【摘要】：隨著人類對海洋資源的深入開發(fā)以及對探測方面日益增長的民用和軍用需求,傳統(tǒng)的信號檢測方法已經(jīng)不能滿足這些要求。為了提高信號處理的性能,本文采用一種基于經(jīng)驗(yàn)?zāi)Ｊ椒纸獾母倪M(jìn)方法-總體經(jīng)驗(yàn)?zāi)Ｊ椒纸夥椒▉磉M(jìn)行信號處理,仿真研究了該算法的性能,并使用基于總體經(jīng)驗(yàn)?zāi)Ｊ椒纸夥椒ê突谛〔ò纸夥椒▽π盘栠M(jìn)行檢測,對比性能,最后使用這種方法進(jìn)行實(shí)際數(shù)據(jù)的處理。論文的主要內(nèi)容如下:首先,分別對點(diǎn)源和偶極子源在自由場和波導(dǎo)中傳播進(jìn)行建模仿真后,得到標(biāo)、矢量信息,可以得出聲波在波導(dǎo)中傳播時,在波導(dǎo)匯聚區(qū)傳播的聲波比其在自由場中傳播的衰減更小。其次,對小波包分解算法的理論基礎(chǔ)進(jìn)行了研究,推導(dǎo)了小波包的頻率順序,使用兩種小波包閾值對加噪信號進(jìn)行去噪處理,仿真后比較了兩種閾值的均方根誤差(RMSE),選取自適應(yīng)閾值的均方根誤差比固定閾值的均方根誤差更小,具有更好的去噪效果。將熵理論與小波包理論相結(jié)合,應(yīng)用到信號檢測中,得到基于小波包能量熵算法的檢測性能,提供了性能對比。然后,研究了 EMD方法的理論基礎(chǔ),對EMD方法中存在的模態(tài)混疊問題進(jìn)行了分析。為了抑制分解間斷信號時EMD算法的模態(tài)混疊問題,本論文采用總體經(jīng)驗(yàn)?zāi)Ｊ椒纸?EEMD)方法來進(jìn)行解決。由于EEMD可以通過添加高斯白噪聲并利用EMD的二元濾波器組的特性,通過仿真對EEMD算法中的相關(guān)參數(shù)進(jìn)行了分析、選定,可以很好的克服間斷信號EMD過程中的模態(tài)混疊問題,然后將這種方法應(yīng)用到信號檢測中,與信號的EEMD能量熵相結(jié)合,并使用浮動門限對信號進(jìn)行檢測。與基于小波包能量熵方法進(jìn)行比較后發(fā)現(xiàn)基于EEMD能量熵的檢測方法比基于小波包的方法檢測性能更好。最后將這種方法對試驗(yàn)數(shù)據(jù)進(jìn)行檢測,采用合適的門限后,基于此種方法的漏檢情況比基于小波包方法要少很多,且基于EEMD能量熵方法的檢測性能比基于小波包能量熵的檢測性能要更好,此種方法對試驗(yàn)數(shù)據(jù)處理是有效的,可以為水下信號的檢測提供技術(shù)支持。
[Abstract]:With the further development of marine resources and the increasing demand for civil and military exploration, the traditional signal detection methods can not meet these requirements. In order to improve the performance of signal processing, an improved method based on empirical mode decomposition, the global empirical mode decomposition, is adopted to process the signal. The performance of the algorithm is simulated. The method based on total empirical mode decomposition and wavelet packet decomposition is used to detect and compare the performance of the signal. Finally, the method is used to process the actual data. The main contents of the thesis are as follows: firstly, after modeling and simulating the propagation of point source and dipole source in the free field and waveguide, the scalar and vector information can be obtained, and the sound wave propagating in the waveguide can be obtained. The attenuation of sound waves propagating in the convergence region of the waveguide is less than that in the free field. Secondly, the theoretical basis of wavelet packet decomposition algorithm is studied, the frequency sequence of wavelet packet is deduced, and two kinds of wavelet packet threshold are used to Denoise the noised signal. Simulation results show that the root-mean-square error (RMS) of the two thresholds selected by (RMSE), is smaller than that of the fixed threshold, and the root-mean-square error of the adaptive threshold (RMSE), is better than that of the fixed threshold. The entropy theory is combined with the wavelet packet theory and applied to signal detection. The detection performance based on the wavelet packet energy entropy algorithm is obtained and the performance comparison is provided. Then, the theoretical basis of EMD method is studied, and the modal aliasing problem in EMD method is analyzed. In order to suppress the modal aliasing problem of EMD algorithm when discontinuous signal is decomposed, this paper uses the (EEMD) method of total empirical mode decomposition to solve the problem. Because EEMD can add Gao Si white noise and make use of the characteristic of binary filter bank of EMD, the related parameters in EEMD algorithm are analyzed and selected by simulation, which can overcome the problem of modal aliasing in the process of discontinuous signal EMD. Then this method is applied to signal detection, combined with the EEMD energy entropy of the signal, and the floating threshold is used to detect the signal. Compared with the energy entropy method based on wavelet packet, it is found that the detection method based on EEMD energy entropy is better than that based on wavelet packet. Finally, this method is used to detect the experimental data. After adopting the appropriate threshold, the leakage rate based on this method is much less than that based on wavelet packet method. The detection performance based on EEMD energy entropy method is better than that based on wavelet packet energy entropy. This method is effective for experimental data processing and can provide technical support for underwater signal detection.
【學(xué)位授予單位】：哈爾濱工程大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2015
【分類號】：P714;TB566

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本文編號：2201859