An Algorithm to Assist the Robust Filter for Tightly Coupled RTK/INS Navigation System

The Real-Time Kinematic (RTK) positioning algorithm is a promising technique that can provide real-time centimeter-level precision in GNSS-friendly areas. However, the performance of RTK degrade GNSS-hostile areas like urban canyons. surrounding buildings and trees reflect block Global Navigation Satellite System (GNSS) signals, obstructing GNSS receivers’ ability to maintain signal tracking exacerbating multipath effect. A common method assist couple with Inertial (INS). INS accurate short-term relative results. Extended Kalman Filter (EKF) usually used INS, whereas outlying observations significantly influence performance. Robust (RKF) developed offer resilience against outliers. In this study, we design an improve traditional RKF. We begin by implementing tightly coupled RTK/INS conventional RKF C++. also introduce our specific implementation detail. Then, test analyze codes on public datasets. Finally, propose novel improvement. Carrier-to-Noise Ratio (CNR) help detect outliers should be discarded. results tests show new algorithm’s accuracy improved when compared open source majority code, as find there are few open-source projects for Researchers access at GitHub.