Abstract
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.
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