Real-Time Position, Velocity and Attitude Estimation Using Low-Cost GNSS Only Reduced Navigation System

Integrated navigation systems are essential for position, velocity, and attitude determination for different applications, including military and civilian ones (drones, UAVs, UGVs, self-driving cars, etc.). The advancements in the Micro-Electromechanical Systems (MEMS) technology have allowed the possibilities of having miniature sensors with a whole wide range of accuracies. Most low-cost navigation system are based on the idea of integrating low-cost GNSS receivers with MEMS-based IMUs using sensor fusion algorithms to provide localization and attitude navigational information with acceptable accuracy at relatively low power consumption and reduced computations as well. This paper aims to propose a low-cost Arduino compatible GNSS-only reduced navigation module that provides eight-out of-nine navigation states (represented in 3D positioning, 3D estimated velocity components in LLF, pitch and heading estimated attitude angles) using a proposed real-time estimation algorithm and without incorporating any inertial sensors. Real in-field data were collected under off-road and urban environments to evaluate the fidelity of the proposed GNSS-only module (including real-time estimation algorithm running on the aforementioned Arduino compatible receiver) using two different GNSS antennas. Such an evaluation was performed by comparing the navigation states acquired from the system undertest with an integrated INS/GPS reference system attached on the same platform. The results showed that the proposed reduced navigation system associated with the real-time estimation algorithm is successfully capable of providing 8-out of-9 navigational states with acceptable accuracy using both antennas. Results also demonstrated a better performance for the reduced GNSS-only system connected to one antenna (Taoglas ADFGP.50A) than the other (Taoglas AGGP.35f) in terms of altitude information and speed recovery of the localization information after GNSS outage periods.