本文關(guān)鍵詞： 有限新息率 聲吶回波信號(hào) 多普勒聚焦 目標(biāo)檢測(cè) 信號(hào)恢復(fù)　出處：《哈爾濱工業(yè)大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

【摘要】：聲吶系統(tǒng)目前正向系統(tǒng)性、綜合性方向發(fā)展,意味著聲吶系統(tǒng)將越來(lái)越復(fù)雜,有效的采樣及數(shù)據(jù)傳輸是重要基礎(chǔ)。傳統(tǒng)奈奎斯特采樣產(chǎn)生的數(shù)據(jù)量對(duì)于聲吶系統(tǒng)中的水下數(shù)據(jù)傳輸及無(wú)線數(shù)據(jù)傳輸來(lái)說(shuō)過(guò)大。因此,研究面向聲吶回波信號(hào)的高效的采樣方案很有必要。近年來(lái)提出的有限新息率(Finite Rate of Innovation,FRI)采樣理論能夠根據(jù)遠(yuǎn)低于奈奎斯特的采樣率獲得的采樣值,利用恢復(fù)算法估計(jì)出FRI信號(hào)的自由參量。本文將聲吶回波信號(hào)建模為參數(shù)化信號(hào)后,可以利用有限新息率采樣理論來(lái)對(duì)聲吶回波信號(hào)進(jìn)行欠采樣。首先對(duì)聲吶回波信號(hào)進(jìn)行模擬預(yù)處理,然后利用低速采樣獲得的采樣值獲得聲吶回波信號(hào)的傅里葉級(jí)數(shù)系數(shù)集,再根據(jù)回波信號(hào)特點(diǎn)利用不同的恢復(fù)算法估計(jì)未知參數(shù)。主要研究?jī)?nèi)容包括:1、研究聲吶回波信號(hào)的建模及FRI采樣理論。對(duì)聲吶回波信號(hào)的建模進(jìn)行了詳細(xì)的闡述,包括采用亮點(diǎn)模型法對(duì)目標(biāo)回波信號(hào)進(jìn)行建模,采用點(diǎn)散射方法與單元散射方法相結(jié)合的方式對(duì)混響信號(hào)進(jìn)行建模。研究了FRI采樣理論的采樣過(guò)程及恢復(fù)過(guò)程,針對(duì)不同的采樣結(jié)構(gòu)及恢復(fù)算法分別進(jìn)行比較,為利用有限新息率采樣理論處理聲吶回波信號(hào)提供理論基礎(chǔ)。2、針對(duì)無(wú)混響時(shí)靜止點(diǎn)目標(biāo)的檢測(cè),提出將聲吶回波信號(hào)建模為由時(shí)延和幅度參數(shù)決定的參數(shù)化信號(hào),能夠應(yīng)用FRI采樣理論。分別探究了利用單通道調(diào)制低通濾波結(jié)構(gòu)及多通道調(diào)制積分結(jié)構(gòu)來(lái)獲取聲吶回波信號(hào)的傅里葉級(jí)數(shù)系數(shù),兩種結(jié)構(gòu)有各自的優(yōu)缺點(diǎn),可根據(jù)具體情況選擇適合的采樣結(jié)構(gòu),并分析了對(duì)兩種采樣結(jié)構(gòu)恢復(fù)效果的影響因素。3、針對(duì)混響背景下的動(dòng)目標(biāo)檢測(cè),提出將目標(biāo)回波信號(hào)建模為由時(shí)延、幅度和多普勒頻率參數(shù)決定的參數(shù)化信號(hào),可以利用FRI采樣理論實(shí)現(xiàn)欠采樣。根據(jù)目標(biāo)回波信號(hào)與混響信號(hào)多普勒頻率不同的特點(diǎn),應(yīng)用多普勒聚焦技術(shù)對(duì)聲吶回波信號(hào)進(jìn)行處理,可以排除混響的干擾,先恢復(fù)目標(biāo)的多普勒頻率,再恢復(fù)時(shí)延參數(shù)和幅度參數(shù),說(shuō)明了多普勒聚焦處理的優(yōu)勢(shì)并進(jìn)行了仿真驗(yàn)證。4、聲吶回波信號(hào)FRI采樣的硬件實(shí)驗(yàn)驗(yàn)證。完成了硬件部分的模塊設(shè)計(jì),搭建了由乘法器模塊、放大器模塊和模擬低通濾波模塊等組成的模擬預(yù)處理結(jié)構(gòu)。利用LabVIEW上位機(jī)編程控制NI PXIe設(shè)備完成了信號(hào)模擬輸出、數(shù)據(jù)采集、數(shù)據(jù)存儲(chǔ)及上位機(jī)重構(gòu)等功能。本文通過(guò)大量實(shí)驗(yàn)證明了所設(shè)計(jì)的FRI欠采樣系統(tǒng)能夠?qū)崿F(xiàn)對(duì)聲吶回波信號(hào)的欠采樣,壓縮比能夠達(dá)到4.72%。
[Abstract]:Sonar systems are developing in the direction of systematization and comprehensiveness, which means that sonar systems will become more and more complex. Effective sampling and data transmission is an important foundation. Traditional Nyquist sampling produces too much data for underwater data transmission and wireless data transmission in sonar systems. It is necessary to study an efficient sampling scheme for sonar echo signals. A new finite Rate of Innovation has been proposed in recent years. Fri) sampling theory can estimate the free parameters of FRI signal based on the sampling value which is far lower than the Nyquist sampling rate. In this paper, the sonar echo signal is modeled as parameterized signal. The limited new sampling theory can be used to undersample the sonar echo signal. Firstly, the sonar echo signal can be simulated and preprocessed. Then the Fourier series coefficient set of sonar echo signal is obtained