Analysis of Parameter Estimation Using Pei Algorithm of FRFT

2014 ◽  
Vol 577 ◽  
pp. 758-761
Author(s):  
Bing Deng
Keyword(s):  
Fourier Transform ◽  
Parameter Estimation ◽  
Fractional Fourier Transform ◽  
Estimation Accuracy ◽  
Chirp Signal ◽  
Factors Influencing

Parameter estimation of chirp signal is analyzed using Pei algorithm of FRFT (Fractional Fourier Transform). Firstly, the model of parameter estimation has been made. Secondly, the factors influencing the estimation accuracy have been analyzed. Finally, the simulation has been made to verify the conclusions.

Detection and Parameter Estimation for Chirp Signal Based on Fractional Fourier Transform

2014 ◽  
Vol 599-601 ◽  
pp. 1474-1477
Author(s):  
Xin Chen ◽  
Min Tao ◽  
Tian Tang Pan ◽  
Yan Li
Keyword(s):  
Parameter Estimation ◽  
Fractional Fourier Transform ◽  
Estimation Algorithm ◽  
Wave Parameter ◽  
Estimation Accuracy ◽  
Radar Signal ◽  
Chirp Signal ◽  
Computation Complexity ◽  
Maximum Value ◽  
Radar Echo

The Chirp signal has been used widely in radar signal, radar echo wave can established to be Chirp model. The estimation of radar echo wave parameter is a important task in radar signal processing. In this paper, we introduced three theories and algorithms of detection and estimation of Chirp signal: 2D peak searching algorithm, two steps searching of maximum value algorithm and pre-estimation algorithm firstly. The parameter estimation precision and computation complexity in low SNR was simulated for these three algorithms. The final simulation indicate that the two steps searching algorithm of maximum value take on nice estimation accuracy and low computation complexity in contrast.

Detection and Parameter Estimation of Chirp Signal Based on Time-Frequency Analysis

2014 ◽  
Vol 989-994 ◽  
pp. 3989-3992
Author(s):  
Guang Zhi Wu ◽  
Gang Fu ◽  
Yan Jun Wu
Keyword(s):  
Fourier Transform ◽  
Parameter Estimation ◽  
Fractional Fourier Transform ◽  
Chirp Signal ◽  
Wigner Transform ◽  
Time Frequency ◽  
The Relationship ◽  
Generic Time ◽  
Time Frequency Distribution ◽  
Better Than

Based on the relationship between the Radon-Wigner transform and fractional Fourier transform and the time frequency distribution, using the property that Radon-Wigner transform has better performance in time and frequency domain, detection and parameter estimation of Chirp signal have been done by Radon-Wigner transform or fractiona1 Fourier transform. The theoretica1 analysis and simulation prove that two techniques are better than generic time-frequency transform, such as Wigner-Ville transform.

scholarly journals Chirp Signal Denoising Based on Convolution Neural Network

2020 ◽  
Author(s):  
Ben Guangli ◽  
Xifeng Zheng ◽  
Yongcheng Wang ◽  
Xin Zhang ◽  
Ning Zhang
Keyword(s):  
Neural Network ◽  
Parameter Estimation ◽  
Estimation Algorithm ◽  
Estimation Accuracy ◽  
Chirp Signal ◽  
Signal Processing Algorithm ◽  
Low Snr ◽  
Result Show ◽  
Parameter Estimation Algorithm ◽  
Two Parameter

Abstract Many classical chirp signal processing algorithm may experience distinct performance decrease in noise circumstance. To address the problem, this paper proposes a deep learning based approach to filter noises in time domain. The proposed denoising convolutional neural network (DCNN) is trained to recover the original clean chirps from observation signals with noises. Following denosing, we employ two parameter estimation algorithm to DCNN output. Simulation result show that the proposed DCNN method improves the signal noise ratio (SNR) and parameter estimation accuracy to a great extent compared to the signals without denoising. And DCNN have a strong adaptability of low SNR input scenarios that never trained.

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