基于MEMS矢量水聽器的信號處理與DOA估計
發(fā)布時間：2019-04-28 10:04
【摘要】：MEMS矢量水聽器的優(yōu)點在于它體積小、一致性好、成本低等優(yōu)勢,且能夠同時、共點地獲得聲場中的標量聲壓信息和矢量振速信息,而更豐富的輸出信號也為聲源目標的信號處理與波達方向估計提供了更多的處理手段,并且具備抵消各向同性噪聲干擾的能力。近年來,矢量水聽器技術(shù)在水下目標探測、潛艇隱身及聲源定向定位等領(lǐng)域受到了各海洋大國的普遍關(guān)注,并已用于水聲領(lǐng)域的工程應(yīng)用階段,而相關(guān)的信號處理問題也成為各國研究的前沿熱點。本文對自適應(yīng)算法和DOA估計算法在水聲信號處理中的應(yīng)用進行了比較系統(tǒng)的研究,主要研究內(nèi)容如下:(1)根據(jù)水聲信號與噪聲信號特征的差異性,針對MEMS水聽器采集的數(shù)據(jù)“淹沒”在強噪聲場中的問題,提出采用LMS自適應(yīng)噪聲對消與Fourier變換濾波相結(jié)合的改進算法進行信噪分離,對提取后的信號與理想信號做MATLAB仿真實驗對比,并從均方誤差(RMSE)、信噪比(SNR)、信噪比增益(GSNR)、相似度(R)等方面進行了去噪性能評價分析。仿真結(jié)果表明,該改進算法突破了傳統(tǒng)自適應(yīng)噪聲對消法在低信噪比(低于0dB)和非平穩(wěn)噪聲環(huán)境下去噪效果奇差的局限,在信噪比降至-15dB以下時,仍有很好的去噪能力。(2)利用改進去噪算法得到預(yù)處理信號,分別運用反切算法,平均聲強法,互譜算法及最小二乘法進行了單矢量水聽器的聲源的波達方向(DOA,Direction Of Arrival)估計,與設(shè)定的方位角進行均方誤差與成功率分析,評價改進算法與中心濾波算法的在不同快拍數(shù)和信噪比環(huán)境下的優(yōu)劣性能,為工程應(yīng)用提供實驗依據(jù)。(3)利用改進算法結(jié)合多重信號分類(Multiple Signal Classification,MUSIC)算法進行矢量水聽器陣列的DOA估計,評價改進MUSIC算法與原MUSIC算法的在不同快拍數(shù)和信噪比環(huán)境下的優(yōu)劣性能,分別比較分析了方位角估計的均方誤差與預(yù)測成功率,顯示出改進算法在低信噪比下的情況下仍有一定的工程應(yīng)用性。仿真結(jié)果表明:該改進去噪算法極大的提高了聲源方位角估計精度,其中平均聲強法、互譜法在小快拍數(shù)和低信噪比下也具有良好的單矢量水聽器DOA估計性能精度;改進MUSIC算法在小快拍數(shù)和低信噪比下要比原MUSIC算法要具有更高的預(yù)測成功率和更小的方位角均方誤差值。(4)最后,進行了汾河二庫實驗�；诜诤雍嚁�(shù)據(jù)的實驗處理結(jié)果表明:經(jīng)過數(shù)據(jù)預(yù)處理的定位定向結(jié)果顯示良好,性能良好,計算簡單高效,為工程實際應(yīng)用提供滿意的效果。
[Abstract]:The advantages of MEMS vector hydrophone are its small size, good consistency, low cost, and the ability to obtain the scalar sound pressure information and vector vibration velocity information in the sound field simultaneously and at the same time, the vector hydrophone has the advantages of small size, good consistency and low cost. The richer output signal also provides more processing means for signal processing and DOA estimation of sound source target and has the ability to counteract isotropic noise interference. In recent years, vector hydrophone technology in underwater target detection, submarine stealth and sound source orientation and other fields has been widely concerned by the major marine countries, and has been used in the field of underwater acoustic engineering application stage. And the related signal processing problem has also become a hot spot in the research of various countries. In this paper, the application of adaptive algorithm and DOA estimation algorithm in underwater acoustic signal processing is studied systematically. The main contents are as follows: (1) according to the difference of characteristics between underwater acoustic signal and noise signal, the main research contents are as follows: (1) according to the difference between underwater acoustic signal and noise signal, In order to solve the problem of "submerged" data collected by MEMS hydrophone in strong noise field, an improved algorithm combining LMS adaptive noise cancellation with Fourier transform filtering is proposed to separate the signal-to-noise (SNR). The extracted signal is compared with the ideal signal by MATLAB simulation, and the de-noising performance of the extracted signal is evaluated from the aspects of mean square error (RMSE), signal to noise ratio (SNR), signal to noise gain (GSNR), similarity (R) and so on. The simulation results show that the improved algorithm breaks through the limitation of the traditional adaptive noise cancellation method in low signal-to-noise ratio (lower than 0dB) and non-stationary noise. When the signal-to-noise ratio is lower than-15dB, the noise-to-noise ratio is lower than-noise. There is still good denoising ability. (2) pre-processing signal is obtained by using improved denoising algorithm. The direction of arrival (DOA,) of the source of single vector hydrophone is carried out by using anti-tangent algorithm, average sound intensity method, cross-spectral algorithm and least square method respectively. Direction Of Arrival) estimation, mean square error and success rate analysis of azimuth were performed to evaluate the performance of the improved algorithm and the center filtering algorithm in different fast beat number and signal-to-noise ratio (SNR) environment. It provides experimental basis for engineering application. (3) DOA estimation of vector hydrophone array is carried out by using improved algorithm combined with multiple signal classification (Multiple Signal Classification,MUSIC (Multi-signal Classification) algorithm. The advantages and disadvantages of the improved MUSIC algorithm and the original MUSIC algorithm under different snapshot number and signal-to-noise ratio (SNR) are evaluated. The mean square error and prediction success rate of azimuth estimation are compared and analyzed, respectively. It is shown that the improved algorithm still has some engineering application under the condition of low signal-to-noise ratio. The simulation results show that the improved de-noising algorithm greatly improves the accuracy of azimuth estimation of the sound source. The average sound intensity method and cross-spectrum method also have good performance accuracy for DOA estimation of single vector hydrophone under the condition of small snapshot number and low signal-to-noise ratio. The improved MUSIC algorithm has higher prediction success rate and smaller azimuth mean square error than the original MUSIC algorithm under the condition of small snapshot number and low signal-to-noise ratio. (4) at last, the Fenhe No. 2 reservoir experiment is carried out. The experimental results based on the experimental data of Fenhe Lake show that the orientation result after data preprocessing is good, the performance is good, the calculation is simple and efficient, and it provides a satisfactory effect for the practical application of the project.
