文章摘要
何百岳,张文安.基于无逆Kalman滤波器的姿态估计算法[J].高技术通讯(中文),2021,31(10):1027~1036
基于无逆Kalman滤波器的姿态估计算法
Inverse free Kalman filtering approach for orientation estimation
  
DOI:10.3772/j.issn.1002-0470.2021.10.003
中文关键词: 磁-惯性传感单元(MIMU); 姿态估计; 单位四元数; 无逆Kalman滤波器(IFKF); 严重干扰拒绝(SDR)
英文关键词: magnetic/inertial measurement unit (MIMU), orientation estimation, unit quaternion, inverse free Kalman filter (IFKF), severe disturbance rejection (SDR)
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作者单位
何百岳  
张文安  
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中文摘要:
      研究了一种基于磁-惯性传感单元(MIMU)的采用无逆Kalman滤波器(IFKF)的姿态估计算法。该方法将运动分为稳定和运动两种状态。针对稳定状态,该算法使用了稳态策略。这种状态下,估计器利用之前时刻的估计值和预测协方差,从而达到既降低运算量,又有效缓解磁场变化带来的姿态偏移和陀螺仪数值积分漂移的目的。另一方面,在动态策略中,严重干扰拒绝方法(SDR) 被用于缓解瞬时干扰。同时,无逆Kalman滤波器被用于融合磁-惯性传感单元的数据,有效避免矩阵的求逆运算,由此减轻计算负担。实验结果证明,所提出的方法在有效减少计算时间的同时维持了较高的姿态估计精度。
英文摘要:
      A novel orientation estimation approach with inverse free Kalman filter (IFKF) is proposed by using magnetic/inertial measurement unit (MIMU). The approach separates the motion into two states, including static state and dynamic state. A static strategy is presented for orientation estimation in the static state. In this state, the estimator utilizes the previous estimate and predicts the covariance, which reduces the computation time and overcomes the magnetic disturbance as well as the integration drift. On the other hand, in the dynamic state, a severe disturbance rejection method (SDR) is employed to alleviate the negative effects of temporary disturbance. Meanwhile, the IFKF is capitalized to improve estimation efficiency by replacing the exact inverse of the innovation covariance matrix with an approximate inverse. Experiments on a body tracking system are presented to demonstrate the effectiveness of the proposed approach.
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