基于变维卡尔曼滤波的UUV目标运动优化估计方法

为实现无人水下航行器精准、安全的跟踪目标从而高效地实现目标的信息采集,提出了一种针对该个体的目标运动优化估计方法。此方法通过建立目标运动模型,基于卡尔曼滤波基本原理,利用变维卡尔曼滤波的方法,达到UUV个体对目标运动状态准确估计的预期效果。为提高该方法的可行性,在利用最小化目标位置估计协方差矩阵完成目标运动轨迹估计及优化的过程中,考虑实际UUV机动时的最大速度限制、与目标最小距离的限制。文章详细阐述该方法的实现和步骤,并通过仿真实验验证了该优化算法的有效性。

An Optimized Method of Target Motion Estimation for UUV Based on Variable Kalman Filter

In order to achieve an accurate, safe and efficient way of tracking the target for Unmanned Underwater Vehicle (UUV) to collect information, it proposed an optimization of target motion estimation method for the individual. By establishing target motion model and the use of variable Kalman filtering, it achieved the expected results of accurate estimates. To improve the feasibility of the method, it adapted minimized target position estimate covariance matrix to realize target trajectory estimation and optimization. At the same time, it took the limit of maximum speed of UUV and the minimum distance to the moving target into consideration. It elaborated specific methods and steps of this method, and proved the effectiveness of the optimization algorithm by simulation.