基于MARG的两种实时姿态测量算法的分析与比较

Analyzing and comparing of two different methods to compute the real-time orientation based on MARG

通过XENS采集MARG传感器的三维加速度,三维地磁场和三维角速度,用QUEST算法和Gauss-Newton算法计算姿态,并与原始姿态进行对比,分析2种算法的优劣。最后发现Gauss-Newton迭代算法能够用来计算与体坐标系中测量的加速度和地磁场相关的最优四元数。这个最优四元数送到扩展卡尔曼滤波中作为测量值。实验结果证实了滤波器设计的有效性,证明了利用惯性/磁性传感器模型能够实现实时人体运动跟踪。

Using the XENS to get the data of MARG 3-D Acceleration, 3-D local magnetic, 3-D angular rate, computing the orientation through two methods：QUEST algorithm and Gauss-Newton algorithm and comparing with the original orientation to see the advantages and disadvantages of these two methods. The Gauss-Newton iteration algorithm is utilized to find the best quaternion that relates the measured accelerations and earth magnetic field in the body coordinate frame. The best quaternion is used as part of the measurements for the Extensive Kalman filter. Experimental results validate the filter design, and show the feasibility of using inertial/magnetic sensor modules for real-time human body motion tracking.