Title :
Radar High-Speed Target Detection Based on the Scaled Inverse Fourier Transform
Author :
Jibin Zheng ; Tao Su ; Wentao Zhu ; Xuehui He ; Qing Huo Liu
Author_Institution :
Nat. Lab. of Radar Signal Process., Xidian Univ., Xi´an, China
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.
Keywords :
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; Algorithm design and analysis; Coherence; Computational efficiency; Object detection; Radar detection; Transforms; Coherent detection; fast Fourier transform (FFT); inverse fast Fourier transform (IFFT); scaled inverse Fourier transform (SCIFT); symmetric autocorrelation function;
Journal_Title :
Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of
DOI :
10.1109/JSTARS.2014.2368174