Periodogram with varying and data-driven window length
Signal Processing
The self-duality of discrete short-time Fourier transform and its applications
IEEE Transactions on Signal Processing
Robust time-frequency distributions with complex-lag argument
EURASIP Journal on Advances in Signal Processing - Special issue on robust processing of nonstationary signals
Hybrid FM-polynomial phase signal modeling: parameter estimationand Cramer-Rao bounds
IEEE Transactions on Signal Processing
Improved estimation of hyperbolic frequency modulated chirp signals
IEEE Transactions on Signal Processing
The Cramer-Rao lower bound for signals with constant amplitude andpolynomial phase
IEEE Transactions on Signal Processing
Modification of the ICI rule-based IF estimator for high noise environments
IEEE Transactions on Signal Processing
STFT-based estimator of polynomial phase signals
Signal Processing
| Hi-index | 0.08 |
This paper presents a fast and robust method for estimating the starting frequency and period slope of hyperbolic frequency modulated (HFM) signals. The method involves, first, the instantaneous frequency (IF) estimation of HFM signals based on the peak of short-time Fourier transform (STFT) and, second, taking reciprocal of the estimated IF to get the zero crossing interval (ZCI). Parameter estimation of HFM signals is then achieved by using iteratively reweighted least squares (IRLS) linear fitting method to fit the ZCI which is a linear function of time. Both the approximate analysis of the magnitude spectrum and the formula used to determine the window length of STFT are derived for HFM signals. The lower bound of the estimator's variance and bias of the parameters of HFM signals are also derived in order to compare the performance of the proposed method. At last, both the simulation results and processing of sea trial data are presented to justify the validity and feasibility of the proposed method.