Robust BDS/5G integrated positioning based on resilient observation model

Abstract

The integration of BeiDou System (BDS) and the fifth generation (5G) system is expected to provide positioning services with high accuracy and reliability. In particular, as an important technique in the 5G system, device-to-device (D2D) communication enables the cooperative positioning for the mobile users (MUs) to offer a large number of redundant measurements, where the received signal strength (RSS) measurement can be exploited due to its easy access and cost-efficiency. However, the RSS measurements cannot be accurately modelled to reflect the propagation distances. In this paper, a robust BDS/5G integrated positioning scheme based on the resilient observation model is proposed. Specifically, the extended Kalman filter (EKF) is exploited to recursively integrate the BDS pseudorange and RSS measurements to estimate the unknown position parameters. We establish a resilient observation model based on the signal propagation model in the 5G network, through which the errors in the RSS measurements are compensated for by the BDS pseudorange measurements. Moreover, the effects of the abnormal errors in both kinds of the measurements are controlled by the robust estimation through automatically adjusting the weights of the measurements. Numerical results show that the proposed resilient observation model can correct part of the errors in the RSS measurements and results in higher positioning accuracy compared to the positioning based on the RSS measurements or the direct integration of both the BDS pseudorange and RSS measurements in different scenarios. The proposed algorithm also outperforms the positioning based on the BDS pseudorange measurements when the visible satellites are not sufficient.