Information fusion and data-driven processing in inertial measurement units for cyber-physical systems

Abstract

Our research is aimed to increase accuracy and enhance data quality of inertial sensors. Inertial navigation systems (INSs) combine physical and cyber components such as micromachined sensing elements, processing and interfacing application-specific integrated circuits, software, etc. Our goals are to develop physics-consistent tools and algorithms for inertial measurement units (IMUs). Using the measured accelerations and velocities, post-processing is performed to reduce noise and errors in the measured and estimated physical quantities. These features ensure accurate estimates on position, orientation, and trajectory. Basic and applied results are experimentally validated using an Inertial Measurement Platform which consists of an IMU and microcontroller. Our findings both contribute to engineering solutions and empower transformative technologies towards technology transfer for cyber-physical systems. The proposed solutions can be applied to enable cloud information fusion and data management. We performed and demonstrated analytical and laboratory studies to validate methods, algorithms, and technology components.