Detection of low observable moving target in sea clutter via fractal characteristics in fractional Fourier transform domain. Issue 6 (1st July 2013)

• Record Type: Journal Article
• Authors: Chen, Xiaolong; Guan, Jian; He, You; Zhang, Jian
• Is Part Of: IET radar, sonar & navigation. Volume 7:Issue 6(2013)
• Page Start: 635
• Page End: 651
• Publication Date: 2013-07-01
• Subjects: Brownian motion -- curve fitting -- Fourier transforms -- fractals -- marine radar -- object detection -- radar clutter -- radar detection -- radar signal processing -- remote sensing by radar -- statistical analysis; observable moving target detection -- sea clutter -- fractal characteristics -- remote sensing -- radar signal processing -- nonGaussian characteristic -- statistics based detector -- intelligent pixel sea clutter data -- fractional Fourier transform -- FRFT domain -- fractional Brownian motion model -- self‐similarity property -- scale invariant interval -- fractal statistics -- fractal dimension -- fractal curve -- fractal fitting error -- FD variance; Signal processing -- Periodicals; Radar -- Periodicals; Sonar -- Periodicals; Electronics in navigation -- Periodicals; Navigation -- Periodicals; 621.3848
• DOI: 10.1049/iet-rsn.2012.0116
• Languages: English
• ISSNs: 1751-8784

Abstract

Abstract : 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.