Reduction of PPP convergence period through pseudorange multipath and noise mitigation

摘要

Pseudorange multipath and pseudorange noise are the largest remaining unmanaged error sources in PPP. It is proposed that by reducing the effects of multipath and noise on the pseudorange observable, accurate estimates of carrier phase float ambiguities will be attained sooner, thus reducing the initial convergence period of PPP. Given the problem, this study seeks to improve mitigation of the pseudorange errors. The well-known multipath linear combination is used in two distinct ways: (1) to directly correct the raw pseudorange observables and (2) to stochastically de-weight the pseudorange observables. The improvements in the solution were calculated with respect to the conventional GPS PPP float solution, where the raw pseudorange observables were not modified or stochastically de-weighted. Corrections to the observables were made using the multipath linear combination from data obtained from the previous and same day. Minimal improvements were noted using the multipath observable from the previous day. Using the multipath observable from the same day was possible in real-time and post-processing modes, showing an improvement in the rate of convergence for 48 and 57 % of the data, respectively. An improvement in the rate of convergence for 34 % of the data was observed when the pseudorange measurements were stochastically de-weighted using the multipath observable. Datasets with no improvements from directly correcting the raw pseudorange observables (43 %) or stochastically de-weighting the pseudorange observables (66 %) presented similar quality of results as the conventional PPP solution.