Open AccessSegmented discrete polynomial‐phase transform with coprime sampling
Author(s) -
Liu Shengheng,
Ma Yahui,
Shan Tao
Publication year - 2019
Publication title -
the journal of engineering
Language(s) - English
Resource type - Journals
ISSN - 2051-3305
DOI - 10.1049/joe.2019.0312
Subject(s) - chirp , segmentation , polynomial , computer science , coprime integers , algorithm , sampling (signal processing) , ambiguity , phase (matter) , mathematics , artificial intelligence , pattern recognition (psychology) , computer vision , physics , optics , mathematical analysis , laser , filter (signal processing) , quantum mechanics , programming language
Segmented discrete polynomial‐phase transform (DPT) integrates input signals to enable detection and parameter estimation of weak linear frequency modulated (LFM) signals. However, conventional DPT approaches suffer from a low unambiguously detectable range of the chirp rates because the segmentation effectively reduces the sampling rate between adjacent segments. To enable unique detection of LFM signals with a high chirp rate estimation, the authors propose the use of multiple segmentation sets where the respective segment lengths are governed by a coprime relationship. As such, the ambiguity of the estimated chirp rates that arise from a single segmentation set is eliminated through the fusion of the multiple segmentation sets using the Chinese Remainder Theorem. The effectiveness of the proposed method for the estimation of LFM signals with a high chirp rate is validated by simulation results.