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一种基于模态域波束形成的水平阵被动目标深度估计
引用本文:李鹏,章新华,付留芳,曾祥旭.一种基于模态域波束形成的水平阵被动目标深度估计[J].物理学报,2017,66(8):84301-084301.
作者姓名:李鹏  章新华  付留芳  曾祥旭
作者单位:1. 哈尔滨工程大学水声工程学院, 哈尔滨 150001; 2. 哈尔滨工程大学水声技术重点实验室, 哈尔滨 150001; 3. 海军大连舰艇学院军事海洋系, 大连 116018
基金项目:国家自然科学基金(批准号:61271443,61471378)资助的课题.
摘    要:水面水下目标分辨与识别一直是被动声呐探测领域的难题.利用一种水平阵模态域波束形成算法获得己知方位目标声源的各阶模态强度,将其与不同深度的各阶参考模态强度进行匹配,最终实现了对声源的深度估计.仿真结果表明,该算法可以在信噪比为-10 dB的情况下,用300Hz带宽的信号样本,实现对声源深度的有效估计.系统分析了不同参数和不同波导条件对该方法目标深度估计性能的影响.其中,阵元数越多,模态样本数越多,计算频段越宽,方位估计精度越高,有效阵长越长,深度估计的性能越好.阵元间距和波导深度的变化不会影响该方法的深度估计性能,并且该方法的深度估计性能在声速剖面、海底参数等波导条件存在扰动时具有鲁棒性.

关 键 词:简正波  模态域波束形成  目标深度估计
收稿时间:2016-06-27

A modal domain beamforming approach for depth estimation by a horizontal array
Li Peng,Zhang Xin-Hua,Fu Liu-Fang,Zeng Xiang-Xu.A modal domain beamforming approach for depth estimation by a horizontal array[J].Acta Physica Sinica,2017,66(8):84301-084301.
Authors:Li Peng  Zhang Xin-Hua  Fu Liu-Fang  Zeng Xiang-Xu
Institution:1. School of Underwater Acoustic Engineering, Harbin Engineering University, Harbin 150001, China; 2. Acoustic Science and Technology Laboratory, Harbin Engineering University, Harbin 150001, China; 3. Department of Military Oceanography, Dalian Navy Academy, Dalian 116018, China
Abstract:Distinguishing and recognizing water targets and underwater targets has been the focus of passive sonar detection. The depth of the target is closely related to the physical characteristics of the signal. In the shallow water waveguide, the normal mode theory can be used to give a good explanation to the acoustic signal physical properties. In this paper, a new method of beam forming in horizontal array modal domain is proposed. Under the condition of predicting target azimuth, the difference in acoustic path between the horizontal array elements corresponding to the direction of the target signal can be calculated according to the azimuthal information, and the phase delay of each normal mode component of the acoustic signal can be obtained. The horizontal wave number varies with order of normal mode, so each order of the normal mode has a specific phase delay. By using the beam forming principle, when the phase of a certain order of normal mode is compensated for, the output of the superposition of the signal on each element is the modal intensity of the normal mode. After obtaining the target signal modal intensity of each order, based on the shallow water condition, the modal intensities of sound source excitation at different depths are obtained as the reference mode intensities of the sound source at corresponding depths in the shallow water waveguide by simulating on Kracken software. Then, calculating the correlation coefficient between the target signal modal intensity of each order and the reference modal intensity of the sound source at each depth, we search for the maximum value of the correlation coefficient. The reference depth corresponding to the maximum value of the correlation peak is the estimated value of the target depth calculated by the method. Based on physical causes and characteristics of the normal modes, in this paper, the influences of the parameters such as the element number of horizontal array, depth of receiving array, signal-to-noise ratio, velocity profile, waveguide depth, azimuthal estimation accuracy, effective array length and application frequency band on the performance of this method are analyzed. The simulation results show that the algorithm can estimate the depth of the sound source effectively by using the signal sample with a bandwidth of 300 Hz when the signal-to-noise ratio is -10 dB. The wider the frequency band, the longer the effective array length, and the more the array element number, the higher the accuracy of azimuth estimation will be, which will bring beneficial effects to the depth estimation with the method. In addition, the depth estimation performance of the proposed method is still robust when the waveguide conditions such as the velocity profile and the seafloor parameters are disturbed.
Keywords:normal mode wave  modal domain beamforming  depth estimation
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