Two-Step Frequency Estimation of GNSS Signal in High-Dynamic Environment

Abstract

To improve frequency accuracy which is affected by two parameters in high-dynamic acquisition, we propose a two-step frequency estimation method based on the mean frequency (MF) model for high-dynamic parameters estimation. The first step is based on the discrete chirp-Fourier transform (DCFT) for coarse MF estimation, where the MF accuracy and frequency search step are derived. In the second step, the maximum likelihood estimation process (MLEP) is adopted for fine MF estimation. Compared with state-of-art methods, it is verified that the two-step method can improve the detection probability in coarse MF estimation and improve the MF accuracy with low computational burdens under conditions with a moderate signal-to-noise ratio (SNR).