Advanced GNSS positioning for low-cost Android smartphones using RTS assisted extended Kalman filter

Global navigation satellite system (GNSS) is pervasively employed in smartphone location services. However, the positioning performance of low-cost Android smartphones is often limited by the sub-optimal quality of their GNSS observation data, impeding their ability to fulfil user demands. To address this need, this paper proposes an improved positioning algorithm using Rauch-Tung-Striebel and extended Kalman filter (RTS-EKF). This algorithm initially enhances the raw data quality through rigorous gross error detection and elimination, coupled with Doppler smoothing. Subsequently, the RTS-EKF algorithm is employed to estimate and smooth localisation results, ultimately enhancing positioning accuracy. To validate the effectiveness of this algorithm, dynamic experiment was conducted, yielding results that demonstrate horizontal positioning accuracy exceeding 1.9 metres and vertical positioning accuracy better than 7 metres. Compared with traditional positioning algorithms, the RTS-EKF exhibits at least a 15% improvement in localisation accuracy and superior performance, thereby satisfying the high-precision requirements of low-cost smartphone users.