GPS/DR Navigation Data Fusion Research Using Neural Network

Abstract

It is well known that GPS can be used for localization and navigation in outside environment. Standard DGPS can be used to get an accuracy of under one meter. The precision improves but the cost is very high. The cheep single frequency GPS receiver is used in this paper to provide the positioning information. This paper proposes a new navigation data fusion method using neural network. DR (dead reckoning) navigation system can provide precise short term navigation information. But the error can accumulate over time without limitation. A BP neural network is employed to predict next sampling time GPS output and a new Kalman filter based data fusion method is proposed to do the navigation data fusion with GPS/DR system. Simulation is conducted to validate the proposed fusion method. The result shows the potential of this fusion method for outside used mobile robot navigation.