5G/GNSS Integrated Vehicle Localization with Adaptive Step Size Kalman Filter

被引：0

作者：

Guo G. ^{[1
]}

Sun X. ^{[2
]}

Liu J. ^{[2
]}

机构：

[1] State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Shenyang

[2] College of Information Science and Engineering, Northeastern University, Shenyang

来源：

IEEE Transactions on Vehicular Technology | 2024年 / 73卷 / 11期

基金：

中国国家自然科学基金;

关键词：

5G; 5G mobile communication; Accuracy; Adaptation models; adaptive step size; GNSS; Gyroscopes; Kalman filter; Location awareness; Size measurement; Uncertainty; vehicle localization;

D O I：

10.1109/TVT.2024.3421383

中图分类号：

学科分类号：

摘要：

This paper investigates an adaptive step size Kalman filter for 5G/GNSS integrated positioning of land-vehicles to deal with model uncertainties and multi-frequency measurements. A set of system and measurement models are established including a nonlinear dynamic vehicle model as the prediction model for the fusion filter. A robust stepwise fusion method is introduced to address model uncertainties, which is based on an adaptive Kalman filter with a step size adaptation mechanism involved to deal with multi-frequency measurements. The resulted fusion-based localization algorithm achieves a balance of positioning accuracy and computational cost. Both simulation and experimental results demonstrate that the proposed method outperforms the state-of-the-art methods in urban environments. IEEE

引用

页码：1 / 10

页数：9

5G&#x002F;GNSS Integrated Vehicle Localization with Adaptive Step Size Kalman Filter

5G/GNSS Integrated Vehicle Localization with Adaptive Step Size Kalman Filter