三轴MEMS加速度计的最大似然校正算法

加速度计是惯性导航系统的重要测量元件,而由于制造工艺及各类传感器误差,低成本加速度计很难达到要求的精度,因此需要对其进行校正。提出一种基于最大似然估计的加速度计自校正算法。综合考虑加速度计零偏、比例误差、非正交误差、安装误差与测量噪声,建立了传感器误差模型。在此基础上,将加速度校正问题转化为校正参数的最大似然估计问题。通过数值仿真和实测试验验证,表明算法具有较高的参数估计精度,能够有效地对上述因素引起的误差进行校正。

Maximum likelihood calibration for MEMS triaxial accelerometer

Development of Micro-electromechanical System (MEMS) technology has lead to low cost sensors being widely used in both military and commercial fields. Accelerometer is one of the fundamental measurement units of inertial navigation system (INS). It is difficult to meet the precision requirement for low-cost sensors due to the manufacturing process and all kinds of sensor errors. Calibration for accelerometer is essential before being used. This paper establishes the sensor errors model by taking comprehensive consideration of zero bias, scale errors non-orthogonal errors, installation errors and measurement noise of the accelerometer, based on which the calibration problem of accelerometer is transformed into maximum likelihood estimation (MLE) problem of calibration parameters. The self-calibration algorithm based on maximum likelihood Estimation is tested by both numerical simulation and real data experiment. The result shows the MLE algorithm has a high precision of parameters estimation which can calibrate the errors caused by factors mentioned above effectively.