摘要
针对无人艇平台在高速机动时导航雷达目标定位方位误差异常增大的问题,提出了一种异类多特征与导航雷达目标联合精确定位方法。该方法通过模糊神经网络对光电跟踪仪数据和雷达点迹信息进行特征匹配,实时修正导航雷达目标方位,以补偿因平台机动等因素产生的系统误差。仿真实验结果表明,该方法能有效降低方位误差,提高雷达目标定位精度,对于无人艇在恶劣海况或平台机动时的精确态势感知具有重要意义。
In response to the problem of exacerbated azimuth errors in navigation radar target positioning during high-speed maneuvers of unmanned surface vehicles(USVs),this paper presents a joint precise localization method of heterogeneous multi-feature and navigation radar targets.The proposed method performs feature matching between electro-optical tracker data and radar point trace information by using a fuzzy neural network,corrects the target azimuth of navigation radar in real time to compensate for systematic errors caused by platform maneuvering and other factors.Simulation experiment results demonstrate that the proposed method can effectively reduce azimuth errors and improve the localization accuracy of radar target,which is of significant importance for precise situational awareness of USVs under harsh maritime conditions or during platform maneuvering.
作者
赵国清
王景石
蒋丙栋
张煌
高兆强
ZHAO Guoqing;WANG Jingshi;JIANG Bingdong;ZHANG Huang;GAO Zhaoqiang(The 716 Institute of CSSC,Lianyungang 222006,China)
出处
《舰船电子对抗》
2025年第3期26-30,共5页
Shipboard Electronic Countermeasure
关键词
无人艇
导航雷达
模糊神经网络
误差补偿
unmanned surface vehicle
navigation radar
fuzzy neural network
error compensation
