GNSS NLOS and Multipath Error Mitigation using Advanced Multi-Constellation Consistency Checking with Height Aiding

High sensitivity multi-constellation GNSS receivers can dramatically improve the satellite availability in an urban environment. However, positioning accuracy remains a challenge because of blockage, reflection and diffraction of signals by buildings. In typical urban positioning scenarios, the receiver often receives a mixture of non-line-of-sight (NLOS) signals, multipath-contaminated direct line-of-sight (LOS) signals, and clean direct-LOS signals. Multi-constellation GNSS allows maximising the positioning accuracy by selecting only those signals that are least contaminated by multipath and NLOS propagation to form the navigation solution. A technique exploring the consistency among received signals using randomly draw subsets of all available signals is proposed in this research. The implementation of the algorithm follows an estimation scheme known as RANdom SAmple Consensus (RANSAC). A pre-defined cost function is firstly used to select the best available subset of measurements. A reference solution is produced from the best available subset. The "residuals" of all received signals, i.e. the differences between the observed measurements and the predictions from the reference solution, are examined. The examination features a receiver autonomous integrity monitoring (RAIM) like statistical test based on specific distributions. A final solution is produced from measurements passed the examination plus the best available subset. In addition, height aiding from a terrain elevation database is used as an additional ranging measurement to further enhance the positioning performance. Two GPS/GLONASS data sets collected from different urban areas of central London were used for testing. Different versions of the cost function and the effect of introducing height aiding are tested. The results show an improvement of positioning accuracy over conventional least-squares algorithm and previous consistency-checking algorithm through reduction of the impact of multipath and NLOS propagation errors.