A Low-Slow-Small Target Detection Method for Offshore Radar Based on GPU

K. Guo, Xin Zheng, Shuhai Shi, Kaili Qin, Tingyao Xie
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引用次数: 1

Abstract

In recent years, the detection of low-slow-small targets by offshore radar has become a key issue to be solved urgently. This paper analyzes the echo characteristics of the sea clutter and the target, by extracting the features of the target and sea clutter, the feature detector is used to realize the classification of the target and the clutter, and then extract the target information. In addition, the method in this paper is implemented by GPU to increase the computing speed. The method in this paper is verified by the measured data of a Ku-band offshore radar. It has a higher detection capability than traditional CFAR, and the GPU processing speed meets engineering requirements, realizing the real-time detection of the target by the radar.
基于GPU的海上雷达低慢小目标检测方法
近年来,海上雷达对低慢小目标的探测已成为一个亟待解决的关键问题。本文分析了海杂波和目标的回波特征,通过提取目标和海杂波的特征,利用特征检测器实现目标和杂波的分类,进而提取目标信息。此外,本文的方法通过GPU实现,提高了计算速度。用ku波段海上雷达的实测数据对本文方法进行了验证。它具有比传统CFAR更高的检测能力,且GPU处理速度满足工程要求,实现了雷达对目标的实时检测。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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