Comparative analysis of regression algorithms for the prediction of NavIC differential corrections

Abstract

Abstract Indian Regional Navigation Satellite System (IRNSS) or Navigation with Indian Constellation (NavIC) provides positioning, navigation and timing information services to various users in Indian region. Standalone NavIC may not meet the position accuracies for certain application such as civil aviation. Differential NavIC is used for improving the position accuracy of rover receiver, which make use of differential corrections (transmitted from reference station). However, if the satellite signals are temporarily lost due to abruptly changing atmosphere, satellite health issues or if the satellite signals are attenuated due to city infrastructures in urban areas, tree canopies, the accuracy of NavIC will be degraded. This article compares regression tree and bagging tree based differential corrections prediction algorithm with the actual differential corrections, by considering the NavIC satellite signal strength (C/No) and elevation angle (El), to improve the NavIC positioning accuracy. The improvement in the position accuracy is obtained by utilizing predicted differential corrections. The position accuracy of rover using actual differential corrections (2DRMS – 3.09 m), regression tree predicted differential corrections (2DRMS – 5.96 m) and bagged tree predicted differential corrections (2DRMS – 3.06 m) are compared. Here, the rover accuracy using actual differential corrections and bagged tree predicted differential corrections are approximately equal. So, the position accuracy using bagged tree predicted differential corrections are accurate when compared to regression tree predicted differential corrections.