Performance Evaluation of Combined L1/L5 Kalman Filter-Based Tracking versus Standalone L1/L5 Tracking in Challenging Environments

Abstract

The ever-increasing demand on GPS to perform in challenging environments is the main motivation behind this research. With the existence of these challenging environments, more research is directed towards enhancing the tracking capabilities. Several solutions have been proposed to enable high sensitivity tracking using only one signal. However, new GPS signals are now available, in addition to the conventional L1 signal. Being transmitted from the same space vehicle through the same environment, the errors between these signals are correlated. Hence, an increase in tracking sensitivity can be achieved by combining two or more of these signals. This paper proposes the idea of combining the L1 and L5 signals using one Kalman filter, where the correlator outputs of the two signals are used to estimate the tracking errors. The performance of this combined Kalman filter is compared to a similar Kalman filter that is used separately for tracking each of the two signals. The performance of both filters is compared in environments suffering urban canyon multipath, moderate ionospheric errors, in addition to a motion model of a typical vehicle. The combined Kalman filter is shown to outperform the separate Kalman filter, both in the tracking errors and in the filter statistics.