Open AccessDetection of low observable moving target in sea clutter via fractal characteristics in fractional Fourier transform domain
Author(s) -
Chen Xiaolong,
Guan Jian,
He You,
Zhang Jian
Publication year - 2013
Publication title -
iet radar, sonar and navigation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.489
H-Index - 82
eISSN - 1751-8792
pISSN - 1751-8784
DOI - 10.1049/iet-rsn.2012.0116
Subject(s) - clutter , fractal , fractional fourier transform , fourier transform , domain (mathematical analysis) , fourier domain , discrete fourier transform (general) , observable , frequency domain , physics , mathematics , mathematical analysis , computer science , fourier analysis , radar , telecommunications , quantum mechanics
Effective detection of low observable moving target at sea is important for remote sensing and radar signal processing. The non‐Gaussian property of sea clutter and lack of accurate model make the detection difficult for statistics based detectors. Also the fractal techniques in time domain cannot achieve high detection probability in heavy sea clutter. To help solve the problems, fractal characteristics of IPIX datasets in fractional Fourier transform (FRFT) domain are analysed making use of the fluctuation of FRFT amplitudes and moving target detection algorithms are proposed based on the fractal characteristics in FRFT domain. Firstly, fractal model in FRFT domain is established with fractional Brownian motion model and two judgment and extraction methods are employed for calculating the fractal characteristics in FRFT domain. It is found that sea clutter of different polarisations exhibit fractal behaviours in FRFT domain, that is, self‐similarity property, within its corresponding scale‐invariant interval. Then, we find that four specific fractal statistics in the best FRFT domain can provide valuable information for developing simple and effective detectors. Finally, traditional amplitude detector and Hurst exponent detector in time domain are compared and the results prove the superior detection ability of low observable moving target without complex computations.