用自适应扩展卡尔曼滤波跟踪水下目标的算法研究

针对短基线声纳系统跟踪水下目标的问题，建立了状态方程和观测方程，提出了一种自适应扩展卡尔曼滤波的跟踪算法，该算法包含八个基本步骤。将声波传输时延转换为水下目标的距离，用卡尔曼滤波的方法对数据中的噪声进行滤波。对目标的匀速航行和机动航行进行了仿真实验，实验结果表明了该算法的正确性和有效性。最后将该算法用于水下目标的实测数据，收到了良好的效果。

Adaptive Extended Kalman Filter for Underwater Target Tracking

The underwater target tracking problem is investigated in a short-base line sonar system. Based on the state and observation equations, it proposes an approach of adaptive extended Kalman filter, which consists of eight steps. Signal time delay is converted to underwater distance, and noise is filtered out with Kalman filter. The approach is evaluated with simulations where the target is at either regular or flexible speed. Also it is tested with real datasets. The results from the experiments confirm the effectiveness of the approach.