基于MEMS矢量水听器阵列的声目标定向定位技术研究
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摘要
将MEMS技术应用于水听器的研制是一种新的尝试。由中北大学自主研制的新型MEMS矢量水听器，具有体积小、矢量性、批量制造、一致性好且成本低等优势，其制作工艺和性能日趋成熟，因此研究基于MEMS矢量水听器阵列的声目标定向定位技术对其工程化应用具有重要的意义。
本论文系统研究了声矢量阵列信号处理的相关内容，通过数学建模、理论分析、算法仿真和MEMS矢量水听器阵列实验数据的处理等各个方面，测试了所提各种算法的性能，检验了MEMS矢量水听器的工程实用性。论文主要研究成果有：
（1）根据盖氏圆盘定理，提出了声矢量阵列的盖氏圆信号源数估计方法（GDE-V）及其修正形式（MGDE-V），给出了判断信号源数的准则，并通过在信号源相干时对协方差矩阵的修正，解决了相干信号源数的判断。仿真实验表明，GDE-V和MGDE-V方法可有效发挥矢量阵列的优势，与传统声压阵列相比，有更强的角度分辨能力，在左右舷声源分辨、相干声源分辨、低信噪比、小快拍数等方面具有更高的分辨概率，同时在相同阵列孔径下能分辨更多的信号源数。
（2）通过对声矢量阵列协方差矩阵的重构和引导方位的自适应选取，提出了声矢量阵列的求根MUSIC算法，同时为减少计算量，又提出其实值化形式。理论推导和仿真实验表明，所提算法在低信噪比、小快拍数情况下的估计性能要优于传统声压阵列的求根MUSIC算法。同时在MEMS水听器阵列的湖试实验中进行了应用，准确估计了声源的方位，并成功跟踪了机动船的运行轨迹。
（3）提出了声压振速联合处理的MUSIC算法。通过对观测方向的选择，将矢量水听器的振速输出进行投影，以此构成声压振速的互协方差矩阵，并通过特征分解实现声源的DOA估计。仿真实验表明了该算法在各向同性噪声场中具有比传统声压阵列的MUSIC算法更好的估计性能，同时也在MEMS矢量水听器阵列的湖试实验中得到成功应用。
（4）结合二维MEMS矢量水听器的特点，分析了各种类型误差对阵列性能影响的表达式，建立了在误差影响下的矢量阵列信号模型，并进一步提出了矢量阵列误差的自校正算法，最后通过仿真实验和MEMS矢量水听器阵列的湖试实验数据进行了验证。
（5）为解决非均匀结构矢量阵列的DOA估计，详细推导了四种常见非均匀结构矢量阵列的时延表达式，形成各阵列导向向量，提出了非均匀结构矢量阵列的MUSIC算法，并通过选择各阵列中性能最优的阵元结构设置，统计了各阵列在DOA估计中随信噪比和快拍数变化的成功概率和均方根误差，仿真实验表明，非均匀线阵在低信噪比和小快拍数的情况下具有更高的估计性能。
（6）结合MEMS矢量水听器阵列在不同环境中的实验数据，分别从实验数据预处理、环境噪声测量、声压振速相关性、矢量阵阵增益、方位估计等多个方面进行了分析与讨论，验证了文中所提算法的实用性，同时为MEMS矢量水听器的工程应用提供技术支撑。
论文主要创新有：
（1）提出了矢量阵列信号源数估计的盖氏圆方法，使得矢量阵列在信号源数估计方面的性能得到提升；
（2）提出了矢量阵列的Root-MUSIC算法及其实值化形式，使得矢量阵列在提高DOA估计精度的同时，能有效减少计算量，同时在MEMS矢量水听器阵列的实验中得到成功应用；
（3）提出了MEMS矢量水听器阵列误差的自校正算法，提高了各类算法的工程实用性。
MEMS矢量水听器的工程化应用是一个庞大的系统工程，仍然有大量的工作需要进行研究，真诚的希望本文的研究工作能有助于矢量阵列信号处理技术的深入研究和发展，推动MEMS矢量水听器更广泛的工程化应用。
The MEMS technology is a new attempt to design hydrophone. MEMS vectorhydrophone is a novel sensor researched independently by the North University of China,which has the advantages of small size, vector, lot manufacturing with well consistent, lowcost and so on. With the growing maturity of production process and performance, it is veryimportant for engineering applications that the research on the DOA estimation andlocalization technology to acoustic target for MEMS vector hydrophone array.
