The generalised Pareto distribution is an efficient model to characterise the high-resolution sea clutter. Robust and precise estimation of the model's parameters is a precondition of effective target detection in sea clutter. It is known that the explicit bipercentile (BiP) estimators are efficient in computation and robust to outliers. In this study, it is proved that the explicit BiP estimators are also consistent with respect to sample size. In practical applications, only limited samples are available and the bias of the BiP estimators degrades the estimation precision. The properties of the biases are analysed and BiP estimators of bias reduction are constructed by the look-up table method. The BiP estimators of bias reduction are verified by simulated data and measured sea clutter data.

中文翻译：

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广义Pareto杂波模型偏差减少的双百分参数估计。

广义帕累托分布是表征高分辨率海杂波的有效模型。对模型参数的鲁棒和精确估计是在海浪杂波中有效检测目标的前提。众所周知，显式二百分位数（BiP）估计量在计算中有效并且对异常值具有鲁棒性。在这项研究中，证明了明确的BiP估计量在样本量方面也是一致的。在实际应用中，只有有限的样本可用，BiP估计器的偏差会降低估计精度。分析了偏差的性质，并通过查找表方法构造了偏差减小的BiP估计器。通过模拟数据和实测海杂波数据验证了偏差减少的BiP估计量。