Study of the variance ratio effect to improve conventional Kalman filter applications in vehicle navigation system

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• 作者：H. T. El Shambaky ; Mosbeh R. Kaloop
• 关键词：kalman filter tuning ; adaptive kalman ; random process noise ; vehicle navigation
• 刊名：KSCE Journal of Civil Engineering
• 出版年：2017
• 出版时间：January 2017
• 年：2017
• 卷：21
• 期：1
• 页码：408-417
• 全文大小：
• 刊物类别：Engineering
• 刊物主题：Civil Engineering; Industrial Pollution Prevention; Geotechnical Engineering & Applied Earth Sciences;
• 出版者：Korean Society of Civil Engineers
• ISSN：1976-3808
• 卷排序：21

文摘

Recently Kalman filters have been widely used in vehicle navigation systems and various Global Navigation Satellite System (GNSS) receivers. A conventional Kalman (CK) filter is found as an inferior solution to precisely determine the turning and monitoring points in comparison with the Adaptive Kalman filter, previously. Therefore, this study aims at investigating a novel solution to improve the CK. algorithm based on the effect of the variance ratio on the algorithm accuracy. The simulation process is used to determine and update the characteristic equation of the Kalman algorithm system. In addition, the comparison between the real observations for proposed updated CK (UCK) and Adaptive algorithms are applied and discussed in this study. The results, herein, demonstrate that the variance factor ratio (variance ratio) can aid a CK algorithm to be more economical, precise and steady. Moreover, the real observations prove that the CK filter with variance ratio performs more efficient than the adaptive one.