基于Kalman滤波器的无人机高度融合方法  

A UAV Altitude Fusion Method Based on Kalman Filter

作　　者：党兵兵 武耀发 豆毅庚 高鹏 王威 DANG Bingbing;WU Yaofa;DOU Yigeng;GAO Peng;WANG Wei(Xi'an ASN Technology Group Co.,Ltd.,Xi'an 710065)

机构地区：[1]西安爱生技术集团有限公司,西安710065

出　　处：《火控雷达技术》2024年第4期47-50,60,共5页Fire Control Radar Technology

摘　　要：在无人机起飞、降落及定高飞行控制中,针对单一高度传感器测量精度低、稳定性差、易受干扰,难以适应不同的飞行场景等问题,提出了基于Kalman滤波器的多传感器高度融合方法。首先建立了无人机高度状态方程和传感器观测模型,然后利用北斗、气压计和加速度计设计了基于STM32H753的多余度航姿测量单元,最后通过软件递归的方式对高度信息进行预测和更新,得到最优的测量结果。仿真结果表明,该方法测量精度更高、稳定性更好、鲁棒性更强,可以满足无人机在不同场景下的飞行控制要求。In the takeoff,landing,and fixed-altitude flight control of unmanned aerial vehicles(UAVs),single altitude sensor often suffers from low measurement accuracy,poor stability,and susceptibility to interference,making it difficult to adapt to various flight scenarios.To address these issues,a multi-sensor altitude fusion method based on the Kalman filter is proposed.Firstly,the UAV altitude state equation and sensor observation model are established.Then,a redundant attitude measurement unit based on STM32H753 is designed by using BeiDou navigation equipment,barometer,and accelerometer.Finally,altitude information is predicted and updated through software recursion,resulting in optimal measurement outcomes.The simulation results show that the proposed method has higher measurement accuracy,better stability,and higher robustness.It can meet the flight control requirements of UAVs in different scenarios.

关 键 词：无人机 高度测量 信息融合 KALMAN滤波器 STM32 

分 类 号：TN95[电子电信—信号与信息处理] TP212[电子电信—信息与通信工程]