THE DEVELOPMENT AND VALIDATION OF A TACTICAL GRADE EGI SYSTEM FOR LAND VEHICULAR NAVIGATION APPLICATIONS

Abstract

Over recent years, the utilization of commercially available integrated navigation systems for the development of navigation algorithms has become increasingly commonplace. Nevertheless, the wide range of sensor quality on the market complicates system customization and restricts the evolution of navigation algorithms. This study aims to address these issues by creating an affordable, tactical-grade, real-time integrated navigation system, EGI-500 (Embedded GNSS and INS), encompassing both hardware and software components. EGI-500 incorporates a tactical-grade IMU500 and a Septentrio Mosaic-X5 GNSS receiver module. The integration process is segmented into three distinct stages. The first involves hardware integration, with an illustrative architecture diagram of the real-time navigation system. Second, we focus on data preprocessing, where a cross-correlation approach is proposed to tackle multi-sensor time synchronization issues, specifically to determine potential time lags in IMU data. The final phase covers the fusion of multi-sensor data and motion constraints. The Extended Kalman Filter (EKF) forms the backbone of this part, with Zero Velocity Update (ZUPT) and Non-Holonomic Constraints (NHC) being integrated into the Loosely Coupled (LC) scheme. Furthermore, the IMU calibration process is performed to ascertain necessary algorithmic parameters. Experimental results, conducted in diverse environments (open sky, GNSS challenging, and GNSS denied), will be presented in this paper. Comparisons with reference data indicate that the navigation accuracy of the developed integrated system, both in terms of hardware and navigation algorithm, achieves expected meter-level accuracy, fulfilling the "Which Lane" and "Which Road" level criteria in varied environments. Furthermore, outcomes from the GNSS denied environment align with predictions based on propagation error theory, demonstrating the feasibility of our navigation algorithm for tactical integrated navigation systems.