Paper Info
Title
Radar High-Speed Target Detection Based on the Scaled Inverse Fourier Transform
Abstract
In this paper, by employing the symmetric autocorrelation function and the scaled inverse Fourier transform (SCIFT), a coherent detection algorithm is proposed for high-speed targets. This coherent detection algorithm is simple and can be easily implemented by using complex multiplications, the fast Fourier transform (FFT) and the inverse FFT (IFFT). Compared to the Hough transform and the keystone transform, this coherent detection algorithm can detect high-speed targets without the brute-force searching of unknown motion parameters and achieve a good balance between the computational cost and the antinoise performance. Through simulations and analyses for synthetic models and the real data, we verify the effectiveness of the proposed coherent detection algorithm.
Year
DOI
Venue
2015
10.1109/JSTARS.2014.2368174
Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of  
Keywords
Field
DocType
object detection,remote sensing by radar,hough transform,antinoise performance,brute-force searching,coherent detection algorithm,computational cost,fast fourier transform,keystone transform,motion parameters,radar high-speed target detection,scaled inverse fourier transform,symmetric autocorrelation function,coherent detection,fast fourier transform (fft),inverse fast fourier transform (ifft),scaled inverse fourier transform (scift),algorithm design and analysis,coherence
Computer vision,Non-uniform discrete Fourier transform,Harmonic wavelet transform,Split-radix FFT algorithm,Prime-factor FFT algorithm,Short-time Fourier transform,Artificial intelligence,Discrete Fourier transform,Hartley transform,Fractional Fourier transform,Mathematics
Journal
Volume
Issue
ISSN
8
3
1939-1404
Citations 
PageRank 
References 
14
0.62
18
Authors
5
Name
Order
Citations
PageRank
Jibin Zheng113112.74
Tao Su2805.67
wentao zhu3233.94
Xuehui He4302.57
Q. Liu529271.17