Open AccessCoherently integrated cubic phase function for multiple LFM signals analysis
Author(s) -
Su Jia,
Tao Haihong,
Rao Xuan,
Xie Jian,
Guo Xiaolu
Publication year - 2015
Publication title -
electronics letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.375
H-Index - 146
eISSN - 1350-911X
pISSN - 0013-5194
DOI - 10.1049/el.2014.4164
Subject(s) - spurious relationship , identifiability , component (thermodynamics) , estimator , phase (matter) , noise (video) , algorithm , function (biology) , computer science , phase noise , mathematics , electronic engineering , physics , statistics , engineering , artificial intelligence , quantum mechanics , evolutionary biology , biology , image (mathematics) , thermodynamics
The cubic phase function (CPF) based estimator is efficient in estimating the parameters for mono‐component linear frequency‐modulated (LFM) signals. However, it suffers from cross‐terms and spurious peaks when dealing with multi‐component LFM signals. Aimed at this identifiability problem, a coherently integrated CPF (CICPF) algorithm is proposed to enhance the auto‐terms and suppress spurious peaks. Comparisons with several existing algorithms are made, which show that the CICPF not only solve the identifiability problem for multi‐component LFM signals, but also acquires high anti‐noise performance.