NDLI: Compound time-frequency domain method for estimating parameters of uniform-sampling polynomial-phase signals on the entire identifiable region

Content Provider	IET Digital Library
Author	Deng, Zhenmiao Xu, Rongrong Zhang, Yixiong Ye, Yishan
Abstract	Parameter estimation of polynomial-phase signals (PPSs) observed in additive white Gaussian noise (AWGN) is addressed. Most of the existing estimators cannot work on a fully identifiable region. Using the algebraic number theory, McKilliam et al. proposed a least squares unwrapping (LSU) estimator, which can operate on the entire identifiable region. However, its computational load may be large, especially when the number of samples is large. In this study, the authors first extend the amplitude-weighted phase-based estimator (AWPE) for sinusoidal and chirp signals to PPSs and derive a time domain maximum likelihood estimator. The performance is analysed and compared with the Cramér–Rao lower bound (CRLB). Then, the authors propose an iterative compound time-frequency domain parameter estimation method, which includes a coarse estimation step and a fine estimation step conducted by the discrete polynomial phase transform and AWPE estimator, respectively. Monte–Carlo simulations show that the proposed method can work on the entire identifiable region and that it outperforms the existing state-of-the-art estimators. Its computational complexity is considerably lower than that of the LSU estimator, while its threshold signal-to-noise ratio is a few decibels higher than that of the LSU estimator.
Starting Page	743
Ending Page	751
Page Count	9
ISSN	17519675
Volume Number	10
e-ISSN	17519683
Issue Number	Issue 7, Sep (2016)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-spr/10/7
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-spr.2015.0361
Journal	IET Signal Processing
Publisher Date	2016-09-01
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Additive White Gaussian Noise Channel Algebraic Number Theory Amplitude-weighted Phase-based Estimator AWGN AWPE Estimator Coarse Estimation Step Computational Complexity Cramér–Rao Lower Bound CRLB Discrete Polynomial Phase Transform Fine Estimation Step Interpolation And Function Approximation Iterative Compound Time-frequency Domain Parameter Estimation Method Iterative Method Least Squares Approximation Least Squares Unwrapping Estimator LSU Estimator Maximum Likelihood Estimation Monte Carlo Method Monte–Carlo Simulations Numerical Analysis Polynomial Approximation Polynomial-phase Signal PPS Signal Processing And Detection Signal Processing Theory Signal Sampling Threshold Signal-to-noise Ratio Time Domain Maximum Likelihood Estimator Time-frequency Analysis
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering

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