Frequency acquisition and tracking in high dynamic environments

This paper presents mean squared error (MSE) analysis of two classes of frequency acquisition and tracking algorithms. Additive white Gaussian noise as well as Rician fading channels are considered. The class of batch-processing algorithms is an extension of earlier least squares proposals used in more benign (lower dynamic) environments. These algorithms try to fit the phase trajectory of the down-converted samples of a received signal. Such a trajectory will depend on the histories of both the signal and the local frequency variations when the local frequency is updated recursively. We propose a method to solve this difficulty and present both first-order and second-order recursive algorithms. Numerical results demonstrate that the MSE performance predicted by our analysis is consistent with that estimated by computer simulation and that the proposed algorithms not only provide rapid acquisition times but also give small tracking jitters