Thermal Calibration of MEMS Inertial Sensors for an FPGA-Based Navigation System

Based on a small, lightweight, low-cost high performance inertial Measurement Units (IMU), an effective calibration method is implemented to evaluate the performance of Micro-Electro-Mechanical Systems (MEMS) sensors suffering from various errors to get acceptable navigation results. A prototype development board based on FPGA, dual core processor's configuration for IMU/INS/GPS integrated navigation system is designed for experimental tests. The significant error sources of IMU such as bias, scale factor, and non-orthogonality are estimated in virtue of static tests, rate tests, thermal tests. Allan variance method is used to characterize the stochastic noise in inertial sensor. Moreover, a reliable intelligent thermal compensation method comparing polynomial model methods is proposed to reduce the effect of these errors that can degrade the system performance. Experimental results are afforded and evaluated.