In this thesis, we studied the signal processing for acoustic vector sensor array. Throughmathematical modeling,theoretical analysis,algorithm simulation and experimental dataprocessing of MEMS vector hydrophone array and so on, we test the performance of differentalgorithms and the engineering practicability of MEMS vector hydrophone. The mainresearch results are follows.
(1)According to Gerschgorin disks theory, we propose the new signal numberestimation algorithm(GDE-V) and modified form(MGDE-V) for acoustic vector sensorarray, and given the criterion to detect the number of signals, in which the covariance matrixhas been adjusted for the coherent signals. Simulation experiments show that the GDE-Vmethod and MGDE-V method can efficiently exert the advantages of vector sensor array, andthey have better estimation performance for the port/starboard signals detecting, coherentsignals detecting, low SNR and few snapshot, and can distinguish more signals than acousticpressure sensor array with the same array aperture size.
(2)Through re-construction for the covariance matrix of acoustic vector sensor array andself-adaptive selecting for the lead orientation, we propose a new root-MUSIC algorithm andits real-valued form for acoustic vector sensor array. The theoretical derivation and simulationexperiments show that two new algorithms have better DOA estimation performance in lowSNR and few snapshot than traditional root-MUSIC algorithm for acoustic pressure sensorarray. In the lake trials of MEMS vector hydrophone array, the azimuth of acoustic source hasbeen accurately estimated and the running tracks of moto boats have been successfullyfollowed by two new algorithms.
(3)We propose a novel MUSIC algorithm with pressure and particle velocity combinedprocessing(PV-MUSIC) for acoustic vector sensor array, and make DOA estimation byeigen-decomposing for the cross-covariance matrix which is obtained by selecting for the lead orientation and projecting for the particle velocity of acoustic vector sensor. The simulationexperiments show the better DOA estimation performance of PV-MUSIC algorithm thantraditional MUSIC algorithm in isotropic noise field, and the PV-MUSIC algorithm has beensuccessfully application in lake trials of MEMS vector hydrophone array.
(4)According to the characteristics of two-dimensional MEMS vector hydrophone, wederivate the expression of various kinds of array errors, and build the vector array signalmodel under the influence of the error, further proposes self-calibration algorithm of acousticvector array error, and verify the algorithm by the simulation experiment and the measureddata in lake trials of MEMS vector hydrophone array.
(5)To solve the DOA estimation in non-uniform vector sensor array, we derivate thetime delay expression of four non-uniform vector sensor array and the array direction vector,and proposed the MUSIC algorithm for non-uniform vector array. Through selecting for thearray with optimization performance, we take statistic to the change of probability of successand RMSE with SNR and snapshots, simulate experiment shows that the performance ofnon-uniform line array is best, it has better DOA estimation performance in low SNR and fewsnapshots.
(6)Though the experimental data of MEMS vector hydrophone array in differentenvironments, we analysis and discuss about data preprocessing, measuring for environmentalnoise, the correlation of pressure and particle velocity, the gain of vector sensor array, DOAestimation and so on, and verify the feasibility of the proposed algorithms in this thesis, andprovide technical support for the engineering application of MEMS vector hydrophone.
The main innovations in the paper are follows.
(1)We propose the Gerschgorin disks algorithm estimating the signal number, which cangreatly improve the estimation performance for acoustic vector sensor array.
(2)We propose the Root-MUSIC algorithm and its real-valued form, which can improvethe DOA estimation accuracy and effectively reduce the computational complexity, and hasbeen successfully applied in the experiment of MEMS vector hydrophone array.
(3)We proposes the self-calibration algorithm of MEMS vector hydrophone arrayerror,which can improve the engineering practicability of various algortithms.
