NDLI: Quasi-maximum-likelihood estimator of polynomial phase signals

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Volume 8 (2014) : Issue 3, May

Volume 8 (2014) : Issue 2, Apr

Volume 8 (2014) : Issue 1, Feb

IET Wireless Sensor Systems

Micro & Nano Letters

The Journal of Engineering

Quasi-maximum-likelihood estimator of polynomial phase signals

Content Provider	IET Digital Library
Author	Djurović, Igor Stanković, Ljubiša
Abstract	A novel approach for the parameter estimation of the polynomial phase signals (PPS) based on the short-time Fourier transform (STFT) is proposed. Estimator accuracy is significantly higher compared to the high-order ambiguity function (HAF), product HAF, and similar the non-linear transforms based strategies. The proposed approach is more efficient than the maximum likelihood (ML) estimator for the high-order PPS. One-dimensional search is performed over a set of window widths in the STFT, whereas in the case of ML estimators, it has been done over the space of phase parameters. The proposed estimator is implemented in several steps: the instantaneous frequency (IF) estimation using the STFT for various window widths; a polynomial regression from the IF estimate producing a coarse signal coefficients estimate; refinement procedure, producing fine coefficients estimates; determination of the optimal window width in the STFT. The proposed technique is extended for the non-parametric estimation with a 2D search over a set of polynomial orders and window widths. Good estimation results are achieved up to the SNR threshold of about SNR=0 dB for the parametric case and SNR=2 dB for the non-parametric case.
Starting Page	347
Ending Page	359
Page Count	13
ISSN	17519675
Volume Number	8
e-ISSN	17519683
Issue Number	Issue 4, Jun (2014)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-spr/8/4
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-spr.2013.0104
Journal	IET Signal Processing
Publisher Date	2013-10-08
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Algebra Fourier Transforms HAF High-order Ambiguity Function Integral Transforms Maximum Likelihood Estimation Maximum Likelihood Estimator ML Estimator Nonlinear Transforms Optimal Window Parameter Estimation Polynomial Polynomial Orders Polynomial Phase Signal Polynomial Regression PPS Quasimaximum Likelihood Estimator Refinement Procedure Regression Analysis Short-time Fourier Transform Signal Coefficient Estimation Signal Processing Signal Processing And Detection Signal Processing Theory Signal to Noise Ratio SNR Statistics STFT
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering

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