A Refined Estimator of Multicomponent Third-Order Polynomial Phase Signals

GuoJian OU  ShiZhong YANG  JianXun DENG  QingPing JIANG  TianQi ZHANG  

Publication
IEICE TRANSACTIONS on Communications   Vol.E99-B   No.1   pp.143-151
Publication Date: 2016/01/01
Online ISSN: 1745-1345
DOI: 10.1587/transcom.2015EBP3131
Type of Manuscript: PAPER
Category: Fundamental Theories for Communications
Keyword: 
multicomponent third-order polynomial phase signals,  fast Fourier transformation (FFT),  moving average filter,  k-means algorithm,  singular value decomposition (SVD),  

Full Text: PDF(1.7MB)>>
Buy this Article




Summary: 
This paper describes a fast and effective algorithm for refining the parameter estimates of multicomponent third-order polynomial phase signals (PPSs). The efficiency of the proposed algorithm is accompanied by lower signal-to-noise ratio (SNR) threshold, and computational complexity. A two-step procedure is used to estimate the parameters of multicomponent third-order PPSs. In the first step, an initial estimate for the phase parameters can be obtained by using fast Fourier transformation (FFT), k-means algorithm and three time positions. In the second step, these initial estimates are refined by a simple moving average filter and singular value decomposition (SVD). The SNR threshold of the proposed algorithm is lower than those of the non-linear least square (NLS) method and the estimation refinement method even though it uses a simple moving average filter. In addition, the proposed method is characterized by significantly lower complexity than computationally intensive NLS methods. Simulations confirm the effectiveness of the proposed method.