A Bayesian Algorithm for GNSS Time-Delay Estimation Using an Uncalibrated Array

This paper introduces a Bayesian algorithm designed for precise estimation of the propagation time delay in global navigation satellite systems (GNSS) signals, taking into account a multi-antenna setup with an uncalibrated antenna array. The algorithm utilizes the signal tensor model, specifically the parallel factor signal model (PARAFAC), to determine the time delay of each signal path. This approach minimizes the least squares error between the multidimensional data received and the PARAFAC model. The findings demonstrate that the proposed method significantly outperforms current state-of-the-art techniques, achieving submeter accuracy under certain conditions. In addition, the results exhibit good performance with time-correlated signals.