MEMS惯性测量组合初始标定方法研究

Initial Calibration of MEMS Inertial Measurement Unit

为了降低MEMS惯性测量组合(IMU)的测试成本,提出一种借助于机器视觉技术标定MEMS惯性测量组合的方法。综合考虑了3个加速度计和3个陀螺仪的标定因数、零偏误差和安装方位误差因素的影响,建立了IMU数学模型。在外力的推动下,悬挂于2个屏幕之间的IMU作不规则运动,安装在IMU上的2根准直激光束在屏幕上生成4个指示光斑。借助于双目三维重构技术测量指示光斑在世界坐标系内的坐标,然后应用欧拉角算法确定载体坐标系相对于世界坐标系的旋转角速度向量和线加速度向量。求解IMU数学模型,确定模型中的待定参数。实验结果表明:该文给出的方法可以准确测量载体坐标系相对于世界坐标系的旋转角速度向量和线加速度向量。

To decrease the cost of calibrating MEMS inertial measurement unit （IMU）, this paper proposes an approach to calibrating MEMS IMU by means of machine vision technique. Mathematical models are derived from the thre.e aeeelerometers and three rate gyros, taking into account the sensor axis misalignments, scale factors, and biases. Driven by external force, the IMU flies randomly between two screens. The collimated laser beams mounted on the plate of IMU produce four indicative spots on the screens. The coordinates of the indicative spots in the world coordinate system are measured by using binocular stereo reconstruction algorithm, and then the angular rate vector and acceleration vector of the body frame with respect to the world frame are determined by using Euler algorithm. Given this kinematics information, the calibration parameters of the mathematical models are solved by using least squares algorithm. The experimental results show that the angular rate vector and acceleration vector of the body frame with respect to the world frame can be determined accurately.