Application Of The Extented Forgetting Factor Recursive Least Squares Estimator To GPS

The Global Positioning System(GPS)established mainly by America can provide services for very precise positioning and navigation．It has got more and more aPpllcatlons In practice．Many o句ectlve conditions and some conditions even made by men reduce the precise of the GPS．The Extented Kalman Filtering(EKF)is aPplied In the GPS to resolve the problem of＊them stochastlc noise,but It Is a good method only when many conditions have been satisfied．However these conditions are notalways satlsfiedlnpractlce．Inthlsthesls,theExtentedForgettingFactor Recurslve Least Squares Estlmator(EFRLS)Is pplied in the GPS．Firstly3 we briefly Introduce the algorlthlns of＊thethlns EK又 the EFRLS,and we analyze their advantage and disadvantage．Then a moving owect In the GPS Is est劝fished．Finally we compare the performances ofboth algorithms vlathe compmer simulations In some dlfferellt COlldlt100S．...