基于最优三维卡尔曼滤波与萤火虫算法的巡航导弹目标轨迹运动预测
Cruise Missile Target Trajectory Movement Prediction based on Optimal 3D Kalman Filter with Firefly Algorithm
AI总结：
本文提出一种结合LQR控制器与三维卡尔曼滤波的预测方法，利用萤火虫算法优化路径，以提高巡航导弹轨迹预测的准确性与稳定性。
摘要：
尽管世界和平是愿望，但战争中各国的防御需求包括用于破坏和防御的导弹。如今，导弹从起点到终点的运动是战争中重要的问题，因为导弹的射程从低到高不等。参数不确定性是导弹运动预测和轨迹中的几个因素，如速度、运动角度、精度、运动时间、情况和直接控制。因此，本研究试图提供一种基于LQR控制器与三维卡尔曼滤波的方法，然后设定运动并指定路径，以避免偏差，基于萤火虫算法。通过MATLAB环境模拟和巡航导弹的图形显示，期望能够获得适当的评估结果。
英文摘要：
It is hoped that there will never be a war in the world, but one of the defensive requirements of any country during the war is the missiles used for destruction and defense. Todays, missiles movement from origin to destination is an important problem due to abundant application of missiles in wars. This is important because of the range of some missiles is low and other are very high. Parametric indeterminacy are several factors in missile movement prediction and trajectory such as speed, movement angle, accuracy, movement time, and situation and direct control. So this research trying to provide a method based on LQR controller with 3d Kalman filter and then set motion and specify path without deviations based on Firefly Algorithm. It is expected that the results of an appropriate evaluation can be obtained by simulating the MATLAB environment and graphic display of a cruise missile.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
