Weak target detection in sea clutter background using local-multifractal spectrum with adaptive window length

Weak target detection in sea clutter background using local-multifractal spectrum with adaptive window length

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Weak target detection based on fractal analysis is a hot research topic. The existing methods, using single fractal dimension and Hurst exponent, are not applicable under low signal clutter ratio (SCR) conditions. This study focuses on enhancing the performance of weak target detection by utilising the multifractal properties of sea clutter. The existing global multifractal spectrum based method has limited performance because of its non-stability. Therefore this study proposes a weak target detection method by taking into account the local difference of multifractal spectrum between sea clutter with and without target. The local-multifractal spectrum is obtained by adding a rectangle window to the multifractal spectrum, and the local difference is calculated by the local mean square summation algorithm. In addition, the window length, a key parameter for obtaining the local-multifractal spectrum, is adaptively computed by the slope of the singularity intensity. In comparison with the existing multifractal spectrum based method, the experimental results of real S-band and X-band sea clutter data show that the proposed method is more stable, and could achieve a better detection performance under low SCR conditions.


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