基于机动检测的捷联航姿算法研究

Research on Algorithm for Strapdown Attitude Heading Reference System Based on Maneuver Detection

针对低精度陀螺仪、加速度计和磁传感器组成的捷联航姿系统存在的易受载体运动加速度影响而导致姿态精度下降甚至发散的问题进行了研究,提出了一种基于机动检测的捷联航姿算法。该算法根据陀螺仪数据进行姿态实时更新,利用加速度计和磁传感器输出对载体姿态误差进行校正以保持航姿输出的长期精度。算法根据加速度计输出在导航系中投影的水平分量进行机动检测,剔除机动期间的加速度数据,利用载体匀速运动状态下的加速度数据与磁传感器数据构造量测,利用卡尔曼滤波器对姿态误差进行估计并修正。仿真结果表明,该算法能有效完成载体机动检测,保证系统存在机动的情况下姿态精度满足应用要求。

The problem that attitude accuracy declines even diverges on the attitude heading reference system （AHRS） is investigated, which consists of low precision gyros, accelerometers and magnetometers. It is influenced by the acceleration of the moving carriers, and a AHRS algorithm based on maneuver detection is presented. The algorithm uses the output of gyros to update the attitude, and the output of accelerometers and magnetometers to adjust the attitude error for guaranteeing long-time precision. Algorithm uses the horizontal com- ponent of accelerometers, which are projected to navigation coordinate for maneuver detection. Then the ones during maneuver are eliminated. According to the output data of the accelerometers and the magnetometers under the condition of uniform motion, the measurement of the Kalman filter is made to rectify the attitude error. The simulation results show that the method is valid for maneuver detection. Furthermore, it can ensure the system attitude accuracy meet the application requirements of maneuver carriers.