摘要
针对室内无人机的跟踪定位问题,提出一种基于超声波测距和多普勒测速的跟踪定位算法(TLUD)。TLUD算法通过估计超声波信号到达接收端的到达时间差,估计声源离接收端的距离(测距),并利用多普勒效应估计无人机移动的速度(测速)。再利用卡尔曼滤波算法,并结合测距和测速数据,修正测距数据。最后,利用泰勒级数展开的最小二乘法估计无人机位置,实现对无人机的跟踪。仿真结果表明,该算法在室内环境的平均定位误差约为0.55 cm。
Aiming at the tracking and localization problem of indoor unmanned aerial vehicles(UAV),a tracking and positioning algorithm(TLUD)based on ultrasonic ranging and Doppler velocity measurement is proposed.The TLUD algorithm estimates the time of arrival of the ultrasonic signal to the receiving end and the distance between the sound source and the receiving end,and uses Doppler effect to estimate the mobile speed of UAV.Then,Kalman filtering algorithm is used to modify the ranging data by combining ranging and velocity measurement data.Finally,the least square method of Taylor series expansion is used to estimate the UAV position,and the UAV tracking is realized.Simulation results show that the average positioning error of the proposed TLUD algorithm in indoor environment is about 0.55 cm.
作者
黄婷
徐明
HUANG Ting;XU Ming(Nanchang Campus Information Center of Jiangxi Vocational College of Finance and Economics,Nanchang 331700,China)
出处
《弹箭与制导学报》
北大核心
2021年第3期105-108,114,共5页
Journal of Projectiles,Rockets,Missiles and Guidance
关键词
无人机
室内定位
到达时间差
多普勒测速
卡尔曼滤波
unmanned aerial vehicles
indoor localization
time differrence of arrival
Doppler velocimetry
Kalman filtering
