Decimative subspace-based parameter estimation techniques
Signal Processing
Near optimum sampling design and an efficient algorithm for single tone frequency estimation
Digital Signal Processing
Effects of sampling and quantization on single-tone frequencyestimation
IEEE Transactions on Signal Processing
Unitary ESPRIT: how to obtain increased estimation accuracy with areduced computational burden
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
Amplitude estimation of sinusoidal signals: survey, new results,and an application
IEEE Transactions on Signal Processing
Iterative filtering for multiple frequency estimation
IEEE Transactions on Signal Processing
Variance of least squares estimators for a damped sinusoidalprocess
IEEE Transactions on Signal Processing
The most efficient implementation of the IQML algorithm
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
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The problem of oversampling parameter estimation for noisy sinusoidal signals is addressed. We first extend the weighted least squares (WLS) approach to the complex sinusoids. Then the oversampling weighted least squares (OSWLS) estimator is proposed based on data decimation. Estimation performance of the OSWLS method is analyzed via theoretical and simulation studies. Results are also compared to those of the WLS and decimative unitary ESPRIT methods as well as Cramer-Rao lower bound.