无线电工程2025，Vol.55Issue(6)：1298-1305,8.DOI:10.3969/j.issn.1003-3106.2025.06.018
基于雷达HRRP和RCS的神经网络火箭飞行姿态测量
Rocket Flight Attitude Measurement Based on Neural Network Using HRRP and RCS
吕青 1魏明山 1郑昊鹏 1全刚1
作者信息
- 1. 中国酒泉卫星发射中心测控通信联合实验室,甘肃 酒泉 732750
- 折叠
摘要
Abstract
High-resolution Range Profile(HRRP)and Radar Cross Section(RCS)are important target characteristic data obtained by radar,which have the potential to excavate in-depth information about the target and are data basis for achieving target attitude measurement.The data characteristics of HRRP and RCS of the rocket are analyzed.Based on the strategy of data driving,two types of neural networks are proposed:A Multilayer Perceptron(MLP)and a combination of a Convolutional Neural Network(CNN)and an MLP.The L2 regularization is utilized to obtain the sine and cosine outputs of the attitude angles,effectively realizing the measurement of the rocket's flight attitude.To verify the validity of the methods,electromagnetic simulation is used to obtain the simulated HRRP and RCS data of a certain rocket model at different attitudes.The training and test data sets were expanded through data augmentation.The test results show the MLP network has a more practical attitude measurement effect.关键词
高分辨距离像/雷达散射截面/多层感知机/卷积神经网络/电磁仿真Key words
HRRP/RCS/MLP/CNN/electromagnetic simulation分类
信息技术与安全科学引用本文复制引用
吕青,魏明山,郑昊鹏,全刚..基于雷达HRRP和RCS的神经网络火箭飞行姿态测量[J].无线电工程,2025,55(6):1298-1305,8.
