基于卡尔曼滤波的水下近距目标运动分析

Target Motion Analysis of Underwater Short-distance Target Based on Kalman Filter

为跟踪水下近距目标,设计采用被动声纳平台获得目标的方位数据,用扩展卡尔曼滤波算法对测量数据进行目标运动分析来实现.建立了目标相对观测平台在固定深度做直线运动时的理论模型,针对非线性测量方程,采用雅可比矩阵来近似处理.采用标准卡尔曼滤波进行了实例仿真.结果表明,该方法将估计误差控制在8%以下,并有较好的稳定性.

In order to track underwater short-distance target, the method based on the combination of passive sonar and extended Kalman filter was proposed. By passive sonar, the Direction of Arrival （DOA） estimation of the target was obtained. The measurement results of sonar were analyzed using the Kalman filter, and target motion analysis was realized. The theoretical model was established, which was about moving target with rectilinear motion at constant depth relative to observation stand. Aiming at nonlinear measure equation of theoretical model, the approximate method with Jocabi matrix was introduced. The instance simulation on basis of Kalman filter was carried out. The simulation and experiment results show that the error of algorithm can be steadily controlled within 8% by the method.