波导Helix阵三维Fourier变换匹配场定位
发布时间：2018-10-20 09:11
【摘要】：水声探测的核心问题之一是目标声源的被动定位问题。被动定位问题本质是逆问题推断,通过对传感器阵接收的含有噪声的目标辐射声信号在空间和时间上采样、分析,结合传播模型和先验知识等正向知识,推断目标所在的空间位置。目标辐射声信号是在一个上下有界,左右无界的三维波导内传播,是三维声场,目标位置具有三维属性。通常使用的水平线阵或垂直线阵都只是在一维声场上进行采样,没有对三维波导进行充分的空间采样,因而不具备对目标声源的三维定位能力。水平阵只能进行方位角估计,垂直线阵只能对距离-深度定位。本文研究具备三维声场采样能力的双螺旋阵(Helix)的性质和三维联合定位。在声源被动定位问题中,目标在每个瞬时时刻只会出现在空间中的某个点上,数学抽象为,目标在空-时上具有Dirac delta函数性质。被动定位,应当具备与之相适应的能力,在定位结果上,逼近Dirac delta函数。实现这一能力的定位方法是匹配滤波,波导中的水下目标定位,其拷贝是发射信号经传播模型(模拟信道内声场的正向传播)产生的模型场信号,与数据场信号进行匹配得到模糊度表面,最大函数值对应的坐标即是估计的声源位置。这样一种匹配既可以在阵元域内进行,也可以在空间频率域即波数域内进行,因为它们是一对可逆Fourier变换,更有趣的是,人们常常工作在波数域而不是阵元域。实际处理中,阵列对空间的采样和传感器对时间波形的采样总是有限的。根据Gabor不确实性原理,一个域的有限会带来另一个域的扩展。所以有限采样对应的谱域表现就是偏置与泄露,在定位结果的模糊度表面上就显现出旁瓣。为了使结果尽可能地逼近Dirac delta函数,需要在谱域中施以权重作用,将其能量集中在主瓣内而降低旁瓣响应。最佳的权函数是信道响应函数的逆,然而逆问题并不总是存在的且不易计算。一个更广泛而宽容的权函数是信道响应的伴随,对应时域就是时反,对应频域就是共轭,这也导出匹配滤波的概念。本文从数学空间角度出发,根据完备正交归一序列与delta函数之间的完备性关系,利用三维空间Fourier变换,在波数域进行匹配,近似delta函数,实现水下声源定位,即波导中空谱估计声源定位。本文研究空间Fourier变换,尤其是三维Helix阵的空间Fourier变换的特性。以此为基础,本文依次研究Helix阵及其褪化阵列的空谱特性。之后在波导环境中,研究Helix阵及其褪化阵空间Fourier变换匹配定位问题,并对比阵元域匹配场定位。最后,在实验室波导中,设计并实现了三维Helix阵的声源定位验证实验。
[Abstract]:One of the core problems of underwater acoustic detection is the passive location of target sound source. The passive localization problem is essentially an inverse problem. By sampling and analyzing the acoustic signals of the target with noise received by the sensor array in space and time, combining forward knowledge such as propagation model and prior knowledge, Infer the spatial location of the target. The radiated acoustic signal of the target propagates in a three dimensional waveguide with the upper and lower bounds and the left and right unbounded waveguides. It is a three dimensional sound field and the position of the target has three dimensional properties. Usually, the horizontal or vertical linear arrays are only sampled on one dimensional sound field, and the 3D waveguides are not fully sampled in space, so they do not have the ability to locate the target sound source. Horizontal array can only estimate azimuth, vertical linear array can only locate distance-depth. In this paper, the properties of double helical array (Helix) with three dimensional sound field sampling ability and three dimensional joint positioning are studied. In the passive acoustic source localization problem, the target will only appear at a certain point in space at every instantaneous time. The mathematical abstraction is that the target has the property of Dirac delta function in space-time. Passive positioning should have the ability to adapt to the location results, approximate the Dirac delta function. The localization method to achieve this capability is matched filtering, the underwater target location in the waveguide, whose copy is the model field signal generated by the propagation model of the transmitted signal (the forward propagation of the sound field in the analog channel). The ambiguity surface is obtained by matching the data field signal, and the coordinates corresponding to the maximum function value are the estimated sound source position. Such a matching can be carried out either in the array element domain or in the spatial frequency domain or in the wavenumber domain because they are a pair of invertible Fourier transformations. What is more interesting is that people often work in the wave-number domain rather than in the array element domain. In practical processing, the spatial sampling of array and the sampling of time waveform by sensor are always limited. According to the principle of Gabor uncertainty, the finite of one domain leads to the extension of another domain. Therefore, the spectral domain corresponding to the finite sampling is represented by bias and leakage, and the sidelobe appears on the ambiguity surface of the localization result. In order to approximate the Dirac delta function as much as possible, it is necessary to apply the weight in the spectral domain and concentrate its energy in the main lobe to reduce the sidelobe response. The optimal weight function is the inverse of the channel response function, however, the inverse problem does not always exist and is difficult to calculate. A more extensive and tolerant weight function is the adjoint of channel response. The corresponding time-domain is time-inverse and the corresponding frequency-domain is conjugate, which also leads to the concept of matched filtering. From the point of view of mathematical space, according to the completeness relation between complete orthonormal normalized sequence and delta function, using Fourier transform in three dimensional space, matching in wavenumber domain, approximate delta function, the underwater sound source location is realized. That is, waveguide hollow spectrum estimation of sound source location. In this paper, we study the characteristics of spatial Fourier transform, especially the spatial Fourier transformation of 3D Helix matrix. On this basis, the space-spectrum characteristics of Helix array and its chlorinated array are studied in turn. Then, in the waveguide environment, the matching localization problem of Helix array and its fading array space Fourier transform is studied, and the matching field localization in array element domain is compared. Finally, the sound source location verification experiment of 3D Helix array is designed and implemented in the laboratory waveguide.
