【摘要】：海洋水聲調(diào)查既是水聲信道物理規(guī)律性研究的基礎(chǔ),又為聲納設(shè)備的設(shè)計和研制提供依據(jù),一般包括聲源級、聲傳播損失、噪聲、海洋混響、聲速剖面和海底聲學特性測量等。海洋水聲調(diào)查數(shù)據(jù)處理目標在于生成海洋聲學調(diào)查數(shù)據(jù)處理結(jié)果數(shù)據(jù)庫,為海洋環(huán)境信息系統(tǒng)建設(shè)提供基礎(chǔ)性數(shù)據(jù)支持。海洋水聲調(diào)查數(shù)據(jù)量大,傳統(tǒng)的處理方法,人工干預(yù)度大,處理速度慢,對處理人員的專業(yè)性要求較高。本文重點研究聲源級測量、聲傳播損失測量和噪聲測量的數(shù)據(jù)自動處理關(guān)鍵技術(shù),旨在提高處理效率,降低人員干預(yù)度和提高處理結(jié)果質(zhì)量。本文從聲納方程入手,介紹了典型的水聲調(diào)查方法和三分之一倍頻程寬度水聲參量的計算方法。利用球面擴展規(guī)律和水聽器測量得到的信號級,推算聲源級,利用聲源級減去信號級得到聲傳播損失,利用周期圖法估計噪聲的功率譜。論文重點之一是研究實際海洋中的瞬態(tài)信號的自動檢測方法。分析了海洋噪聲的頻譜特性,得出噪聲的主要能量集中在100Hz以下的低頻部分,采用Hinich方法和直方圖法分析海洋噪聲的高斯性,得出持續(xù)秒級的海洋噪聲呈現(xiàn)非高斯分布,而噪聲通過截止頻率為100Hz的高通濾波器后,統(tǒng)計特性近似為高斯分布,因此檢測前數(shù)據(jù)先通過高通濾波器濾波。將海洋噪聲建模為海洋背景噪聲和瞬態(tài)干擾的線性疊加,提出了基于模型的能量檢測器的門限自適應(yīng)設(shè)置方法,使得門限在近收發(fā)距離處高,隨著距離的增加不斷下降,這樣兼顧了近接收距離處低虛警概率和遠接收距離處高檢測概率的要求。論文研究了實驗環(huán)境中,水聽器深度起伏對聲傳播測量的影響,仿真分析結(jié)果表明,該影響不能忽略。由此提出了基于模型的修正方法,即用模型預(yù)測某一收發(fā)距離和聲源深度下,聲傳播損失隨接收深度的變化規(guī)律,再利用多項式擬合固定深度附近聲傳播損失和接收深度的關(guān)系,進而將有深度擾動的測量值修正到固定深度處的值,通過實驗數(shù)據(jù),說明了方法的可行性。這是論文的又一重點。論文最后構(gòu)建了海洋水聲環(huán)境調(diào)查處理系統(tǒng),包括聲源級測量、聲傳播損失測量和噪聲級測量等功能。處理系統(tǒng)首先對測量的原始數(shù)據(jù)作規(guī)范化整理,高通濾波,爆炸波或噪聲截取,信息同步,生成預(yù)處理數(shù)據(jù)；然后對預(yù)處理數(shù)據(jù)進行1/3倍頻程劃分,計算相應(yīng)的聲源級、傳播損失和噪聲級參數(shù)。
[Abstract]:The underwater acoustic survey is not only the basis of the research on the physical regularity of underwater acoustic channel, but also provides the basis for the design and development of sonar equipment, generally including sound source level, loss of sound propagation, noise, marine reverberation, sound velocity profile and measurement of underwater acoustic characteristics, etc. The purpose of data processing of underwater acoustic survey is to generate the database of the data processing results of ocean acoustic survey, and to provide basic data support for the construction of marine environmental information system. Because of the large amount of data and the traditional methods of underwater acoustic survey, the degree of manual intervention is large, the processing speed is slow, and the professional requirement of the personnel is high. This paper focuses on the key techniques of sound source level measurement, sound propagation loss measurement and noise measurement data automatic processing, which aims to improve processing efficiency, reduce staff intervention and improve the quality of processing results. Based on sonar equation, this paper introduces the typical underwater acoustic survey method and the calculation method of 1/3 times width underwater acoustic parameters. By using the law of spherical expansion and the signal level measured by hydrophone, the sound source level is calculated, the sound propagation loss is obtained by subtracting the signal level from the sound source level, and the power spectrum of noise is estimated by using the period diagram method. One of the emphases of this paper is to study the automatic detection method of transient signals in the real ocean. The spectral characteristics of ocean noise are analyzed. It is concluded that the main energy of noise is concentrated in the low frequency part below 100Hz. The Gao Si character of ocean noise is analyzed by Hinich method and histogram method. After the noise passes through the high-pass filter with cut-off frequency of 100Hz, the statistical characteristic is approximately Gao Si distribution, so the data is filtered by high-pass filter before detection. The ocean noise is modeled as the linear superposition of the background noise and the transient interference, and the adaptive threshold setting method of the energy detector based on the model is proposed, which makes the threshold high at the close range and decreases with the increase of the distance. In this way, the requirements of low false alarm probability and high detection probability at near receiving distance are taken into account. The effect of hydrophone depth fluctuation on acoustic propagation measurement is studied in this paper. The simulation results show that the influence can not be ignored. Therefore, a model-based correction method is proposed, that is, the model is used to predict the variation of the sound propagation loss with the receiving depth at a certain transmitting distance and sound source depth. The relation between the sound propagation loss near the fixed depth and the receiving depth is fitted by polynomial, and then the measured value with depth disturbance is corrected to the value at the fixed depth. The feasibility of the method is illustrated by the experimental data. This is another important point of the paper. At the end of the paper, the system of underwater acoustic environment investigation and treatment is constructed, which includes sound source level measurement, sound propagation loss measurement and noise level measurement. The processing system first normalizes the measured raw data, high-pass filtering, explosive wave or noise interception, synchronization of information, generation of preprocessing data, and then divides the preprocessed data by 1 / 3 octave, and calculates the corresponding sound source level. Propagation loss and noise level parameters.
【學位授予單位】：浙江大學
【學位級別】：碩士
【學位授予年份】：2015
【分類號】：P733.2;TB56