The engineering application of MEMS vector hydrophone is a huge systematic project,there are still a lot of work to research, we hope the work in this thesis are helpful to theresearch and development of acoustic vector array signal processing technology, and promotethe MEMS vector hydrophone more extensive engineering application.
本论文系统研究了声矢量阵列信号处理的相关内容，通过数学建模、理论分析、算法仿真和MEMS矢量水听器阵列实验数据的处理等各个方面，测试了所提各种算法的性能，检验了MEMS矢量水听器的工程实用性。论文主要研究成果有：
（1）根据盖氏圆盘定理，提出了声矢量阵列的盖氏圆信号源数估计方法（GDE-V）及其修正形式（MGDE-V），给出了判断信号源数的准则，并通过在信号源相干时对协方差矩阵的修正，解决了相干信号源数的判断。仿真实验表明，GDE-V和MGDE-V方法可有效发挥矢量阵列的优势，与传统声压阵列相比，有更强的角度分辨能力，在左右舷声源分辨、相干声源分辨、低信噪比、小快拍数等方面具有更高的分辨概率，同时在相同阵列孔径下能分辨更多的信号源数。
（2）通过对声矢量阵列协方差矩阵的重构和引导方位的自适应选取，提出了声矢量阵列的求根MUSIC算法，同时为减少计算量，又提出其实值化形式。理论推导和仿真实验表明，所提算法在低信噪比、小快拍数情况下的估计性能要优于传统声压阵列的求根MUSIC算法。同时在MEMS水听器阵列的湖试实验中进行了应用，准确估计了声源的方位，并成功跟踪了机动船的运行轨迹。
（3）提出了声压振速联合处理的MUSIC算法。通过对观测方向的选择，将矢量水听器的振速输出进行投影，以此构成声压振速的互协方差矩阵，并通过特征分解实现声源的DOA估计。仿真实验表明了该算法在各向同性噪声场中具有比传统声压阵列的MUSIC算法更好的估计性能，同时也在MEMS矢量水听器阵列的湖试实验中得到成功应用。
（4）结合二维MEMS矢量水听器的特点，分析了各种类型误差对阵列性能影响的表达式，建立了在误差影响下的矢量阵列信号模型，并进一步提出了矢量阵列误差的自校正算法，最后通过仿真实验和MEMS矢量水听器阵列的湖试实验数据进行了验证。
（5）为解决非均匀结构矢量阵列的DOA估计，详细推导了四种常见非均匀结构矢量阵列的时延表达式，形成各阵列导向向量，提出了非均匀结构矢量阵列的MUSIC算法，并通过选择各阵列中性能最优的阵元结构设置，统计了各阵列在DOA估计中随信噪比和快拍数变化的成功概率和均方根误差，仿真实验表明，非均匀线阵在低信噪比和小快拍数的情况下具有更高的估计性能。
（6）结合MEMS矢量水听器阵列在不同环境中的实验数据，分别从实验数据预处理、环境噪声测量、声压振速相关性、矢量阵阵增益、方位估计等多个方面进行了分析与讨论，验证了文中所提算法的实用性，同时为MEMS矢量水听器的工程应用提供技术支撑。
论文主要创新有：
（1）提出了矢量阵列信号源数估计的盖氏圆方法，使得矢量阵列在信号源数估计方面的性能得到提升；
（2）提出了矢量阵列的Root-MUSIC算法及其实值化形式，使得矢量阵列在提高DOA估计精度的同时，能有效减少计算量，同时在MEMS矢量水听器阵列的实验中得到成功应用；
（3）提出了MEMS矢量水听器阵列误差的自校正算法，提高了各类算法的工程实用性。
MEMS矢量水听器的工程化应用是一个庞大的系统工程，仍然有大量的工作需要进行研究，真诚的希望本文的研究工作能有助于矢量阵列信号处理技术的深入研究和发展，推动MEMS矢量水听器更广泛的工程化应用。
The MEMS technology is a new attempt to design hydrophone. MEMS vectorhydrophone is a novel sensor researched independently by the North University of China,which has the advantages of small size, vector, lot manufacturing with well consistent, lowcost and so on. With the growing maturity of production process and performance, it is veryimportant for engineering applications that the research on the DOA estimation andlocalization technology to acoustic target for MEMS vector hydrophone array.
