Kinematic Positioning Algorithm Based on the Grey Prediction Model for Urban Navigation

Lack of visible satellites in urban environment will have an adverse impact on positioning and navigation. The kinematic positioning will have a degrading accuracy and even fail to gain the consequences of positioning when in serious conditions. In view of the shortage of observable satellites, this paper, based on the grey prediction model, respectively uses the pseudo-range observation values of the latest epochs and the estimation vector of state parameters to forecast the pseudo-range observation values and state parameters of the current epoch. The experimental results show that it is feasible to use the grey prediction model to predict the state value as the navigation and positioning result or pseudo-range observation value for positioning in the epochs with insufficient observable satellites. The actual calculation example shows that the accuracy of predicted observation values in the absence of available satellites in the field is improved by 61.9%, 53.6% and 18.9% respectively in the ENU direction, and the predicted state parameters are improved by 38.1%, 18.1% and 11.3% respectively in the ENU direction. Obviously, the algorithm proposed in this paper can effectively solve the problem that the kinematic positioning accuracy is reduced or even cannot be located when the signal is blocked for a short time in urban environment, and improve the accuracy and reliability of the kinematic positioning.