Cost-effective Testing and Calibration of Low Cost MEMS Sensors for Integrated Positioning, Navigation and Mapping Systems

error modeling. SUMMARY Integrated INS/GPS systems provide continuous positioning information in any environment. Accurate positioning information from GPS is used to provide frequent updates to the INS, while the GPS signal losses will be compensated for in real-time by using the short-term accuracy of the INS derived position and velocity. However, current integrated existing systems use high-end inertial sensors which are expensive and bulky. Hence, to reduce the cost of the integrated system, Micro-Electro-Mechanical System (MEMS) based inertial sensors are proposed. However, these light-weight and low-cost MEMS sensors suffer from various errors like turn-on biases or the scale factor drift errors which are negligible for navigation grade sensors. Moreover the performance characteristics of these sensors are highly depended on the environmental conditions, especially temperature variations. Hence there is a need for the development of accurate, reliable and efficient thermal models to decrease the effect of these errors that can potentially degrade the system performance. In this paper, the maximum noises affecting the MEMS sensors were analyzed and the effects o