In this paper, nonstationary sea clutter time sequence, and corresponding amplitude sequence and phase sequence are modeled as statistically similar fractional-order Brownian motion (fBm) processes at different time scales. Their Hurst exponents form an all-dimensional description of fractal characteristics of sea clutter time sequence. Radar returns with targets and sea clutter exhibit salient differences in the all-dimensional description. Averaging three Hurst exponents followed by an adaptive threshold decision gives a simple but effective detector of sea-surface small targets. Experimental results on the recognized IPIX radar database show that the proposed detector attains much better performance than the detectors using single amplitude features and is competitive in performance with the tri-feature-based detector that requires time-consuming learning and decision processes.

在本文中，将非平稳海杂波时间序列以及相应的振幅序列和相位序列建模为不同时间尺度上统计上相似的分数阶布朗运动（fBm）过程。他们的赫斯特指数形成了海杂波时间序列的分形特征的全方位描述。带有目标和海杂波的雷达回波在全尺寸描述中表现出显着差异。对三个赫斯特指数进行平均，然后进行自适应阈值决策，可提供一种简单但有效的海面小目标检测器。