Periodogram with varying and data-driven window length
Signal Processing
Adaptive Window Size Image De-noising Based on Intersection of Confidence Intervals (ICI) Rule
Journal of Mathematical Imaging and Vision
Signal-to-noise ratio estimation using higher-order moments
Signal Processing
Analysis of polynomial-phase signals by the integrated generalizedambiguity function
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
Spatially Adaptive Estimation via Fitted Local Likelihood Techniques
IEEE Transactions on Signal Processing
Performance analysis of the adaptive algorithm for bias-to-variance tradeoff
IEEE Transactions on Signal Processing
Product high-order ambiguity function for multicomponentpolynomial-phase signal modeling
IEEE Transactions on Signal Processing
The discrete polynomial-phase transform
IEEE Transactions on Signal Processing
Hi-index | 0.08 |
The short-time Fourier transform (STFT) based instantaneous frequency (IF) estimator has been used for polynomial phase signal (PPS) parameters estimation. This estimator is biased but it is less sensitive to the noise influence than the higher-order techniques such as the high-order ambiguity function (HAF). Here, we have developed a method for estimation of the optimal window width in the STFT for the PPS estimation. Obtained results are then refined with the strategy proposed recently by O'Shea. In this way the resulting estimates of parameters outperform the HAF based ones.