基于卡尔曼滤波的无人机目标跟踪系统

Target tracking system of UAV based on Kalman Filter

四旋翼无人机目前被广泛应用于民用或是军事领域。由于其灵活小巧且轻盈的优点,能代替人类探索未知地域或执行各种危险任务,如地形勘察、探取情报、目标跟踪等,而精确可靠的目标跟踪算法更是在无人机领域获得了广泛的应用。本文针对运动目标跟踪问题,将经典的卡尔曼滤波应用于跟踪算法中,对目标的运动行为进行状态预估,预测目标参数,对于目标被遮挡或者丢失的情况具有良好的跟踪效果。通过实验进行跟踪仿真表明:该算法提高了目标跟踪的稳定性、快速性和精确性,能够获得良好的跟踪效果。

Four-rotor UAV is widely used in civil and military fields. Small and light,it can take the place of humans in exploring unknown regions or performing dangerous tasks. Such as terrain survey,information retrieval,target tracking,etc. The precise and reliable target tracking algorithm has been widely used in the field of UAV. This paper aims at the problem of moving target tracking. The classical Kalman Filter is applied to the tracking algorithm. State estimation is carried out on the motion behavior of the target and the target parameters are predicted. It has good tracking effect when the target is blocked or lost. And through the experiment to carry on the tracking simulation research. Experiments show that the algorithm improves the stability,rapidity and accuracy of target tracking. The algorithm can get good tracking results.