scholarly journals Compressed Sensing Reconstruction of Radar Echo Signal Based on Fractional Fourier Transform and Improved Fast Iterative Shrinkage-Thresholding Algorithm

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Rui Zhang ◽  
Chen Meng ◽  
Cheng Wang ◽  
Qiang Wang
Keyword(s):  
Fourier Transform ◽  
Compressed Sensing ◽  
Fractional Fourier Transform ◽  
Radar Signal ◽  
Reconstruction Algorithms ◽  
Echo Signal ◽  
Time Frequency ◽  
Iterative Shrinkage ◽  
Radar Echo ◽  
Iterative Shrinkage Thresholding

The compressed sensing theory, which has received great attention in the field of radar technology, can effectively reduce the data rate of high-resolution radar imaging systems and solve the problem of collecting, storing, and transmitting large amounts of data in radar systems. Through the study of radar signal processing theory, it can be found that the echo of radar LFM transmit signal has sparse characteristics in the distance upward; based on this, we can consider using the theory of compressed sensing in the processing of radar echo to optimize the processing. In this paper, a fast iterative shrinkage-thresholding reconstruction algorithm based on protection coefficients is proposed. Under the new scheme, firstly, the LFM echo signal’s good sparse representation is obtained by using the time-frequency sparse characteristics of the LFM echo signal under the fractional Fourier transform; all reconstruction coefficients are analyzed in the iterative process. Then, the coefficients related to the feature will be protected from threshold shrinkage to reduce information loss. Finally, the effectiveness of the proposed method is verified through simulation experiments and application example analysis. The experimental results show that the reconstruction error of this method is lower and the reconstruction effect is better compared with the existing reconstruction algorithms.

scholarly journals Nyquist Zone Index and Chirp Rate Estimation of LFM Signal Intercepted by Nyquist Folding Receiver Based on Random Sample Consensus and Fractional Fourier Transform

Sensors ◽  
2019 ◽  
Vol 19 (6) ◽  
pp. 1477 ◽  
Author(s):  
Xinqun Liu ◽  
Tao Li ◽  
Xiaolei Fan ◽  
Zengping Chen
Keyword(s):  
Fourier Transform ◽  
Random Sample ◽  
Fractional Fourier Transform ◽  
Estimation Method ◽  
Ultra Wideband ◽  
Estimation Methods ◽  
Radar Signal ◽  
Chirp Rate ◽  
Time Frequency ◽  
Random Sample Consensus

The Nyquist folding receiver (NYFR) can achieve a high-probability interception of an ultra-wideband (UWB) signal with fewer devices, while the output of the NYFR is converted into a hybrid modulated signal of the local oscillator (LO) and the received signal, which requires the matching parameter estimation methods. The linear frequency modulation (LFM) signal is a typical low probability of intercept (LPI) radar signal. In this paper, an estimation method of both the Nyquist Zone (NZ) index and the chirp rate for the LFM signal intercepted by NYFR was proposed. First, according to the time-frequency characteristics of the LFM signal, the accurate NZ and the rough chirp rate was estimated based on least squares (LS) and random sample consensus (RANSAC). Then, the information of the LO was removed from the hybrid modulated signal by the known NZ, and the precise chirp rate was obtained by using the fractional Fourier transform (FrFT). Moreover, a fast search method of FrFT optimal order was presented, which could obviously reduce the computational complexity. The simulation demonstrated that the proposed method could precisely estimate the parameters of the hybrid modulated output signal of the NYFR.

scholarly journals Compressed Sensing Imaging for Staggered SAR with Low Oversampling Rate

2020 ◽  
Author(s):  
Xingxing Liao ◽  
Changlin Jin ◽  
Zhe Liu
Keyword(s):  
Fourier Transform ◽  
Compressed Sensing ◽  
Synthetic Aperture Radar ◽  
Fast Fourier Transform ◽  
Synthetic Aperture ◽  
Data Simulation ◽  
Iterative Shrinkage ◽  
Simulation Results ◽  
Thresholding Algorithm ◽  
Iterative Shrinkage Thresholding

This paper focuses on processing low oversampling echo data of staggered synthetic aperture radar (SAR). In staggered mode, the non-uniformly sampling and irregular loss of echo data cause azimuth ambiguity which severely degrades the imaging quality. To solve this problem, we propose a compressed sensing (CS) method in which the non-uniform fast Fourier transform (NUFFT) technique is adopted to obtain uniform azimuth spectrum, and the fast iterative shrinkage thresholding algorithm (FISTA) is utilized to efficiently reconstruct the ambiguity-free image from in-complete echo data. Simulation results demonstrate the proposed method can effectively suppress the azimuth ambiguity in the vicinity of targets.