by using the sampling value obtained by low-speed sampling, and then the unknown parameters are estimated by different recovery algorithms according to the characteristics of echo signal. The main research contents include: 1. The modeling of sonar echo signal and FRI sampling theory are studied. The modeling of sonar echo signal is described in detail, including the modeling of target echo signal by using bright spot model method. The reverberation signal is modeled by the combination of point scattering method and element scattering method. The sampling process and recovery process of FRI sampling theory are studied. Different sampling structures and recovery algorithms are compared to provide a theoretical basis for processing sonar echo signal using finite new sampling rate theory and to detect static point targets without reverberation. The sonar echo signal is modeled as a parameterized signal determined by delay and amplitude parameters. FRI sampling theory can be applied to explore the use of single-channel modulation low-pass filter structure and multi-channel modulation integration structure to obtain the Fourier series coefficients of sonar echo signal. The two structures have their own advantages and disadvantages. The suitable sampling structure can be selected according to the specific situation, and the factors affecting the recovery effect of the two sampling structures are analyzed. Aiming at the moving target detection under reverberation background, the target echo signal is modeled as time delay. The parametric signals determined by amplitude and Doppler frequency parameters can be undersampled by using FRI sampling theory. According to the characteristics of Doppler frequency of target echo signal and reverberation signal, the Doppler frequency of target echo signal is different from that of reverberation signal. The Doppler focusing technique is used to process sonar echo signal, which can eliminate reverberation interference, recover the Doppler frequency of the target first, and then recover the delay parameters and amplitude parameters. The advantages of Doppler focusing processing are explained and the simulation verification. 4. The hardware experiment of sonar echo signal FRI sampling is carried out. The module design of hardware part is completed and the multiplier module is built. The amplifier module and the analog low-pass filter module are used in the analog preprocessing structure. The LabVIEW upper computer is used to control the NI PXIe equipment to complete the analog output and data acquisition. Data storage and host computer reconfiguration functions. In this paper, a large number of experiments show that the FRI under-sampling system can realize the under-sampling of sonar echo signal, and the compression ratio can reach 4.72.
【學(xué)位授予單位】：哈爾濱工業(yè)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TB56

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