Earth-Centered Earth-Fixed (ECEF) Vehicle State Estimation Performance

Abstract

Many applications, including connected and autonomous vehicles, would benefit from navigation technologies achieving sub-meter position accuracy with high reliability on moving platforms. This article presents the results of a study with two main goals: (1) the feasibility of achieving meter-level positioning accuracy on at least 95% of epochs using differential Global Navigation Satellite System (DGNSS) based state estimation; (2) the presentation and analysis of two state estimation approaches at high frequency (200 Hz) suitable for moving platforms. The Position, Velocity, Acceleration (PVA) approach uses DGNSS data only within a Kalman filter framework.The Inertial Navigation System (INS) approach uses DGNSS and inertial measurement data within an extended Kalman filter implementation. Section V shows that both approaches have performance exceeding the SAE J2945 specification (1.5 meter horizontal accuracy and 3.0 meter vertical accuracy at 68%) with PVA achieving 1m horizontal at 90% and 2 m vertical accuracy at 95% while the INS approach achieves 1m horizontal at 98% and 2 m vertical accuracy at 95%.