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物理学报  2006 

A novel method of target detection based on the sea clutter
海杂波背景下的目标检测新方法

Keywords: fractional Brownian motion,fractal dimension,memory-based predictor,support vector machine classifiers
分形布朗运动
,分形维数,记忆库预测方法,支持向量机分类器

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Abstract:

Adopting the model of fractional Brownian motion, this paper presents the method of deducing Hurst exponent based on the observed sea clutter of S-band radar. Secondly the prediction technology of chaotic time series is studied based on memory-based predictor. Furthermore, adopting the method of support vector machine classifiers of the improved radial basis kernel function, this paper proposes a novel method of target detection based on the sea clutter. Thirdly, on the basis of observed sea clutter of S-band radar, the fractal dimension and the largest Lyapunov exponent are obtained, which proves its chaos and fractal characteristic. Finally, the computer simulation is carried out and the results prove the effective detection performance and noise tolerance.

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