An extended Kalman filter with adaptive gain was used to build a miniature attitude and heading reference system based on a stochastie model. The adaptive filter has six states with a time variable transition matrix. ...An extended Kalman filter with adaptive gain was used to build a miniature attitude and heading reference system based on a stochastie model. The adaptive filter has six states with a time variable transition matrix. When the system is in the non-acceleration mode, the accelerometer measurements of the gravity and the compass measurements of the heading have observability and yield good eslimates of the states. When the system is in the high dynamic mode and the bias has converged to an aceurate estimate, the attitude caleulation will be maintained for a long interval of time. The adaptive filter tunes its gain automatically based on the system dynamics sensed by the accelerometers to yield optimal performance,展开更多
MEMS （micro electro mechanical systems） inertial navigation system ~, Mll＇~3） nas Been WllUly used in robots for its low-cost. The MINS and magnetometers are commonly the component parts of the attitude and headin...MEMS （micro electro mechanical systems） inertial navigation system ~, Mll＇~3） nas Been WllUly used in robots for its low-cost. The MINS and magnetometers are commonly the component parts of the attitude and heading reference systems （AHRS）, which provide pitch and roll angles relative to the earth gravity vector, and heading angle relative to the north. However, the performance of sen- sors with low cost AHRS is not so good. The gyros are not sensitive enough to observe the earth an- gular velocity, so the traditional technique like alignment algorithm is invalid. The measurements of gyros become useless to determine the initial attitude matrix from navigation frame to body frame. The alignment algorithm is computed by the accelerometers and magnetometers. The process is es- tablished as an optimization problem of finding the maximum eigenvector. Meanwhile the sensitive analysis with respect to the biases of accelerometers is proposed. Then the recursive least squares al- gorithm （RLSA） is introduced. The comparison between the proposed method and RLSA is provid- ed. The results demonstrate its accuracy favorably and verify the feasibility of the proposed algo- rithm.展开更多
This article proposes a new inner attitude integration algorithm to improve attitude accuracy of the strapdown inertial attitude and heading reference system （SIAHRS） , which, by means of a Kalman filter, integrates...This article proposes a new inner attitude integration algorithm to improve attitude accuracy of the strapdown inertial attitude and heading reference system （SIAHRS） , which, by means of a Kalman filter, integrates the calculated attitude from the accelerometers in inertial measuring unit （IMU） , called damping attitudes, with those from the conventional IMU. As vehicle＇ s acceleration could produce damping attitude errors, the horizontal outputs from accelerometers are firstly used to judge the vehicle＇ s motion so as to determine whether the damping attitudes could be reasonably applied. This article also analyzes the limitation of this approach. Furthermore, it suggests a residual chi-square test to judge the validity of damping attitude measurement in real time, and accordingly puts forward proper information fusion strategy. Finally,the effectiveness of the proposed algorithm is proved through the experiments on a real system in dynamic and static states.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
文摘An extended Kalman filter with adaptive gain was used to build a miniature attitude and heading reference system based on a stochastie model. The adaptive filter has six states with a time variable transition matrix. When the system is in the non-acceleration mode, the accelerometer measurements of the gravity and the compass measurements of the heading have observability and yield good eslimates of the states. When the system is in the high dynamic mode and the bias has converged to an aceurate estimate, the attitude caleulation will be maintained for a long interval of time. The adaptive filter tunes its gain automatically based on the system dynamics sensed by the accelerometers to yield optimal performance,
基金Supported by the National Natural Science Foundation of China(No.60905056)
文摘MEMS （micro electro mechanical systems） inertial navigation system ~, Mll＇~3） nas Been WllUly used in robots for its low-cost. The MINS and magnetometers are commonly the component parts of the attitude and heading reference systems （AHRS）, which provide pitch and roll angles relative to the earth gravity vector, and heading angle relative to the north. However, the performance of sen- sors with low cost AHRS is not so good. The gyros are not sensitive enough to observe the earth an- gular velocity, so the traditional technique like alignment algorithm is invalid. The measurements of gyros become useless to determine the initial attitude matrix from navigation frame to body frame. The alignment algorithm is computed by the accelerometers and magnetometers. The process is es- tablished as an optimization problem of finding the maximum eigenvector. Meanwhile the sensitive analysis with respect to the biases of accelerometers is proposed. Then the recursive least squares al- gorithm （RLSA） is introduced. The comparison between the proposed method and RLSA is provid- ed. The results demonstrate its accuracy favorably and verify the feasibility of the proposed algo- rithm.
基金Aeronautical Science Foundation of China(20080852011,20070852009)
文摘This article proposes a new inner attitude integration algorithm to improve attitude accuracy of the strapdown inertial attitude and heading reference system （SIAHRS） , which, by means of a Kalman filter, integrates the calculated attitude from the accelerometers in inertial measuring unit （IMU） , called damping attitudes, with those from the conventional IMU. As vehicle＇ s acceleration could produce damping attitude errors, the horizontal outputs from accelerometers are firstly used to judge the vehicle＇ s motion so as to determine whether the damping attitudes could be reasonably applied. This article also analyzes the limitation of this approach. Furthermore, it suggests a residual chi-square test to judge the validity of damping attitude measurement in real time, and accordingly puts forward proper information fusion strategy. Finally,the effectiveness of the proposed algorithm is proved through the experiments on a real system in dynamic and static states.
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。
