Autocorrelation-based algorithm for single-frequency estimation
Signal Processing
Analysis of Multicomponent Polynomial Phase Signals
IEEE Transactions on Signal Processing
Aliasing of polynomial-phase signal parameters
IEEE Transactions on Signal Processing
Product high-order ambiguity function for multicomponentpolynomial-phase signal modeling
IEEE Transactions on Signal Processing
Estimation of frequency, amplitude, and phase from the DFT of atime series
IEEE Transactions on Signal Processing
IEEE Transactions on Information Theory
IEEE Transactions on Information Theory
Estimation and classification of polynomial-phase signals
IEEE Transactions on Information Theory
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A novel method for aliasing detection and resolving in the estimation of polynomial-phase signal (PPS) parameters is presented. Aliasing is detected using two high-order ambiguity functions (HAFs) of a uniformly sampled PPS embedded in noise. If aliasing occurred, we propose a way of recovering the true parameters from their aliased positions. To that end, a closed-form expression for the true parameter value is derived. As opposed to the concurrent methods, the proposed method provides much more robust results with higher order PPSs and does not require nonuniform sampling. In addition, it can be readily extended to the multicomponent PPS case. Simulations support the theoretical results.