In this thesis, we studied the signal processing for acoustic vector sensor array. Throughmathematical modeling,theoretical analysis,algorithm simulation and experimental dataprocessing of MEMS vector hydrophone array and so on, we test the performance of differentalgorithms and the engineering practicability of MEMS vector hydrophone. The mainresearch results are follows.
(1)According to Gerschgorin disks theory, we propose the new signal numberestimation algorithm(GDE-V) and modified form(MGDE-V) for acoustic vector sensorarray, and given the criterion to detect the number of signals, in which the covariance matrixhas been adjusted for the coherent signals. Simulation experiments show that the GDE-Vmethod and MGDE-V method can efficiently exert the advantages of vector sensor array, andthey have better estimation performance for the port/starboard signals detecting, coherentsignals detecting, low SNR and few snapshot, and can distinguish more signals than acousticpressure sensor array with the same array aperture size.
(2)Through re-construction for the covariance matrix of acoustic vector sensor array andself-adaptive selecting for the lead orientation, we propose a new root-MUSIC algorithm andits real-valued form for acoustic vector sensor array. The theoretical derivation and simulationexperiments show that two new algorithms have better DOA estimation performance in lowSNR and few snapshot than traditional root-MUSIC algorithm for acoustic pressure sensorarray. In the lake trials of MEMS vector hydrophone array, the azimuth of acoustic source hasbeen accurately estimated and the running tracks of moto boats have been successfullyfollowed by two new algorithms.
(3)We propose a novel MUSIC algorithm with pressure and particle velocity combinedprocessing(PV-MUSIC) for acoustic vector sensor array, and make DOA estimation byeigen-decomposing for the cross-covariance matrix which is obtained by selecting for the lead orientation and projecting for the particle velocity of acoustic vector sensor. The simulationexperiments show the better DOA estimation performance of PV-MUSIC algorithm thantraditional MUSIC algorithm in isotropic noise field, and the PV-MUSIC algorithm has beensuccessfully application in lake trials of MEMS vector hydrophone array.
(4)According to the characteristics of two-dimensional MEMS vector hydrophone, wederivate the expression of various kinds of array errors, and build the vector array signalmodel under the influence of the error, further proposes self-calibration algorithm of acousticvector array error, and verify the algorithm by the simulation experiment and the measureddata in lake trials of MEMS vector hydrophone array.
(5)To solve the DOA estimation in non-uniform vector sensor array, we derivate thetime delay expression of four non-uniform vector sensor array and the array direction vector,and proposed the MUSIC algorithm for non-uniform vector array. Through selecting for thearray with optimization performance, we take statistic to the change of probability of successand RMSE with SNR and snapshots, simulate experiment shows that the performance ofnon-uniform line array is best, it has better DOA estimation performance in low SNR and fewsnapshots.
(6)Though the experimental data of MEMS vector hydrophone array in differentenvironments, we analysis and discuss about data preprocessing, measuring for environmentalnoise, the correlation of pressure and particle velocity, the gain of vector sensor array, DOAestimation and so on, and verify the feasibility of the proposed algorithms in this thesis, andprovide technical support for the engineering application of MEMS vector hydrophone.
The main innovations in the paper are follows.
(1)We propose the Gerschgorin disks algorithm estimating the signal number, which cangreatly improve the estimation performance for acoustic vector sensor array.
(2)We propose the Root-MUSIC algorithm and its real-valued form, which can improvethe DOA estimation accuracy and effectively reduce the computational complexity, and hasbeen successfully applied in the experiment of MEMS vector hydrophone array.
(3)We proposes the self-calibration algorithm of MEMS vector hydrophone arrayerror,which can improve the engineering practicability of various algortithms.
The engineering application of MEMS vector hydrophone is a huge systematic project,there are still a lot of work to research, we hope the work in this thesis are helpful to theresearch and development of acoustic vector array signal processing technology, and promotethe MEMS vector hydrophone more extensive engineering application.
引文
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