摘要
针对无人机室内定位问题,提出一种WIFI指纹定位与多传感器融合的定位方法。分析三维空间的WIFI指纹定位方法应用于无人机定位的难点,利用超声波传感器测量的无人机高度信息将定位匹配范围缩减至邻近的两个层面,提升WIFI定位的速度;设计卡尔曼滤波器,将WIFI定位结果作为卡尔曼滤波器预测阶段的输入,通过融合惯性传感器信息得到更准确的无人机位置估计,采用数据拟合的方法对定位结果进一步优化。仿真结果表明,该定位方法可实现无人机室内定位,有良好的定位速度和精度。
Aiming at the problem of UAV indoor positioning,a positioning method based on WIFI fingerprint positioning and multi-sensor fusion was proposed.The difficulty of applying the three-dimensional WIFI fingerprint positioning method to UAV positioning was analyzed.The UAV height information measured by the ultrasonic sensor was used to reduce the positioning matching range to two adjacent levels,which improved the speed of WIFI positioning.A Kalman filter was designed,the WIFI positioning result was used as the input of the Kalman filter prediction stage,a more accurate UAV position estimation was obtained by fusing the inertial sensor information,and the positioning result was further optimized using the method of data fitting.The simulation results show that the positioning method can realize the UAV indoor positioning,and has good positioning speed and accuracy.
作者
景晓娟
曹以龙
景旭川
JING Xiao-juan;CAO Yi-long;JING Xu-chuan(College of Electronics and Information Engineering,Shanghai University of Electric Power,Shanghai 201306,China)
出处
《计算机工程与设计》
北大核心
2021年第12期3569-3575,共7页
Computer Engineering and Design
基金
上海市科技创新行动计划基金项目(19DZ1205402)。
