(1) Department of Geomatics Engineering, University of Calgary, Schulich School of Engineering, Calgary, AB, Canada;
Abstract:
A Kalman filter-based method combining the energy of both L1 C/A and L2C GPS signals in a combined tracking loop method to enhance performance under adverse conditions is developed. Standard tracking methods and the ionospheric effect on GPS signals are reviewed and compared to a new Kalman filter that simultaneously estimates delay, phase and total electron content by combining L1 C/A and L2C code and phase discriminator outputs. The new filter is tested and compared to standard methods for tracking L1 C/A and L2C using both simulated and real data. The new method is found to have improved sensitivity of 3 dB compared to standard L1 tracking and 4.5 dB compared to standard L2C tracking while at the same time providing an accurate estimate of the total electron content along the signal path.
