Development of Advanced Extended Kalman Filter for Precise Estimation of GPS Receiver Position
| Autor: | Nalineekumari Arasavali, N. Ashok Kumar, G. Sasibhushana Rao |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Computer science
business.industry Gps receiver 020206 networking & telecommunications 02 engineering and technology Kalman filter Extended Kalman filter Position (vector) ComputerSystemsOrganization_MISCELLANEOUS 0202 electrical engineering electronic engineering information engineering Global Positioning System 020201 artificial intelligence & image processing Development (differential geometry) business Algorithm |
| Zdroj: | 2019 International Conference on Wireless Communications Signal Processing and Networking (WiSPNET). |
| DOI: | 10.1109/wispnet45539.2019.9032769 |
| Popis: | Most of the navigation algorithms are being used to estimate GPS receiver position. But, none of them are achieved full accuracy yet. Thus, there is requirement of new algorithms. Precise estimation of GPS receiver clock bias is essential in order to eliminate its affect on the position estimation. Otherwise, the estimated position shall be inaccurate. In this paper, an Advanced Kalman Filter (AEKF) is proposed which offers accurate estimation and fast convergence rate in order to precisely estimate the GPS receiver clock bias along with its position. The proposed AEKF and standard Extended Kalman Filter (EKF) are practically implemented on the GPS data collected from a dual frequency GPS receiver that is installed at Andhra University, Visakhapatnam (Lat. $17.73^{\circ}N/Lon. 83.31^{\circ}E$). From the results, it is observed that the proposed AEKF is a better algorithm that provides precise estimation of GPS receiver clock bias and GPS receiver position compared to standard EKF. |
| Databáze: | OpenAIRE |
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