GPS/INS System Integratin Based on Neuro-Wavelet Techniques.

TLDR: A new method for error estimation in a GPS/INS augmented system based on Artificial Neural Network (ANN) and Wavelet Transform (WT) was offered and it was found that the proposed technique reduces the standard deviation error in the position by about 91% and in velocity it was reduced by about 94%.

Abstract: Global Positioning System (GPS) and Strapdown Inertial Navigation System (SDINS) can be integrated together to provide a reliable navigation system. This paper offers a new method for error estimation in a GPS/INS augmented system based on Artificial Neural Network (ANN) and Wavelet Transform (WT). An ANN was adopted in this paper to model the GPS/INS position and velocity errors in real time to predict the error in the integrated system and provide accurate navigation information for a moving vehicle. It was found that the proposed technique reduces the standard deviation error in the position by about 91% for X, Y, and Z axes, while in velocity it was reduced by about 94% for North, East, and Down directions.