基于Tiny-YOLOV3的无人机地面目标跟踪算法设计

Ground Target Tracking Algorithm Design of UAV Based on Tiny- YOLOV3

摘要:

为了提高四旋翼无人机对地面目标跟踪的稳定性和跟踪精度，提出了一种结合Tiny-YOLOV3和卡尔曼滤波的跟踪算法。首先分析了Tiny-YOLOV3的原理和网络结构，并基于Tiny-YOLOV3的目标检测结果，结合无人机状态和目标的几何关系建立了目标跟踪系统的数学模型；接着对目标相对运动关系进行分析，建立目标的运动学模型，考虑到目标检测结果受干扰影响较大，应用卡尔曼滤波器实现对目标轨迹的滤波和预测，进而提升目标跟踪的精度；最后根据经过卡尔曼滤波后的目标轨迹信息设计无人机控制律，在轨迹控制的同时引入对无人机偏航角的控制，从而实现无人机对目标的稳定跟踪。仿真结果表明无人机对目标的位置跟踪精度在0.5m以内，速度跟踪误差在0.2m/s以内，偏航角跟踪误差在3度以内，跟踪效果良好，从而论证了所提算法的有效性。

Abstract:

In order to improve the stability and tracking accuracy of the quadrotor UAV to the ground target, a tracking algorithm combining Tiny-YOLOV3 and Kalman filter is proposed. Firstly, the principle and network structure of Tiny-YOLOV3 are analyzed, and based on the target detection results of Tiny-YOLOV3, the mathematical model of target tracking system is established by combining the state of UAV and the geometric relationship of target; Then, the relative motion relationship of target is analyzed, and the kinetic model of target is established, considering that the detection result is greatly affected by interference, Kalman filter is applied to filter and predict the target trajectory, so as to improve the accuracy of target tracking. Finally, the UAV control law is designed according to the target trajectory information after Kalman filtering, at the same time, the yaw angle control of UAV is introduced to realize the UAV's stable tracking to the target. The simulation results show that the position tracking accuracy of UAV to target is within 0.5 m, the velocity tracking error is within 0.2 m/s, and the yaw angle tracking error is within 3 degrees, the tracking effect is good, which proves the effectiveness of the proposed algorithm.