本文關(guān)鍵詞： 聲矢量傳感器陣列 高階累積量 高斯色噪聲 DOA估計(jì) MUSIC ESPRIT　出處：《吉林大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

【摘要】：聲矢量傳感器是近年興起的一種新型聲音信號(hào)探測(cè)設(shè)備。它能夠同步共點(diǎn)的測(cè)量某地的聲壓信息和三維振速信息,相較于傳統(tǒng)的聲壓傳感器,不僅能夠捕獲更多的有用信息,而且探測(cè)更加靈敏,探測(cè)范圍更加廣泛。在通信、雷達(dá)、定位、生物醫(yī)學(xué)及軍事國(guó)防方面,正逐步取代傳統(tǒng)的聲壓傳感器。因此,無(wú)論從國(guó)民經(jīng)濟(jì),還是國(guó)家安全領(lǐng)域來看,對(duì)聲矢量傳感器的研究都具有十分重要的意義。目前對(duì)聲矢量傳感器技術(shù)的研究主要兩大部分:其一是聲矢量傳感器機(jī)械構(gòu)成的研究;另一個(gè)是對(duì)聲矢量傳感器的應(yīng)用方面的研究,即對(duì)聲矢量傳感器所接收的信號(hào)進(jìn)行處理。如果說前者是骨架的構(gòu)建,后者便是賦予這副骨架靈魂。本文將側(cè)重于對(duì)后者的研究。波達(dá)方向估計(jì)(Direction Of Arrival,DOA),作為陣列信號(hào)處理的重要課題之一,也是聲矢量傳感器陣列實(shí)際應(yīng)用中面臨的重要難題。能夠準(zhǔn)確的估計(jì)出信號(hào)的到達(dá)角,是后續(xù)聲矢量傳感器的應(yīng)用基礎(chǔ)。自聲矢量傳感器問世以來,許多基于二階統(tǒng)計(jì)量的算法,如聲矢量MUSIC算法(Acoustic Vector Sensor MUSIC,A-MUSIC),聲矢量ESPRIT(Acoustic Vector Sensor ESPRIT,A-ESPRIT)等,這些算法雖然對(duì)高斯白噪聲有一定的抑制作用,但是對(duì)高斯色噪聲抑制卻無(wú)能為力�？紤]實(shí)際工況中多是高斯色噪聲,該問題的存在嚴(yán)重制約了聲矢量技術(shù)向?qū)嶋H應(yīng)用的轉(zhuǎn)化。高階累積量,由于其對(duì)高斯噪聲的不敏感性,一經(jīng)提出便受到了許多專家學(xué)者的青睞,各種基于常規(guī)陣元的高階累積量算法層出不窮,并取得了很好的效果,很多已經(jīng)付諸于實(shí)際應(yīng)用。但是對(duì)于聲矢量傳感器而言,高階累積量的處理卻鮮有人為。究其原因,莫過于聲矢量傳感器的特性導(dǎo)致用高階累積量的處理計(jì)算復(fù)雜、計(jì)算量大。基于上述原因,本文對(duì)基于高階累積量的聲矢量陣列DOA估計(jì)問題進(jìn)行了研究。首先,從抑制高斯色噪聲的角度出發(fā),推導(dǎo)了聲矢量陣列的高階累積量DOA估計(jì)算法。其次,考慮到實(shí)際應(yīng)用中計(jì)算量的問題,提出了基于高階累積量對(duì)角切片的聲矢量MUSIC算法。再次,為了取得更加精確的DOA估計(jì)效果,提出了基于累積量3,4維切片的聲矢量MUSIC算法。接著,為了更進(jìn)一步減少計(jì)算量,將ESPRIT算法引入到高階累積量切片中,提出了聲矢量陣列高階累積量對(duì)角切片的ESPRIT算法。然后,為了克服高階累積量對(duì)角切片ESPRIT計(jì)算中導(dǎo)致DOA估計(jì)精度降低的問題,本文提出了改進(jìn)的聲矢量陣列高階累積量對(duì)角切片ESPRIT算法。最后,通過MATLAB對(duì)上述的算法進(jìn)行了仿真驗(yàn)證,結(jié)果表明所提算法具有較好的DOA估計(jì)性能。本文主要針對(duì)聲矢量傳感器陣列的DOA估計(jì)進(jìn)行了研究,以期望有助于聲矢量陣列信號(hào)的理論研究和實(shí)際應(yīng)用。
[Abstract]:Acoustic vector sensor is a new kind of sound signal detection equipment, which can synchronously measure the sound pressure information and the three-dimensional vibration velocity information of a place at the same time, compared with the traditional sound pressure sensor. Not only can more useful information be captured, but detection is more sensitive and more extensive. In communications, radar, positioning, biomedical and military defense. Is gradually replacing the traditional sound pressure sensor. Therefore, whether from the national economy or the field of national security. The research of acoustic vector sensor is of great significance. At present, there are two main parts in the research of acoustic vector sensor technology: one is the research on the mechanical structure of acoustic vector sensor; The other is the research on the application of acoustic vector sensor, that is, processing the signal received by the acoustic vector sensor, if the former is the construction of skeleton. The latter is to give the skeleton soul. This paper will focus on the study of the latter. As an important subject of array signal processing, it is also an important problem in the practical application of acoustic vector sensor array. It can accurately estimate the arrival angle of the signal. Since the advent of acoustic vector sensors, many algorithms based on second-order statistics have been developed. For example, acoustic Vector Sensor MUSICI A-MUSICA (acoustic vector MUSIC algorithm). Acoustic vector ESPRIT(Acoustic Vector Sensor Esprit (A-Esprit), et al. Although these algorithms can suppress Gao Si's white noise to some extent, there is no way to suppress Gao Si's color noise. The existence of this problem seriously restricts the transformation of acoustic vector technology to practical application. Because of its insensitivity to Gao Si noise, high order cumulant is favored by many experts and scholars. A variety of high-order cumulant algorithms based on conventional array elements have emerged and achieved good results, many of which have been applied to practical applications, but for acoustic vector sensors. The processing of high-order cumulants is rare. The reason is that the characteristics of acoustic vector sensors lead to the complexity and complexity of the processing of high-order cumulants. In this paper, the DOA estimation problem of acoustic vector array based on higher-order cumulant is studied. Firstly, from the point of view of suppressing Gao Si color noise. The high-order cumulant DOA estimation algorithm for acoustic vector array is derived. Secondly, considering the computational complexity in practical application, a novel acoustic vector MUSIC algorithm based on diagonal slice of high-order cumulant is proposed. In order to obtain more accurate DOA estimation effect, an acoustical vector MUSIC algorithm based on cumulant 3-dimensional slice is proposed. Then, in order to further reduce the computational complexity. The ESPRIT algorithm is introduced into higher-order cumulant slice, and the ESPRIT algorithm for diagonal slice of high-order cumulant in acoustic vector array is proposed. In order to overcome the problem of reducing the accuracy of DOA estimation in diagonal slice ESPRIT calculation of high-order cumulants. In this paper, an improved ESPRIT algorithm of high order cumulant diagonal slicing of acoustic vector array is proposed. Finally, the above algorithm is simulated by MATLAB. The results show that the proposed algorithm has good DOA estimation performance. This paper mainly focuses on the DOA estimation of acoustic vector sensor array. It is expected to be helpful to the theoretical research and practical application of acoustic vector array signals.
【學(xué)位授予單位】：吉林大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TP212

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