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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。
In the case of horizontal and non-uniform shallow sea environment, the change of sound velocity profile will affect the sound field when moving sound source is tracked. A sound velocity profile tracking inversion and moving sound source tracking positioning based on ensemble Kalman filter algorithm method. First of all, the sound velocity profile is parametrically expressed in terms of distance and depth so that the tracking of the sound velocity profile is transformed into the third-order empirical orthogonal function coefficients of the sound velocity profile. Secondly, by means of representing the sound source state information and sound velocity profile information As the state variable, the sound field information received by the vertical line array is used as the measurement value to establish the state-measurement model, and then the state variables of the model are tracked by the method of ensemble Kalman filter. The simulation results show that the root mean square error of the acoustic velocity profile tracking inversion and the absolute error of the moving sound source tracking and positioning are very small, and the tracking and positioning accuracy to the sound source is very high. And by increasing the number of set samples, increasing the signal-to-noise ratio of the received signal and increasing the number of receiving elements, the accuracy of the tracking positioning result can be improved. Finally, the method is validated using the East China Sea experimental data.