الفهرس 
IntroductionOnly 14 pages are availabe for public view
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Abstract
Autonomous systems represent a prominent area of contemporary research. Fundamen- tal to these systems is the ability of mobile entities to self-locate within their operational environments. Achieving precise localization necessitates the utilization of various sen- sors, each with its own set of advantages and limitations.
MEMS IMU (Micro-Electro-Mechanical Systems Inertial Measurement Unit) stands as a crucial sensor for system localization due to its self-contained nature, eliminating reliance on the external environment for measurements. It offers several benefits, including affordability, low power consumption, and lightweight design. Nonetheless, MEMS IMUs are not without their challenges, primarily stemming from significant errors that restrict their utility to only a short time period of operation. A major source of these errors originates from the MEMS gyroscope inaccuracies.
Our research is dedicated to the characterization of MEMS gyroscopes, with a focus on identifying different noise sources affecting gyroscope output. To accomplish this, we employed the Allan variance technique to quantitatively estimate noise processes in three distinct MEMS gyroscopes: InvenSense MPU6050, Analog Devices ADIS16334BLM, and an early-stage R&D Gyrosocope designed by Si-ware Systems.
Additionally, we explored the application of the rotation modulation technique by build- ing a lab setup using the MPU6050 and ADIS16334BLM gyroscopes to mitigate attitude angle drift in gyroscopes.
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