Tightly Coupled Integration of GNSS and IMU sensor

Abstract

The objective of this research is to investigate the potential benefits of integrating Inertial Measurement Units (IMU) with Global Navigation Satellite Systems (GNSS) in order to attain accurate positioning. This research tackles the challenging task of maintaining precise location estimations in various situations by tightly integrating GNSS and IMU readings with sophisticated fusion methods like Extended Kalman filtering. Real-time navigation and positioning are facilitated by the collection of data from GNSS receivers and IMU sensors installed in a lab environment. The findings show notable gains in positioning precision and reliability over stand-alone GNSS or IMU systems. Particularly noteworthy is the effective mitigation of GNSS signal obstructions and multipath errors through the integrated approach, which improves positioning performance in difficult environments such as indoor environments or in urban canyons. Furthermore, this research highlights the significance of using multiple satellite constellations, including Global Positioning System (GPS) and BeiDou Navigation Satellite System (BDS), to improve the reliability and precision of location. By using signals from multiple satellite constellations, the available data sources are diversified, which decreases vulnerability to signal interruptions and enhances the overall reliability of the integrated system. GNSS-IMU integration has practical consequences in a wide range of applications such as navigation, autonomous cars, robotics, and augmented reality. By harnessing the capabilities of supplementary sensor technologies, this integrated system presents a potentially effective resolution for attaining accurate and robust positioning through implementation of an 11-state Extended Kalman Filter (EKF). Findings from this research highlight the need to optimize sensor setups and continue honing fusion algorithms in order to improve integrated navigation systems. Further developments in technology may prompt future research to concentrate on investigating supplementary sensor modalities and fortifying integrated navigation solutions in order to cater to the requirements of emergent applications.