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  本文選題：聲矢量傳感器 + Unitary-MUSIC算法��； 參考：《哈爾濱工業(yè)大學》2014年碩士論文

【摘要】：聲矢量傳感器是由聲壓傳感器與質(zhì)點振速傳感器兩部分構(gòu)成的,在空域環(huán)境中具有同步采集聲場中的聲壓信息(標量)與振速信息(矢量)的特性。其增加的數(shù)據(jù)維度等同于更多的數(shù)據(jù)快拍,較之聲壓傳感器會有更高的檢測靈敏度。但是現(xiàn)有的大量聲矢量陣信號處理技術都是將矢量傳感器的振速信息作為額外的獨立陣元來處理,而沒有充分利用遠場環(huán)境下聲壓與振速的相關性特點。事實上,在各項同性的噪聲場中,聲壓及振速是非相關的;利用這一特性,即可在信號波達方向角估計過程有效降低高斯白噪聲所產(chǎn)生的影響及干擾。本文在回顧聲矢量傳感器的基本原理、聲壓振速聯(lián)合信息處理的物理基礎以及子空間類算法的聲矢量陣信號處理技術的基礎上,采用聲壓振速聯(lián)合信息對矢量傳感器陣列信號處理進行算法上的改進,為解決在低信噪比環(huán)境下高效地定位目標方位提供了一種可行的解決思路。本文引入了基于聲壓振速聯(lián)系信息的P-V互協(xié)方差矩陣來處理接收數(shù)據(jù)信號。這種新型的協(xié)方差矩陣將振速信息合成到某一觀測方向上,避免了接收數(shù)據(jù)矩陣的維度增加,因此降低了聲矢量陣信號處理的計算復雜度。在接收信號矩陣的后續(xù)處理中,本文結(jié)合現(xiàn)有的Unitary-MUSIC算法和Root-MUSIC算法提出了一種基于聲矢量傳感器陣P-V互協(xié)方差矩陣的Unitary-Root MUSIC改進算法。該算法不僅在原有的算法基礎上提升了信號的檢測性能,更進一步降低了計算復雜度。文中也從不同信噪比條件下的均方根誤差、檢測概率、空間功率譜、仿真耗時等多個角度對新提出的算法進行了仿真,并通過與現(xiàn)有算法的對比,驗證了其優(yōu)秀的檢測性能。
[Abstract]:Acoustic vector sensor is composed of sound pressure sensor and particle vibration velocity sensor. It has the characteristics of collecting sound pressure information (scalar) and vibration velocity information (vector) synchronously in the spatial environment. The increased data dimension is equivalent to more data shot and has higher detection sensitivity than sound pressure sensor. However, a large number of existing acoustic vector array signal processing techniques are based on the vector sensor's vibration velocity information as additional independent elements, without fully utilizing the correlation between sound pressure and vibration velocity in far-field environment. As a matter of fact, the sound pressure and velocity are non-correlated in various homogeneous noise fields, which can effectively reduce the influence and interference caused by the white Gao Si noise in the estimation of the DOA of the signal. On the basis of reviewing the basic principle of acoustic vector sensor, the physical foundation of combined information processing of acoustic pressure and vibration velocity and the technology of acoustic vector array signal processing based on subspace algorithm, The algorithm of vector sensor array signal processing is improved by using the combined information of sound pressure and vibration velocity, which provides a feasible solution for efficiently locating target azimuth in low signal-to-noise ratio (SNR) environment. In this paper, P-V cross covariance matrix based on acoustic pressure and velocity contact information is introduced to process received data signals. The new covariance matrix synthesizes the vibration velocity information to a certain observation direction, avoids the dimension increase of the received data matrix, thus reduces the computational complexity of the acoustic vector array signal processing. In the following processing of the received signal matrix, an improved Unitary-Root music algorithm based on P-V cross-covariance matrix of acoustic vector sensor array is proposed, which combines the existing Unitary-MUSIC algorithm and Root-MUSIC algorithm. This algorithm not only improves the performance of signal detection, but also reduces the computational complexity. This paper also simulates the proposed algorithm from different SNR conditions, such as root mean square error, detection probability, spatial power spectrum, time consuming and so on, and verifies its excellent detection performance by comparing with existing algorithms.
【學位授予單位】：哈爾濱工業(yè)大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：TP212;TN911.7

【參考文獻】

相關期刊論文 前1條

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本文編號：2025449