)境的基于數(shù)學(xué)形態(tài)學(xué)的聲源定位方法,主要內(nèi)容如下:首先,為解決低信噪比噪聲中單獨使用小波濾波器時的頻率分辨率較低以及對存在跳變信號時處理效果不佳的問題,提出了一種結(jié)合形態(tài)學(xué)濾波器和小波濾波器的融合型濾波器——形態(tài)-小波濾波器對缺陷信號進行處理。本文以混有white噪聲,destroyerengine噪聲和f16噪聲的信號為例,針對其信號的特性,運用平結(jié)構(gòu)元素的級聯(lián)結(jié)構(gòu)的形態(tài)學(xué)濾波器提高低信噪比信號的信噪比,再由小波濾波器進行濾波處理,實現(xiàn)對低信噪比信號的噪聲濾除。其次,在前面濾除噪聲過程的基礎(chǔ)之上,將小波的預(yù)處理方法與經(jīng)驗?zāi)B(tài)分解方法結(jié)合起來,分離混在聲音信號中的混響信號,得出原信號的重構(gòu)信號。本文以一段加上混響后的語音信號為例,采用小波預(yù)處理方法將信號分為一系列窄帶信號,然后再使用經(jīng)驗?zāi)B(tài)分解,得到一系列的能表征信號特征的信號分量,篩選后重構(gòu)原信號,最終就可以得到濾除混響的聲音信號。最后,根據(jù)前面的濾除噪聲和混響的方法并結(jié)合基于時延估計的聲源定位算法,設(shè)計了基于數(shù)學(xué)形態(tài)學(xué)和經(jīng)驗?zāi)B(tài)分解的聲測定位方法,并在mini2440上使用Matlab實現(xiàn)了聲測定位系統(tǒng)。經(jīng)過仿真實驗可知,該方法可以有效地濾除噪聲,抑制混響,為進一步提高定位精度,增強抗外界環(huán)境因素的干擾性能奠定了基礎(chǔ)。
[Abstract]:The reverberation environment of low signal-to-noise ratio in a narrow space will affect the positioning accuracy of the sound source location system and even cause the system to fail to work properly even if the noise is filtered by the filter. The sound signal will also be reflected by obstacles and there will be reverberation, which can not be filtered by conventional filters. It is necessary to propose a method to filter reverberation and noise with high positioning accuracy. In view of the problems encountered in practice above, this paper takes the quaternion T microphone array as an example. For the acoustic signal with low SNR noise and reverberation received, the empirical mode decomposition and reconstruction of filtering noise and signal by morphological filter are deeply analyzed. A mathematical morphology based sound source location method for low SNR reverberation environment is proposed. The main contents are as follows: firstly, In order to solve the problem of low frequency resolution when wavelet filter is used alone in low signal-to-noise ratio (SNR) noise, and the problem that the processing effect is not good when there is a jump signal, In this paper, a hybrid filter, Morphology-wavelet filter, which combines morphological filter and wavelet filter, is proposed to process the defective signal. In this paper, the signal mixed with white noise, destroyerengine noise and f16 noise is taken as an example, and the characteristics of the signal are analyzed. A cascade morphological filter with flat structure elements is used to improve the signal-to-noise ratio (SNR) of low signal-to-noise ratio (SNR) signal, and then the wavelet filter is used to filter the signal to realize the noise filtering of the low signal-to-noise ratio signal. Secondly, On the basis of filtering noise process in front, the pre-processing method of wavelet and empirical mode decomposition method are combined to separate reverberation signal mixed in sound signal. The reconstructed signal of the original signal is obtained. Taking a speech signal with reverberation as an example, the signal is divided into a series of narrow band signals by wavelet pretreatment method, and then the empirical mode decomposition is used. We get a series of signal components that can represent the characteristics of the signal. After screening the original signal, we can reconstruct the original signal, and finally we can filter the reverberation sound signal. Finally, According to the previous methods of noise filtering and reverberation, combined with the acoustic source location algorithm based on time delay estimation, the acoustic location method based on mathematical morphology and empirical mode decomposition is designed. The sound measurement and positioning system is realized on mini2440 with Matlab. The simulation results show that the method can effectively filter noise and suppress reverberation, which lays a foundation for further improvement of positioning accuracy and enhancement of anti-interference performance of external environment factors.
【學(xué)位授予單位】：電子科技大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：TN912.2

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本文編號：1697730