Conceptual Framework for the Analysis and Modeling of GNSS Measurements based on Gaussian Process

The Global Navigation Satellite Systems (GNSS) have been used in autonomous vehicles and remote sensing. The GNSS receiver can be a conventional device or an enhanced device that adopts precise positioning technology such as differential positioning and real time kinematics. However, the GNSS devices could still produced outputs that are subjected to various sources of errors. Hence, their performance needs to be evaluated and analyzed. Subsequently, error mitigation techniques are proposed to enhance the GNSS performance. In this paper, we aim to present a conceptual framework on the analysis and modeling of GNSS measurements based on Gaussian Process (GP). Firstly, the methods of performance analysis of GNSS devices are presented. Secondly, current works on the applications of GP to model GNSS and position sensors’ errors are briefly reviewed. Subsequently, we present a conceptual framework to provide an overview to the readers the purpose of various performance evaluation methods. On the other hand, the conceptual framework on the current applications of GP to model and improve GNSS errors is presented to wrap up the concepts and methods of GP that has been implemented by researchers thus far. The established framework assists us to identify some research gaps and further works that can be explored in the applications of Gaussian process to model GNSS measurements and errors.