Expectation Maximization Algorithm for GPS Positioning in Multipath Environments Based on Volterra Series.

The multipath effect error (MEE) is typically not taken into account by the RTKLIB localization method, and this may lead to poor positioning accuracy. This paper proposes an expectation maximization (EM) algorithm for GPS positioning based on Volterra series, and the pseudoranges contaminated by MEE are considered as missing data. Firstly, the Volterra series is introduced to linearize the pseudorange equation. Then, the EM algorithm is used to iteratively update the user location and missing data. Compared with the RTKLIB method, the proposed algorithm has more accurate positioning accuracy. The simulation example shows the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]