A Study of a GNSS/IMU System for Object Localization and Spatial Position Estimation

Today, navigation systems are commonly used in a variety of applications such as autonomous vehicles, image stabilization, object detection and tracking, and virtual reality (VR) or artificial reality (AR) systems. These systems require not only the precise location but also the accurate tracking of the orientation of rigid bodies moving in a three-dimensional (3D) space. This study introduces the integration of GNSS and a 10DoF IMU system to solve the navigation task and calculation of the object position, attitude, and heading. As the location and the attitude calculations require different states but use the same data from the INS sensors, the sensor data fusion in two Kalman filters is proposed. As the filters' performance is critical, according to the initial states, we study in detail the Allan Variance and normal distribution parameters of three different MEMS IMU sensors. The GNSS system performance and statistics are examined using two commercial and three proposed single or dual-band GNSS antennas. An experimental study is conducted, and the KF output of the heading angle is compared with other sources.