Performance assessment of aided Global Navigation Satellite System for land navigation

Land navigation includes the methods to determine the time varying position and velocity of a moving object on Earth surface using suitable measurements; it is typically performed in signal-degraded environments where GPS signals are blocked or degraded; hence GPS-only cannot guarantee an accurate and continuous positioning. The multi-constellation approach is a possible way to fill this gap. In this work GPS/GLONASS systems are combined and single point algorithm performance is assessed for different configurations in urban scenario. GLONASS is nearly fully operational and its inclusion guarantees satellite availability improvement, but the GPS/GLONASS multi-constellation use involves the addition, as further unknown, of the intersystem time-scale offset. The considered estimation techniques are Least Squares and Kalman filter. The first method uses only the measurement model, with the drawback of solution unavailability during GNSS outages. The last uses, in addition to a measurement model, a process model allowing the estimation of the unknowns in case of GNSS outage. To improve both methods performances aiding are considered on height and intersystem time scale offset. The main purposes of this work are the performance assessment of a multi-constellation system relative to GPS-only, adopting the aforesaid estimators, and the benefit evaluation of the aiding.