本文選題：艦船輻射噪聲 + 匹配小波��； 參考：《昆明理工大學(xué)》2014年碩士論文

【摘要】：艦船輻射噪聲是艦船特征信號(hào)的一個(gè)重要標(biāo)志,其線譜由于傳播距離遠(yuǎn)、衰減緩慢、能量集中、所含信息量豐富等特點(diǎn)成為研究艦船輻射噪聲的重點(diǎn)。由于海洋背景噪聲復(fù)雜多變,實(shí)際接收的艦船輻射噪聲十分微弱,線譜變得越來越難于檢測(cè)和提取,因此線譜識(shí)別問題值得深刻研究。 小波分析是近年來發(fā)展起來的信號(hào)處理方法,其突出的時(shí)頻局部特性及優(yōu)異的去相關(guān)能力得到了廣泛應(yīng)用,并取得了顯著的效果,特別是能有效檢測(cè)信號(hào)的奇異點(diǎn)。本文在剖析艦船輻射噪聲特點(diǎn)的基礎(chǔ)上,從一個(gè)新的角度,根據(jù)艦船輻射噪聲的頻域特征,從選取最優(yōu)小波基入手,由小波變換與奇異性的聯(lián)系對(duì)低信噪比的艦船輻射噪聲的線譜進(jìn)行分析。按照小波基選取三個(gè)準(zhǔn)則,選取bior5.5小波為最優(yōu)基,并通過不同小波基對(duì)艦船輻射噪聲功率譜奇異性的檢測(cè)比較,驗(yàn)證了bior5.5的最優(yōu)性,其近似正交性保證了重構(gòu)信號(hào)的精確度,也兼顧了對(duì)小波基緊支性和正則性的要求。 為了精確模擬低信噪比信號(hào)中的真實(shí)線譜,通過設(shè)置不同信噪比噪聲背景下,將艦船輻射噪聲分低頻段、中頻段、高頻段三個(gè)頻帶進(jìn)行多角度線譜分析。在低頻段,本文論述了基于小波變換的信號(hào)匹配分析方法。經(jīng)不同小波基處理的實(shí)驗(yàn)結(jié)果比較,只有bior5.5小波基能準(zhǔn)確提取艦船輻射噪聲的特征；在中頻段,本文總結(jié)構(gòu)造閾值函數(shù)用于小波去噪的必要條件下,改進(jìn)了一種新閾值函數(shù),并巧妙地將其應(yīng)用到艦船輻射噪聲分析,重新完善了基于小波變換的中頻段信號(hào)匹配分析方法,實(shí)現(xiàn)了線譜提取；在高頻段,則引入基于小波包變換的信號(hào)匹配分析方法,大量實(shí)驗(yàn)表明三種方法的有效性、可行性以及各自的匹配性。本文首次從頻域的角度對(duì)艦船的特征信號(hào)進(jìn)行小波分析,得到了一些有意義的初步結(jié)果,證明了bior5.5小波基對(duì)艦船輻射噪聲信號(hào)分析有良好的分辨率。
[Abstract]:Ship radiated noise is an important symbol of ship characteristic signal. Because of its long propagation distance, slow attenuation, concentrated energy, abundant information and so on, its line spectrum has become the focus of research on ship radiated noise. Because of the complex and changeable background noise and the weak radiated noise of the ship actually received, the line spectrum becomes more and more difficult to detect and extract, so the problem of line spectrum recognition is worth studying deeply. Wavelet analysis is a signal processing method developed in recent years. Its outstanding time-frequency local characteristics and excellent ability of de-correlation have been widely used, and have achieved remarkable results, especially the singularity can be effectively detected. On the basis of analyzing the characteristics of ship radiated noise, from a new point of view, according to the frequency domain characteristics of ship radiated noise, this paper begins with the selection of optimal wavelet basis. The linear spectrum of ship radiated noise with low signal-to-noise ratio (SNR) is analyzed by the relation between wavelet transform and singularity. According to three criteria of wavelet basis selection, bior5.5 wavelet is chosen as the optimal basis, and the singularity of power spectrum of ship radiated noise is detected by different wavelet bases. The optimality of bior5.5 is verified, and its approximate orthogonality ensures the accuracy of reconstructed signal. It also gives consideration to the requirements of wavelet basis compactness and regularity. In order to accurately simulate the true line spectrum of low signal-to-noise ratio (SNR) signal, the ship radiated noise is divided into three frequency bands: low frequency band, middle frequency band and high frequency band by setting different signal-to-noise ratio (SNR) noise background. In low frequency band, the method of signal matching analysis based on wavelet transform is discussed in this paper. By comparing the experimental results of different wavelet bases, only bior5.5 wavelet bases can accurately extract the features of ship radiated noise. In the middle frequency band, this paper summarizes the necessary conditions of constructing threshold functions for wavelet denoising, and improves a new threshold function. It is skillfully applied to the analysis of ship radiated noise, and the matching analysis method based on wavelet transform is improved to realize line spectrum extraction, and the signal matching analysis method based on wavelet packet transform is introduced in high frequency band. A large number of experiments show that the three methods are effective, feasible and matching. In this paper, the characteristic signals of ships are analyzed by wavelet analysis in frequency domain for the first time, and some significant preliminary results are obtained. It is proved that bior5.5 wavelet bases have good resolution for the analysis of ship radiated noise signals.
【學(xué)位授予單位】：昆明理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：U674.70;TN911.4

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