主动声呐目标实时航迹解算算法仿真研究

Simulation Research on Real-time Target Trajectory Solution Algorithm for Active Sonar

摘要:

由于水中声速较低,主动声呐完成量程范围的探测往往需要花费几秒甚至几十秒的时间,这个时间即为主动声呐的扫描周期。 主动声呐对目标的搜索、跟踪等处理都是按扫描周期进行的,目标信息刷新率较低,其上报系统进行目标诸元解算时同样具有这一特点。 为了提高声呐效能及系统解算效率,提出了一种无迹卡尔曼滤波(UKF) 与野值剔除相结合的目标实时航迹解算算法:首先在以声呐扫描周期为间隔获取的目标信息基础上,采用 UKF 预测出目标每秒方位、距离信息,并对野值点进行处理,实时地调整滤波增益或者进行野值计算,最后利用目标的位置信息解算出目标每秒的航速和航向信息。 通过目标在不同航向、 航速下的仿真实验,验证了本文算法的有效性和正确性。

关键词:无迹卡尔曼滤波;航迹解算;目标信息;野值

Abstract:

Due to the low speed of sound in water, it takes several seconds or even tens of seconds for the active sonar to complete the detection of the range. Which is the scanning cycle of the active sonar. As active sonar conduct activities, including searching, tracking of target, etc. , in terms of scanning cycles, its update rate is low and its reporting system has the same feature when it resolves the target's elemants. For the improvement of sonar performance and the efficiency of the system’s visual interpretation, this paper proposes a real-time target trajectory solving algorithm that combines unscented Kalman filter (UKF) and outlier elimination. The algorithm first uses UKF to predict the target’s azimuth and distance information per second on the basis of the target information acquired at the interval of the sonar scanning cycle, and then adjusts the filter gain or performs outlier calculation in real time according to the outlier processing, and finally uses the location information of the target to solve the target speed and heading information per second. The simulation experiment of the target under different headings and speeds is carried out to verify the validity and correctness of the proposed algorithm.

Key words:unscented Kalman filtering; trajectory solution; target information; outlier