Low-cost, Dual-frequency PPP GNSS and MEMS-IMU Integration Performance in Obstructed Environments

Abstract

The GNSS PPP navigation solution has the advantage of not requiring local reference station infrastructure as in the case of the RTK technique and the accuracy of geodetic GNSS PPP solutions can reach the decimetre-level in kinematic mode. The recent emergence of low-cost, high-performance MEMS IMUs prompts the integration of lowcost GNSS PPP and MEMS IMU to improve accuracy and continuity of the navigation solution. In the past, research has been conducted to integrate high-end GNSS receivers with PPP processing and MEMS IMUs, or low-cost, single frequency GNSS receivers with point positioning processing and MEMS IMUs. The objective of this research is to investigate and analyze position solution availability and continuity by integrating low-cost, dual-frequency GNSS receivers using PPP processing with the latest low-cost, MEMS IMUs to offer a complete, low-cost navigation solution that will enable continuously available, high-quality positioning and navigation solutions, even in obstructed environments. Using a dual-frequency GNSS receiver mitigates the ionosphere refraction to a large extent. The integrated solution offers less than meter-level accuracy when there is a GNSS signal outage for half a minute. The results obtained using the tightly-coupled, low-cost, dual-frequency GNSS-PPP and MEMS IMU performs 30% better than the low-cost, single-frequency GNSS-PPP with MEMS IMU solutions demonstrated in previous studies during similar simulated outages. These results encourage usage of such a low-cost navigation system in contemporary applications such as UAVs, pedestrian navigation, autonomous vehicles, etc. As part of future work, the algorithm will be tested and assessed in tunnels and downtown areas. Zero velocity update will be implemented to improve the heading estimate, while the vehicle is stationary. And further refinement of the tight-coupled solution will be performed with the latest low-cost sensors.