【学位授予单位】：浙江大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TB566
本文编号：2282697
[Abstract]:One of the core problems of underwater acoustic detection is the passive location of target sound source. The passive localization problem is essentially an inverse problem. By sampling and analyzing the acoustic signals of the target with noise received by the sensor array in space and time, combining forward knowledge such as propagation model and prior knowledge, Infer the spatial location of the target. The radiated acoustic signal of the target propagates in a three dimensional waveguide with the upper and lower bounds and the left and right unbounded waveguides. It is a three dimensional sound field and the position of the target has three dimensional properties. Usually, the horizontal or vertical linear arrays are only sampled on one dimensional sound field, and the 3D waveguides are not fully sampled in space, so they do not have the ability to locate the target sound source. Horizontal array can only estimate azimuth, vertical linear array can only locate distance-depth. In this paper, the properties of double helical array (Helix) with three dimensional sound field sampling ability and three dimensional joint positioning are studied. In the passive acoustic source localization problem, the target will only appear at a certain point in space at every instantaneous time. The mathematical abstraction is that the target has the property of Dirac delta function in space-time. Passive positioning should have the ability to adapt to the location results, approximate the Dirac delta function. The localization method to achieve this capability is matched filtering, the underwater target location in the waveguide, whose copy is the model field signal generated by the propagation model of the transmitted signal (the forward propagation of the sound field in the analog channel). The ambiguity surface is obtained by matching the data field signal, and the coordinates corresponding to the maximum function value are the estimated sound source position. Such a matching can be carried out either in the array element domain or in the spatial frequency domain or in the wavenumber domain because they are a pair of invertible Fourier transformations. What is more interesting is that people often work in the wave-number domain rather than in the array element domain. In practical processing, the spatial sampling of array and the sampling of time waveform by sensor are always limited. According to the principle of Gabor uncertainty, the finite of one domain leads to the extension of another domain. Therefore, the spectral domain corresponding to the finite sampling is represented by bias and leakage, and the sidelobe appears on the ambiguity surface of the localization result. In order to approximate the Dirac delta function as much as possible, it is necessary to apply the weight in the spectral domain and concentrate its energy in the main lobe to reduce the sidelobe response. The optimal weight function is the inverse of the channel response function, however, the inverse problem does not always exist and is difficult to calculate. A more extensive and tolerant weight function is the adjoint of channel response. The corresponding time-domain is time-inverse and the corresponding frequency-domain is conjugate, which also leads to the concept of matched filtering. From the point of view of mathematical space, according to the completeness relation between complete orthonormal normalized sequence and delta function, using Fourier transform in three dimensional space, matching in wavenumber domain, approximate delta function, the underwater sound source location is realized. That is, waveguide hollow spectrum estimation of sound source location. In this paper, we study the characteristics of spatial Fourier transform, especially the spatial Fourier transformation of 3D Helix matrix. On this basis, the space-spectrum characteristics of Helix array and its chlorinated array are studied in turn. Then, in the waveguide environment, the matching localization problem of Helix array and its fading array space Fourier transform is studied, and the matching field localization in array element domain is compared. Finally, the sound source location verification experiment of 3D Helix array is designed and implemented in the laboratory waveguide.
【学位授予单位】：浙江大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TB566
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