A standard testing and calibration procedure for low cost MEMS inertial sensors and units
A standard testing and calibration procedure for low cost MEMS inertial sensors and units
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DOI：
10.1017/s0373463307004560
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发表时间：
2008-04-01
影响因子：
2.4
通讯作者：
El-Sheimy, N.
中科院分区：
文献类型：
--
作者：
Aggarwal, P.;Syed, Z.;El-Sheimy, N.
导航涉及估计移动对象的时变位置和姿态的方法和系统的集成。惯性导航系统(INS)和全球定位系统(GPS)是应用最广泛的导航系统。基于MEMS的惯性传感器的使用使GPS/INS组合导航系统变得更加经济实惠。然而，MEMS传感器受到各种误差的影响，必须对这些误差进行校准和补偿才能获得可接受的导航结果。此外，这些传感器的性能特性高度依赖于环境条件，如温度变化。因此，需要开发准确、可靠和高效的热模型，以减少这些误差的影响，这些误差可能会降低系统性能。本文利用Allan方差法对MEMS传感器中的噪声进行了表征。采用六位置定标法来估计确定性传感器误差，如偏差、比例因子和非正交性。提出了一种有效的热变化模型，并通过基于GPS和MEMS的组合惯性测量单元(IMU)的运动学货车试验研究了所提出的标定方法的有效性。
Navigation involves the integration of methodologies and systems for estimating the time varying position and attitude of moving objects. Inertial Navigation Systems (INS) and the Global Positioning System (GPS) are among the most widely used navigation systems. The use of cost effective MEMS based inertial sensors has made GPS/INS integrated navigation systems more affordable. However MEMS sensors suffer from various errors that have to be calibrated and compensated to get acceptable navigation results. Moreover the performance characteristics of these sensors are highly dependent on the environmental conditions such as temperature variations. Hence there is a need for the development of accurate, reliable and efficient thermal models to reduce the effect of these errors that can potentially degrade the system performance. In this paper, the Allan variance method is used to characterize the noise in the MEMS sensors. A six-position calibration method is applied to estimate the deterministic sensor errors such as bias, scale factor, and non-orthogonality. An efficient thermal variation model is proposed and the effectiveness of the proposed calibration methods is investigated through a kinematic van test using integrated GPS and MEMS-based inertial measurement unit (IMU).