Characterizing Stochastic Errors of MEMS – Based Inertial Sensors

Abstract

Thank to strong grow of MicroElectroMechanicalSystem (MEMS) technology, high performance and small size sensors are widely used in many areas such as landslide, navigation, mobile phones, etc. However, there are several kinds of errors are still existing in MEMS based sensors that need a carefully analyzing and calibration. By each year, the performances of commercial sensors are also improved. In this paper, we focused on characterizing the stochastic errors of accelerometers and gyroscopes integrated with a latest smart phone of Apple Inc. Iphone6+. The MP67B is a custom version of the InvenSense 6-Axis device (3-Axis gyroscope and 3-Axis accelerometer) made for Apple. This research will play an important step to decide whether we can create an Inertial Navigation System(INS) in the same device (i.e. the smart phone, the users do not need to equip a single device for positioning application). The Allan variance method is exploited to analyze the stochastic errors in these sensors. Experiments proved that the main sources of errors in these sensors are white noises. The Iphone5 can operate as a low-cost solution of positioning and navigation device