Dual GNSS systems positioning based on nonlinear filter and satellites selection in bad conditions
Fucheng Dai, Xuchu Mao · 2014
This paper described how to combine two different GNSS systems to have better result if only one is not enough. Single navigation system faces great problems in bad conditions, where the GNSS signals are often blocked by high-rise buildings and there are not enough available satellite signals to estimate the positioning information. As the BDS comes into use, the visible satellites increase. We can combine BDS with GPS to form dual system positioning. In this way, adequate signals could be received to estimate user's position. This paper presents a new model for position and velocity estimation in BDS/GPS dual system. The model is nonlinear and combines BDS and GPS completely. It is also able to cope with an arbitrary number of satellites. After select the strength satellites' signals, applying this model to extended kalman filter (EKF) and unscented kalman filter (UKF) with varieties of experiment to evaluate its performance. The estimation results show that this model performs high accuracy and stability, when the total satellites of BDS and GPS are no less than 5.