Fault Diagnosis of Integrated Navigation System based on Improved Random Forest

In order to accurately diagnose the fault of integrated navigation system and ensure the stable operation of integrated navigation system, a fault diagnosis method of Global Positioning System (GPS) / Inertial Navigation System (INS) integrated navigation system based on improved random forest algorithm was studied. This method aims to improve the accuracy and reliability of fault detection in integrated navigation system. By utilizing the improved random forest algorithm, the system can classify faults more effectively and with greater precision. Experimental results show that the accuracy of this method is 97.99%. This demonstrates that the fault diagnosis method based on the improved random forest algorithm is highly effective in identifying and classifying faults within the GPS/INS system. At the same time, this paper also compares the accuracy of the traditional random forest algorithm with the improved random forest algorithm in fault identification. The comparison further indicates that the improved random forest algorithm can significantly enhance the accuracy of fault diagnosis, making it a superior choice for enhancing the performance and dependability of GPS/INS integrated navigation systems.