Fundamentals of statistical signal processing: estimation theory
Fundamentals of statistical signal processing: estimation theory
Parameter estimation of a real single tone from short data records
Signal Processing
Clustering the wireless Ad Hoc networks: A distributed learning automata approach
Journal of Parallel and Distributed Computing
An efficient approach for two-dimensional parameter estimation of a single-tone
IEEE Transactions on Signal Processing
Reformulation of Pisarenko harmonic decomposition method for single-tone frequency estimation
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
Subspace Approach for Fast and Accurate Single-Tone Frequency Estimation
IEEE Transactions on Signal Processing
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The problem of single-tone frequency estimation for a discrete-time real sinusoid in white Gaussian noise is addressed. We first show that the frequency information is embedded in the principal singular vectors of a matrix which stores the observed data with no repeated entry. The technique of weighted least squares is then utilized for finding the frequency from the singular vectors. It is proved that the variance of the frequency estimate approaches Cramer-Rao lower bound when the data observation length tends to infinity. The computational efficiency and estimation accuracy are demonstrated via computer simulations.