Improving GPS/INS Integration through Neural Networks

The Global Positioning Systems (GPS) and Inertial Navigation System (INS) technology have attracted a considerable importance recently because of its large number of solutions serving both military as well as civilian applications. This paper aims to develop a more efficient and especially a faster method for processing the GPS signal in case of INS signal loss without losing the accuracy of the data. The conventional or usual method consists of processing data through a neural network and obtaining accurate positioning output data. The new or improved method adds selective filtering at the low-band frequency, the mid-band frequency and the high band frquency, before processing the GPS data through the neural network, so that the processing time is decreased significantly while the accuracy remains the