|Abstract:||This paper presents a novel algorithm to enhance the accuracy of urban positioning in mobile applications, without requiring high processing. A multipath model is derived to express the multipath effects on the auto-correlation function (ACF). The multipath model is a function in the code delay error, the multipath code delays, the multipath complex amplitudes, and the composite complex amplitude, which consists of the complex amplitudes of the Line-of-Sight (LOS) signal and all the existing multipath signals. 3D buildings model and an accelerated ray tracing algorithm are used to get predictions for the code delay error and the multipath code delays at a range of possible positions. The predicted parameters are used to estimate the multipath complex amplitudes and the composite complex amplitude using measured correlations. The predicted and the estimated parameters are plugged into the multipath model to get a predicted ACF, for each possible position. The idea is that if the predictions are correct, then the estimations will be correct, which will lead to a predicted ACF that closely match the measured ACF. Therefore, a consistency analysis is performed to measure the consistency between each predicted ACF and the measured ACF. The possible position with the highest consistency is taken as the estimated position. The proposed algorithm is called Correlation Prediction and Consistency Analysis (CPCA). The CPCA algorithm is verified using real GPS data collected in Hong Kong. The results show enhancement in urban position estimation compared to a conventional position estimation method and a vector tracking-based method.|
Proceedings of the 32nd International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2019)
September 16 - 20, 2019
Hyatt Regency Miami
|Pages:||3469 - 3483|
|Cite this article:||
Ziedan, Nesreen I., "Enhancing GNSS Mobile Positioning in Urban Environments through Utilization of Multipath Prediction and Consistency Analysis," Proceedings of the 32nd International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2019), Miami, Florida, September 2019, pp. 3469-3483.
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