【參考文獻】

相關(guān)期刊論文 前10條

1 劉清宇;馬樹青;楊華;;爆炸聲源聲源級數(shù)據(jù)分析方法[J];聲學與電子工程;2014年04期

2 屈新岳;;海洋調(diào)查工作的發(fā)展與現(xiàn)實問題分析及對策[J];氣象水文海洋儀器;2011年03期

3 肖勇兵;陳鴻志;鄭耀;胡曉峰;;海洋水聲調(diào)查中爆炸聲聲源級的測量分析[J];海洋技術(shù);2009年02期

4 趙先龍;孫磊;王川;;海洋水聲調(diào)查及信號處理方法的研究[J];海洋測繪;2009年02期

5 趙先龍;王川;孫磊;鄧玉芬;;海洋水聲環(huán)境調(diào)查數(shù)據(jù)處理系統(tǒng)的設(shè)計與實現(xiàn)[J];海洋測繪;2009年01期

6 胡友峰,焦秉立;高階譜雙通道的水聲信號檢測方法研究[J];聲學技術(shù);2005年02期

7 唐震,程玉勝;艦船輻射噪聲的非高斯特性和非線性檢驗[J];青島大學學報(自然科學版);2002年03期

8 周越,楊杰,胡英;基于高階累積量的水聲噪聲檢測與識別[J];兵工學報;2002年01期

9 王燕麟;基于匹配濾波器的LFM信號高階譜檢測[J];聲學與電子工程;1997年04期

10 朱業(yè),張仁和;負躍層淺海中的脈沖聲傳播[J];中國科學(A輯 數(shù)學 物理學 天文學 技術(shù)科學);1996年03期

相關(guān)博士學位論文 前1條

1 盛振新;水下連續(xù)爆炸聲學特性及信號分析研究[D];南京理工大學;2013年

相關(guān)碩士學位論文 前1條

1 劉雪宜;水下機器人多普勒測速聲納系統(tǒng)仿真[D];哈爾濱工程大學;2006年

，

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