雷达散射截面（RCS）是衡量船舶目标散射特性的重要参数，是雷达进行船舶目标分类识别最有效的电磁频谱特性。但船舶目标结构、形状复杂，电磁散射机理复杂，同时受雷达探测角度及所在海域电磁环境等因素的影响，船舶的RCS呈现明显的起伏变化特性。本文对不同工况下船舶RCS测量数据进行统计特征描述，并采用BP神经网络进行船舶识别。结果表明，该方法取得了较好的试验结果，可实现对若干工况下不同类型的船舶精准识别。
The Radar Cross Section (RCS) is an important parameter for measuring the ship target scatter characteristics and the most effective electromagnetic spectrum characteristics for the classification and recognition of the ship.The shape and structure of ship are complex and the mechanism of the electromagnetic scattering is complex. At the same time, it is influenced by the detection angle of radar and the electromagnetic environment in the sea area. So the RCS of ship shows obvious fluctuation characteristics. In this paper, the statistical characteristics of ships' RCS is conducted, and the BP neural network is used for the recognition of ships.The results show that the method proposed in the paper achieved good results and it can accurately identify different types of ship under certain condtions.
2018,40(7): 129-132 收稿日期：2018-01-25
DOI：10.3404/j.issn.1672-7649.2018.07.024
分类号：TN911
基金项目：国防基础科研计划资助项目（JCKY2016206C003）
作者简介：纪永强(1986-),男,博士,研究方向为舰船电子信息系统
参考文献：
[1] 王春花, 康猛, 郝明. 基于轮廓像的舰船目标识别方法研究[J].现代雷达,2012,34(4):45-47,52
[2] 赵安军,牛威,郭雷. 基于RCS的空间目标特征提取与识别研究[C]//Proceedings of the 27th Chinese Control Conference, 2008.
[3] 隋栋训, 童创明, 王童, 等. 基于RCS序列的助推段弹道导弹识别[J].火力与指挥控制, 2016:42(3):15-18.
[4] 张建强, 高世家, 赵霁红. 舰船RCS特征提取与GA-BP神经网络分类研究[J]. 船舶科学技术,2016,38(2):125-130.
[5] 高隽. 人工神经网络原理及仿真实例[M]. 北京:机械工业出版社, 2003.
