DocumentCode :
2279032
Title :
The improved parameter estimation method based on fractional fourier transform
Author :
Zhang, Chunjie ; Ren, Lili ; Li, Na
Author_Institution :
Coll. of Inf. & Commun. Eng., Harbin Eng. Univ., Harbin, China
Volume :
3
fYear :
2011
fDate :
10-12 June 2011
Firstpage :
11
Lastpage :
15
Abstract :
For the parameter estimation of linear frequency modulated (LFM) signal, this paper presents an improved arithmetic which is based on fractional Fourier transform (FRFT). Firstly, this paper analyzes the shortcomings of previous methods. Then, according to the characteristics of the LFM signal, a method based on fast Fourier transform (FFT) is used to estimate the coarse chirp rate. Secondly, by analyzing the redundancy of FRFT decomposition, reduced fractional Fourier transform (RFRFT) algorithm is proposed. Then, it develops relationship of signal parameter before and after normalization. Thirdly, it presents a more effective method based on FRFT to implement the parameter estimation of LFM signal. This improved arithmetic enhances the speed of calculation greatly. Finally, simulation results validate the method is able to suppress the noise and cross-terms in lower Signal-to-Noise Ratio (SNR).Comparing with the traditional FRFT, this method has a good performance to match multi-component LFM signals.
Keywords :
fast Fourier transforms; frequency modulation; parameter estimation; signal denoising; FRFT decomposition; LFM signal; coarse chirp rate; fast Fourier transform; improved parameter estimation method; linear frequency modulated signal; noise suppression; reduced fractional Fourier transform algorithm; signal-to-noise ratio; Chirp; Estimation; Fourier transforms; Frequency estimation; Signal to noise ratio; Time frequency analysis; fast Fourier transform; fractional Fourier transform; linear frequency modulated signal; parameter estimation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Science and Automation Engineering (CSAE), 2011 IEEE International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-8727-1
Type :
conf
DOI :
10.1109/CSAE.2011.5952624
Filename :
5952624
Link To Document :
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