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).

Phase Error Criterion Based Adaptive Algorithm for Frequency Estimation

“…Adaptive method-based frequency estimation can be found in many areas of digital signal processing applications [1,2], such as Doppler efect estimation of radar and sonar systems [3][4][5], clock and carrier synchronization in communication systems, angle of arrival estimation in smart antenna systems, frequency estimation in global navigation satellite systems (GNSS) [6], angle and frequency estimation in cognitive wireless systems [7][8][9], and so on. Depending on the statistical properties of the input signal frequency, say, deterministic or random, the frequency estimation can be classifed into two categories: block-based and sequentialbased estimation techniques.…”