A real-time accuracy prediction model on time-relative positioning method considering the correlation of position increment errors

Time-relative positioning (TRP), a global navigation satellite system (GNSS) dead reckoning method with low-cost and highly autonomous characteristics, accumulates the position increments calculated by time-differenced carrier phase (TDCP) between adjacent epochs to extrapolate position. It suffers from error accumulation over time, so it is necessary to judge the availability of positioning services based on predicted accuracy. We propose a new model to predict the accuracy (the root-mean-square error, RMSE) of TRP in real time by determining systematical errors and random errors. The proposed model consists of the following two steps: first, extracting the systematic errors and correlation of position increment errors before position extrapolation; second, predicting RMSE of the positioning results based on the error propagation law during position extrapolation. The experimental results show that after considering the correlation, the predicted RMSE sequences can envelop the actual positioning error more closely. In the case of having static observation before position extrapolation, the predicted RMSEs of extrapolation position in both horizontal and vertical directions decrease by approximately 53.8