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基于变量状态维数卡尔曼滤波的惯性和磁传感器姿态确定方法。

Variable-State-Dimension Kalman-based Filter for orientation determination using inertial and magnetic sensors.

机构信息

The BioRobotics Institute, Scuola Superiore Sant'Anna, Piazza Martiri della Libertà 33, Pisa 56127, Italy.

出版信息

Sensors (Basel). 2012;12(7):8491-506. doi: 10.3390/s120708491. Epub 2012 Jun 25.

Abstract

In this paper a quaternion-based Variable-State-Dimension Extended Kalman Filter (VSD-EKF) is developed for estimating the three-dimensional orientation of a rigid body using the measurements from an Inertial Measurement Unit (IMU) integrated with a triaxial magnetic sensor. Gyro bias and magnetic disturbances are modeled and compensated by including them in the filter state vector. The VSD-EKF switches between a quiescent EKF, where the magnetic disturbance is modeled as a first-order Gauss-Markov stochastic process (GM-1), and a higher-order EKF where extra state components are introduced to model the time-rate of change of the magnetic field as a GM-1 stochastic process, namely the magnetic disturbance is modeled as a second-order Gauss-Markov stochastic process (GM-2). Experimental validation tests show the effectiveness of the VSD-EKF, as compared to either the quiescent EKF or the higher-order EKF when they run separately.

摘要

本文提出了一种基于四元数的变维扩展卡尔曼滤波器(VSD-EKF),用于使用惯性测量单元(IMU)与三轴磁传感器集成的测量值来估计刚体的三维姿态。通过将陀螺偏置和磁干扰包含在滤波器状态向量中,对其进行建模和补偿。VSD-EKF 在静态 EKF 和更高阶 EKF 之间切换,其中磁干扰被建模为一阶高斯-马尔可夫随机过程(GM-1),而额外的状态分量被引入到更高阶 EKF 中,以将磁场的时变率建模为 GM-1 随机过程,即磁干扰被建模为二阶高斯-马尔可夫随机过程(GM-2)。实验验证测试表明,与单独运行的静态 EKF 或更高阶 EKF 相比,VSD-EKF 是有效的。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0bff/3444060/34cd424038ab/sensors-12-08491f1.jpg

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