GNSS-5G-SINS Resilient Integrated Navigation Algorithm for Indoor and Outdoor Seamless Environment

Abstract

At present, the accuracy and reliability of Global Navigation Satellite Systems (GNSS) in complex environments have not been able to meet the demands of seamless location services both indoors and outdoors. The 5G cellular network provides technical characteristics of ultra-dense networking, large bandwidth, and large-scale array antenna, which can offer wide-area and high-precision information on Time of Arrival (ToA) and Angle of Arrival (AoA). This paper proposes an adaptive integrated navigation algorithm based on a federated Kalman filter, integrating three sensors-GNSS/5G base station/Strap-down Inertial Navigation System (GNSS-5G-SINS) - to resolve the signal blocking issue in the indoor-outdoor transition environment. To overcome frequent out-of-lock and non-line-of-sight errors of the satellite in the indoor-outdoor seamless environment, this algorithm realizes the tight combination of observed values in the sub-filter and designs a fault detection and processing module to suppress the influence of abnormal observed values on the system. Finally, the main filter fuses information from each sub-filter and distributes dynamic information according to the quality of observed values. Experimental tests demonstrate that the proposed scheme improves the accuracy and stability of the navigation system. Under the partial lock-out of the satellite, the proposed algorithm reduces the positioning error by 68% compared with the GNSS-SINS compact combination, and the Root Mean Square Error (RMSE) reached 0.37m in the indoor environment. These results indicate that the new 5G technology has the potential to offer relatively high precision positioning services.