详情

原文传递 Investigation on Nonlinear Models for GPS Algorithms

题名：	Investigation on Nonlinear Models for GPS Algorithms
作者：	Xuchu Mao; Massaki Wada; Hideki Hashimoto; Masaki Saito; Shinichi Mastuda
关键词：	Nonlinear Models; GPS; Algorithms; filter
摘要：	This paper presents the results obtained in our research about application of modern non-linear filtering techniques to GPS based position estimation. The stand-alone GPS based position estimation problem using GPS raw data, pseudo-range and Doppler shifts measurements are described. A new model for position and velocity estimation are then developed for nonlinear filtering. The model is nonlinear and has variable measurement number for coping with an arbitrary number of satellites. The model is investigated applying it to two different nonlinear filters. The first one is the presently most used nonlinear filter: the extended Kalman filter. The use of unscented filter as an alternative filter for composing GPS based system and model parameter learning is also proposed. The first experimental results that comprise the comparison of estimation results obtained with the filtering model using different filters are then presented. Future research directions are also discussed.
总页数：	Conference Title: 9th World Congress on Intelligent Transport Systems. Location: Chicago, Illinois. Sponsored by: ITS America, ITS Japan, ERTICO (Intelligent Transport Systems and Services-Europe). Held: 20021014-20021017. 2002. pp12
报告类型：	科技报告