Performance Evaluation of GPS Auto-Surveying Techniques

Area of Science:

• Geomatics Engineering
• Satellite Navigation Systems
• Geodetic Surveying

Background:

• Global Navigation Satellite Systems (GNSS) are increasingly vital for applications demanding precise positioning.
• Differential GNSS (DGNSS) and Real-Time Kinematics (RTK) offer high precision but depend on accurate base station reference positions.
• Auto-surveying base station positions is crucial for absolute positioning accuracy in GNSS applications.

Purpose of the Study:

• To analyze and compare four positioning methods for rapid auto-surveying of GNSS base station receivers.
• To evaluate the performance of Least Squares (LS), Weighted Least Squares (WLS), Extended Kalman Filter (EKF), and Unscented Kalman Filter (UKF) using pseudorange measurements.
• To assess the effectiveness of the Hatch Filter and position thresholding in conjunction with these positioning methods.

Main Methods:

• Comparison of LS, WLS, EKF, and UKF algorithms using only pseudorange measurements.
• Integration of Hatch Filter and position thresholding techniques for enhanced base station auto-surveying.
• Validation of the best-performing methods against existing implementations with varying receiver hardware.

Main Results:

• EKF and UKF demonstrated significantly lower mean errors compared to LS and WLS.
• Attained precision below 1 meter after approximately 4 hours of auto-surveying using EKF and UKF.
• The EKF and UKF methods proved highly competitive against existing implementations, even with different receivers.

Conclusions:

• EKF and UKF are superior methods for auto-surveying GNSS base station positions, achieving high precision efficiently.
• The improved base station position estimates derived from EKF/UKF significantly enhance the accuracy of Differential GNSS (DGNSS) positioning.
• This research validates the practical benefits of advanced filtering techniques for real-world GNSS applications.