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Research On Nonlinear Algorithm For Improving GPS Positioning Precision

Posted on:2008-11-08Degree:MasterType:Thesis
Country:ChinaCandidate:L WenFull Text:PDF
GTID:2120360212476150Subject:Precision instruments and machinery
Abstract/Summary:PDF Full Text Request
Global Position System (GPS) is a precise new-generation satellite-based positioning system. It has gained extensive development in the military and civilian fields for its all-global, all-weather and highly accurate characteristics.In recent years, with the development of navigation and positioning, people have higher demands for the positioning precision. However, GPS positioning includes some error sources such as the measurement errors and the satellite position errors. The filtering algorithm is an important method to reduce these errors and improve the GPS positioning precision.The Kalman filter is one of the optimal filtering algorithms, and the Kalman filtering adapts to the unstable random process. So, it gains extensive application. Recently, Extended Kalman filtering (EKF) has been one of the main methods for studying the two problems of initial alignment and GPS integrated navigation which both have nonlinear characteristics. Because EKF necessitates the linearization of the original nonlinear models, the performances achieved by using EKF are limited to some extent. In recent years, Unscented Kalman filtering (UKF) is becoming the focus of nonlinear estimation. And because Iterated Kalman...
Keywords/Search Tags:GPS, Extended Kalman filter, Unscented Kalman filter, Kalman smoother, Iterative Kalman smoother
PDF Full Text Request
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