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Design and analysis of fractal detector for high resolution radars

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  • Salmasi, Mehrdad
  • Modarres-Hashemi, M.

Abstract

Recently, fractal geometry has been used as a tool for improving the detection of targets in radar systems. The fractal dimension is utilized as a feature to distinguish between target and clutter in fractal detectors. In this paper, a general model is proposed for the target and clutter signals in high resolution radar (HRR). The fractal dimensions of the clutter and the target plus clutter are evaluated. Performing statistical tests on the distribution of the fractal dimension, it is proved that a gaussian distribution can approximately model the distribution of the fractal dimension for HRR signals. The fractal detector is designed based on the gaussian distribution of the fractal dimension and its performance is compared with a semi-optimum detector. It is demonstrated that the fractal detector has great capabilities in the rejection of colored clutter. Moreover, we show that the fractal detector is CFAR, i.e., the probability of false alarm remains approximately constant in different interference powers.

Suggested Citation

  • Salmasi, Mehrdad & Modarres-Hashemi, M., 2009. "Design and analysis of fractal detector for high resolution radars," Chaos, Solitons & Fractals, Elsevier, vol. 40(5), pages 2133-2145.
  • Handle: RePEc:eee:chsofr:v:40:y:2009:i:5:p:2133-2145
    DOI: 10.1016/j.chaos.2007.10.008
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    References listed on IDEAS

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    1. Y. Wang, 1997. "Fractal Function Estimation via Wavelet Shrinkage," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 59(3), pages 603-613.
    2. Pavlov, A.N. & Ziganshin, A.R. & Klimova, O.A., 2005. "Multifractal characterization of blood pressure dynamics: stress-induced phenomena," Chaos, Solitons & Fractals, Elsevier, vol. 24(1), pages 57-63.
    3. Kavasseri, Rajesh G. & Nagarajan, Radhakrishnan, 2005. "A multifractal description of wind speed records," Chaos, Solitons & Fractals, Elsevier, vol. 24(1), pages 165-173.
    4. Gnitecki, January & Moussavi, Zahra, 2005. "The fractality of lung sounds: A comparison of three waveform fractal dimension algorithms," Chaos, Solitons & Fractals, Elsevier, vol. 26(4), pages 1065-1072.
    5. Silva, F.E. & Gonçalves, L.L. & Fereira, D.B.B. & Rebello, J.M.A., 2005. "Characterization of failure mechanism in composite materials through fractal analysis of acoustic emission signals," Chaos, Solitons & Fractals, Elsevier, vol. 26(2), pages 481-494.
    6. Li, Xuewei & Shang, Pengjian, 2007. "Multifractal classification of road traffic flows," Chaos, Solitons & Fractals, Elsevier, vol. 31(5), pages 1089-1094.
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    Cited by:

    1. Kemih, Karim & Kemiha, Adel & Ghanes, Malek, 2009. "Chaotic attitude control of satellite using impulsive control," Chaos, Solitons & Fractals, Elsevier, vol. 42(2), pages 735-744.

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