Blind Box-Counting Based Detection of Low Observable Targets within Sea Clutter

Pournejatian, N.M.; Nayebi, Mohammad Mahdi; Taban, Mohammad Reza

doi:10.1587/transcom.e95.b.3863

Cited by 2 publications

(2 citation statements)

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“…Recently, by analyzing the real high-resolution sea clutter datasets, many unconventional methods exploiting the features of clutter have been developed [29][30][31][32][33][34]. Several researchers have demonstrated that the sea clutter time series exhibit fractal and multiracial behaviors.…”

Section: Motivation and Related Workmentioning

confidence: 99%

“…Several researchers have demonstrated that the sea clutter time series exhibit fractal and multiracial behaviors. Starting from this result, the fractal-based detectors are developed, for example, multifractal analysis based on Hurst exponent [29], multifractal analysis based on blind boxcounting [30], high-order fractal feature [31], and joint fractal with the combination of Hurst exponent and intercept [32]. It has been shown that these fractal-based detectors can achieve very high detection accuracy within a long observation time, but during the several-second observation time, their detection performance suffers from some degradation [32].…”

Section: Motivation and Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Correlation feature-based detector for range distributed target in sea clutter

Yuan

Hong²,

Wang

et al. 2018

EURASIP J. Adv. Signal Process.

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In this paper, a novel correlation feature-based detector is proposed to deal with the challenging problem of detecting a range-distributed target embedded in nonstationary sea clutter. It is well known that sea clutter consists of a speckle component modulated by texture. The nonstationary property of sea clutter is mainly reflected in texture, but its correlation characteristic is mainly dominated by the speckle. Therefore, this detector using the correlation feature of sea clutter can effectively eliminate the negative effect of the nonstationary property of sea clutter on the detection performance. In addition, in order to get rid of the limitation of the knowledge shortage of target scatterers, the modified entropy method is applied to adaptively estimate the number of target scatterers. The real range distributed target data and high-resolution sea clutter are used to evaluate the detector, and the experimental results show that it attains a better detection performance in comparison with several existing detectors. Comparing with the feature-based detector, the proposed detector can effectively reduce the computational complexity.

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