LFM Signal Detection Method Based on Fractional Fourier Transform

2014 ◽  
Vol 989-994 ◽  
pp. 4001-4004 ◽  
Author(s):  
Yan Jun Wu ◽  
Gang Fu ◽  
Yu Ming Zhu
Keyword(s):  
Fourier Transform ◽  
Signal Detection ◽  
Frequency Analysis ◽  
Experimental Analysis ◽  
Fractional Fourier Transform ◽  
Detection Method ◽  
Time Frequency Analysis ◽  
Time Frequency ◽  
Frequency Information ◽  
Strong Impulse

As a generalization of Fourier transform, the fractional Fourier Transform (FRFT) contains simultaneity the time-frequency information of the signal, and it is considered a new tool for time-frequency analysis. This paper discusses some steps of FRFT in signal detection based on the decomposition of FRFT. With the help of the property that a LFM signal can produce a strong impulse in the FRFT domain, the signal can be detected conveniently. Experimental analysis shows that the proposed method is effective in detecting LFM signals.

scholarly journals An Inverse Synthetic Aperture Ladar Imaging Algorithm of Maneuvering Target Based on Integral Cubic Phase Function-Fractional Fourier Transform

Electronics ◽  
2018 ◽  
Vol 7 (8) ◽  
pp. 148 ◽  
Author(s):  
Yakun Lv ◽  
Yanhong Wu ◽  
Hongyan Wang ◽  
Lei Qiu ◽  
Jiawei Jiang ◽  
...  
Keyword(s):  
Fourier Transform ◽  
Phase Function ◽  
Fractional Fourier Transform ◽  
Doppler Frequency ◽  
Synthetic Aperture ◽  
Cubic Phase ◽  
Echo Signal ◽  
Imaging Algorithm ◽  
Maneuvering Target ◽  
Cubic Phase Function

When imaging maneuvering targets with inverse synthetic aperture ladar (ISAL), dispersion and Doppler frequency time-variation exist in the range and cross-range echo signal, respectively. To solve this problem, an ISAL imaging algorithm based on integral cubic phase function-fractional Fourier transform (ICPF-FRFT) is proposed in this paper. The accurate ISAL echo signal model is established for a space maneuvering target that quickly approximates the uniform acceleration motion. On this basis, the chirp rate of the echo signal is quickly estimated by using the ICPF algorithm, which uses the non-uniform fast Fourier transform (NUFFT) method for fast calculations. At the best rotation angle, the range compression is realized by FRFT and the range dispersion is eliminated. After motion compensation, separation imaging of strong and weak scattering points is realized by using ICPF-FRFT and CLEAN technique and the azimuth defocusing problem is solved. The effectiveness of the proposed method is verified by a simulation experiment of an aircraft scattering point model and real data.

Power Quality Disturbance Research of Grid-Connected Wind Generation Based on Fractional Fourier Transform with Wavelet Entropy

2011 ◽  
Vol 130-134 ◽  
pp. 1600-1604
Author(s):  
Hua Li Chen ◽  
Yun Lian Sun
Keyword(s):  
Fourier Transform ◽  
Power System ◽  
Power Quality ◽  
Fractional Fourier Transform ◽  
Wind Generation ◽  
Wavelet Entropy ◽  
Time Frequency ◽  
System A ◽  
Power Quality Disturbance ◽  
Simulation Results

In the process of connected wind generation with the power grid, the classification and recognition of power quality disturbance signals which are researched by the scholars at home and abroad are always the hot issues in Power System. A new method using Fractional Fourier Transform (FRFT) with Wavelet Entropy is presented for recognizing the signals of PQ disturbance based on the characteristics of power quality (PQ) signals. FRFT have better time-frequency aggregation and can choose better domain instead of and make PQ disturbance recognize more accurately with wavelet entropy. Simulation results demonstrate its effectiveness.

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