Dinh Xuan Vinh

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The article discusses the Kalman filter application for temporal random motion of the GPS receiver location. The motion of the GPS receiver is a space state model with time-varying. The spatial state model is usually represented by linear differential equations with white noise. When the state of space fluctuates over time, it is represented by Riccati equations, ie nonlinear differential equations. We proposed extending the Kalman filter with parameters suitable for the measurement conditions established large scale maps in Vietnam today.Coordinate points of GPS mobile over time is compared with coordinate values in a case of static measurements previously with high precision, confirming the Kalman filter extended with parameters suitable to estimate the optimal mobile GPS receiver location. This reduces the investment cost and increases the efficiency of using a common GPS receiver.

Key words: Kalman filter, kinematic GPS.

Keywords: Kalman filter, kinematic GPS.


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