利用STM32F103ZET丰富的接口搭建了基于ADIS1635x系列微电子机械系统陀螺航姿测量系统硬件平台,整个系统由小型无人机机载11.2V锂电池供电。在硬件平台基础上编写了STM32F103控制及读写ADIS16350的SPI程序以及与数传电台通信的串口程序...利用STM32F103ZET丰富的接口搭建了基于ADIS1635x系列微电子机械系统陀螺航姿测量系统硬件平台,整个系统由小型无人机机载11.2V锂电池供电。在硬件平台基础上编写了STM32F103控制及读写ADIS16350的SPI程序以及与数传电台通信的串口程序,完成了精确测量某小型无人机姿态的小型化航姿系统软硬件设计。最后,在小型固定飞行翼UAV上进行静动态测试,测得其航姿数据,并通过3DR Radio Telemetry数传电台将航姿数据传输到地面控制站电脑端进行显示和分析,为以后小型无人机自主飞行提供航姿参数。展开更多
针对传统的航姿系统(attitude and heading reference system,AHRS)在微型无人飞行器、机器人等应用上所体现的成本高、体积大、功耗大的问题,提出了一种低成本高精度AHRS。该系统以数字信号处理器为硬件平台,集成了陀螺仪、加速度计、...针对传统的航姿系统(attitude and heading reference system,AHRS)在微型无人飞行器、机器人等应用上所体现的成本高、体积大、功耗大的问题,提出了一种低成本高精度AHRS。该系统以数字信号处理器为硬件平台,集成了陀螺仪、加速度计、磁罗盘等9自由度微机电系统传感器,采用了基于四元数的姿态估计方法,建立了传感器输出模型和系统状态空间模型,考虑了加速度对系统精度的影响,解决了四元数协方差奇异性问题,通过扩展卡尔曼滤波器进行数据融合以获得姿态的准确输出。经数值仿真分析和三轴飞行转台测试,姿态角的静态精度优于0.5°、动态精度优于2°,并在微型无人飞行器上进行了飞行验证,结果表明其能够满足小型无人飞行器等的应用需求。展开更多
A current statistical model for maneuvering acceleration using an adaptive extended Kalman filter（CS-MAEKF） algorithm is proposed to solve problems existing in conventional extended Kalman filters such as large esti...A current statistical model for maneuvering acceleration using an adaptive extended Kalman filter（CS-MAEKF） algorithm is proposed to solve problems existing in conventional extended Kalman filters such as large estimation error and divergent tendencies in the presence of continuous maneuvering acceleration. A membership function is introduced in this algorithm to adaptively modify the upper and lower limits of loitering vehicles＇ maneuvering acceleration and for realtime adjustment of maneuvering acceleration variance. This allows the algorithm to have superior static and dynamic performance for loitering vehicles undergoing different maneuvers. Digital simulations and dynamic flight testing show that the yaw angle accuracy of the algorithm is 30% better than conventional algorithms, and pitch and roll angle calculation precision is improved by 60%.The mean square deviation of heading and attitude angle error during dynamic flight is less than3.05°. Experimental results show that CS-MAEKF meets the application requirements of miniature loitering vehicles.展开更多
文摘利用STM32F103ZET丰富的接口搭建了基于ADIS1635x系列微电子机械系统陀螺航姿测量系统硬件平台,整个系统由小型无人机机载11.2V锂电池供电。在硬件平台基础上编写了STM32F103控制及读写ADIS16350的SPI程序以及与数传电台通信的串口程序,完成了精确测量某小型无人机姿态的小型化航姿系统软硬件设计。最后,在小型固定飞行翼UAV上进行静动态测试,测得其航姿数据,并通过3DR Radio Telemetry数传电台将航姿数据传输到地面控制站电脑端进行显示和分析,为以后小型无人机自主飞行提供航姿参数。
文摘针对传统的航姿系统(attitude and heading reference system,AHRS)在微型无人飞行器、机器人等应用上所体现的成本高、体积大、功耗大的问题,提出了一种低成本高精度AHRS。该系统以数字信号处理器为硬件平台,集成了陀螺仪、加速度计、磁罗盘等9自由度微机电系统传感器,采用了基于四元数的姿态估计方法,建立了传感器输出模型和系统状态空间模型,考虑了加速度对系统精度的影响,解决了四元数协方差奇异性问题,通过扩展卡尔曼滤波器进行数据融合以获得姿态的准确输出。经数值仿真分析和三轴飞行转台测试,姿态角的静态精度优于0.5°、动态精度优于2°,并在微型无人飞行器上进行了飞行验证,结果表明其能够满足小型无人飞行器等的应用需求。
文摘A current statistical model for maneuvering acceleration using an adaptive extended Kalman filter（CS-MAEKF） algorithm is proposed to solve problems existing in conventional extended Kalman filters such as large estimation error and divergent tendencies in the presence of continuous maneuvering acceleration. A membership function is introduced in this algorithm to adaptively modify the upper and lower limits of loitering vehicles＇ maneuvering acceleration and for realtime adjustment of maneuvering acceleration variance. This allows the algorithm to have superior static and dynamic performance for loitering vehicles undergoing different maneuvers. Digital simulations and dynamic flight testing show that the yaw angle accuracy of the algorithm is 30% better than conventional algorithms, and pitch and roll angle calculation precision is improved by 60%.The mean square deviation of heading and attitude angle error during dynamic flight is less than3.05°. Experimental results show that CS-MAEKF meets the application requirements of miniature loitering vehicles.
