动态威胁环境下单无人机测向定位航迹优化算法

为解决单架无人机在动态战场环境下的测向定位问题,提出了一种基于动态窗口法的单机测向定位航迹优化算法。以最大化Fisher信息矩阵行列式为测向定位评价准则,在由动态探测雷达和静/动障碍构成的动态战场环境中,基于动态窗口法思想,将测向定位航迹优化评价准则由传统的单步最优原则扩展到对多步预测航迹的评价,同时考虑雷达探测和静/动障碍环境对预测航迹的影响,通过滚动时域方法控制无人机最优航向。仿真结果表明,所提方法能够使无人机在有效逃避雷达探测威胁以及规避环境中静/动障碍的条件下保证对目标的高精度测向定位,为解决动态战场环境下的单架无人机测向定位问题提供了新思路。

Trajectory optimization of single UAV for bearing-only target localization in dynamic threats

In order to solve the problem of bearing-only target location for single unmanned aerial vehicle in the dynamic battlefield environment, a new trajectory optimization algorithm based on dynamic window approach was proposed. The maximizing determinant of the Fisher information matrix was set as the trajectory criterion. In the dynamic battlefield, which consisted of dynamic detection radar and fixed/moving obstacles the criterion, based on the idea of dynamic window approach, was extended from the traditional single-step optimal principle to the evaluation of multi-step predicted trajectory. At the same time, the effects of the detection radar and fixed/moving obstacles on the predicted trajectory were also considered. The optimal heading of unmanned aerial vehicle was chosen by the moving horizon method. And the numerical simulations show that the algorithm enables the unmanned aerial vehicle to ensure the high-precision bearing-only target localization under the condition of effectively avoiding the radar threat and fixed/moving obstacles, which provides new ideas for solving the problem of single unmanned aerial vehicle bearing-only target localization in a dynamic battlefield environment.