A novel hybrid approach utilizing principal component regression and random forest regression to bridge the period of GPS outages

摘要

Global Positioning System (GPS) and Inertial Navigation System (INS) are two salient technologies delivering a vehicle's position, velocity and attitude parameters for navigation. The standalone GPS undergoes signal outages (in forest area) and multipath effects (in urban areas), whereas the standalone INS solution accuracy deteriorates with time. To overcome the limitations of standalone GPS and INS, an integrated INS/GPS system is required for continuous, accurate, and reliable navigation solution. This paper proposes a hybrid method of Principal Component Regression (PCR) and Random Forest Regression (RFR) for INS and GPS data fusion.