浅海声速剖面与移动声源的跟踪定位

发布时间：2018-02-26 07:11

本文关键词： 跟踪定位均方根误差卡尔曼滤波算法声场分布阵元数目经验正交函数线列阵定位精度信号信噪比卡尔曼滤波方法 　出处：《声学学报》2017年01期 　论文类型：期刊论文

【摘要】：在水平非均匀分布的浅海环境中,针对移动声源跟踪时,声速剖面的变化会对声场产生影响,提出了一种利用集合卡尔曼滤波算法的声速剖面跟踪反演和移动声源跟踪定位的方法。首先,将声速剖面进行距离和深度的参数化表示,从而将对声速剖面的跟踪转化为对声速剖面前3阶经验正交函数系数的跟踪;其次,通过将声源状态信息和声速剖面信息表示为状态变量,而将垂直线列阵接收到的声场信息作为测量值建立状态-测量模型,然后利用集合卡尔曼滤波方法对模型状态变量进行跟踪。仿真结果得出:声速剖面跟踪反演的均方根误差和移动声源跟踪定位的绝对误差都非常小,对声源的跟踪定位精度很高。并且通过增加集合样本数、增加接收信号信噪比以及增加接收阵元数目都可以提高跟踪定位结果精度。最后,利用东海实验数据对本方法进行了验证。
[Abstract]:In the shallow water environment with horizontal non-uniform distribution, the change of sound velocity profile will affect the sound field when the moving sound source is tracked. A method of acoustic profile tracking inversion and moving sound source tracking based on set Kalman filter algorithm is proposed. Firstly, the sound velocity profile is parameterized for distance and depth. Thus, the tracking of the sound velocity profile is transformed into the tracking of the first three order empirical orthogonal function coefficients of the sound velocity profile. Secondly, the sound source state information and the sound velocity profile information are expressed as state variables. Taking the sound field information received by the vertical linear array as the measurement value, the state-measurement model is established. The simulation results show that the root mean square error of acoustic profile tracking inversion and the absolute error of moving sound source tracking location are very small. The tracking accuracy of sound source is very high, and the accuracy of tracking and localization can be improved by increasing the number of samples, increasing the SNR of received signal and increasing the number of receiving array elements. The experimental data of the East China Sea are used to verify this method.
【作者单位】：西北工业大学海洋声学信息感知工业和信息化部重点实验室;西北工业大学航海学院;
【基金】：国家自然科学基金项目(11174235)资助
【分类号】：P733.2

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