【學(xué)位授予單位】：中北大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TB565.1
本文編號：2467543
[Abstract]:The advantages of MEMS vector hydrophone are its small size, good consistency, low cost, and the ability to obtain the scalar sound pressure information and vector vibration velocity information in the sound field simultaneously and at the same time, the vector hydrophone has the advantages of small size, good consistency and low cost. The richer output signal also provides more processing means for signal processing and DOA estimation of sound source target and has the ability to counteract isotropic noise interference. In recent years, vector hydrophone technology in underwater target detection, submarine stealth and sound source orientation and other fields has been widely concerned by the major marine countries, and has been used in the field of underwater acoustic engineering application stage. And the related signal processing problem has also become a hot spot in the research of various countries. In this paper, the application of adaptive algorithm and DOA estimation algorithm in underwater acoustic signal processing is studied systematically. The main contents are as follows: (1) according to the difference of characteristics between underwater acoustic signal and noise signal, the main research contents are as follows: (1) according to the difference between underwater acoustic signal and noise signal, In order to solve the problem of "submerged" data collected by MEMS hydrophone in strong noise field, an improved algorithm combining LMS adaptive noise cancellation with Fourier transform filtering is proposed to separate the signal-to-noise (SNR). The extracted signal is compared with the ideal signal by MATLAB simulation, and the de-noising performance of the extracted signal is evaluated from the aspects of mean square error (RMSE), signal to noise ratio (SNR), signal to noise gain (GSNR), similarity (R) and so on. The simulation results show that the improved algorithm breaks through the limitation of the traditional adaptive noise cancellation method in low signal-to-noise ratio (lower than 0dB) and non-stationary noise. When the signal-to-noise ratio is lower than-15dB, the noise-to-noise ratio is lower than-noise. There is still good denoising ability. (2) pre-processing signal is obtained by using improved denoising algorithm. The direction of arrival (DOA,) of the source of single vector hydrophone is carried out by using anti-tangent algorithm, average sound intensity method, cross-spectral algorithm and least square method respectively. Direction Of Arrival) estimation, mean square error and success rate analysis of azimuth were performed to evaluate the performance of the improved algorithm and the center filtering algorithm in different fast beat number and signal-to-noise ratio (SNR) environment. It provides experimental basis for engineering application. (3) DOA estimation of vector hydrophone array is carried out by using improved algorithm combined with multiple signal classification (Multiple Signal Classification,MUSIC (Multi-signal Classification) algorithm. The advantages and disadvantages of the improved MUSIC algorithm and the original MUSIC algorithm under different snapshot number and signal-to-noise ratio (SNR) are evaluated. The mean square error and prediction success rate of azimuth estimation are compared and analyzed, respectively. It is shown that the improved algorithm still has some engineering application under the condition of low signal-to-noise ratio. The simulation results show that the improved de-noising algorithm greatly improves the accuracy of azimuth estimation of the sound source. The average sound intensity method and cross-spectrum method also have good performance accuracy for DOA estimation of single vector hydrophone under the condition of small snapshot number and low signal-to-noise ratio. The improved MUSIC algorithm has higher prediction success rate and smaller azimuth mean square error than the original MUSIC algorithm under the condition of small snapshot number and low signal-to-noise ratio. (4) at last, the Fenhe No. 2 reservoir experiment is carried out. The experimental results based on the experimental data of Fenhe Lake show that the orientation result after data preprocessing is good, the performance is good, the calculation is simple and efficient, and it provides a satisfactory effect for the practical application of the project.
【學(xué)位授予單位】：中北大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TB565.1
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