Document Type thesis Author Name Liao, Yizheng Email Address liaoyizheng at wpi.edu URN etd-042511-144644 Title Phase and Frequency Estimation: High-Accuracy and Low- Complexity Techniques Degree MS Department Electrical & Computer Engineering Advisors Donald R. Brown III, Advisor John A. McNeill, Committee Member Andrew G. Klein, Committee Member Keywords real-time signal processing frequency estimation phase estimation maximum likelihood estimation FFT-based estimation zero-crossing detection Date of Presentation/Defense 2011-04-25 Availability unrestricted
The estimation of the frequency and phase of a complex exponential in additive white Gaussian noise (AWGN) is a fundamental and well-studied problem in signal processing and communications. A variety of approaches to this problem, distinguished primarily by estimation accuracy, computational complexity, and processing latency, have been developed. One class of approaches is based on the Fast Fourier Transform (FFT) due to its connections with the maximum likelihood estimator (MLE) of frequency. This thesis compares several FFT-based approaches to the MLE in terms of their estimation accuracy and computational complexity. While FFT-based frequency estimation tends to be very accurate, the computational complexity of the FFT and the latency associated with performing these computations after the entire signal has been received can be prohibitive in some scenarios. Another class of approaches that addresses some of these shortcomings is based on linear regression of samples of the instantaneous phase of the observation. Linear- regression-based techniques have been shown to be very accurate at moderate to high signal to noise ratios and have the additional benefit of low computational complexity and low latency due to the fact that the processing can be performed as the samples arrive. These techniques, however, typically require the computation of four-quadrant arctangents, which must be approximated to retain low computational complexity. This thesis proposes a new frequency and phase estimator based on simple estimates of the zero-crossing times of the observation. An advantage of this approach is that it does not require arctangent calculations. Simulation results show that the zero-crossing frequency and phase estimator can provide high estimation accuracy, low computational complexity, and low processing latency, making it suitable for real-time applications. Accordingly, this thesis also presents a real-time implementation of the zero-crossing frequency and phase estimator in the context of a time-slotted round-trip carrier synchronization system for distributed beamforming. The experimental results show this approach can outperform a Phase Locked Loop (PLL) implementation of the same distributed beamforming system.
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