%0 Journal Article
%T 基于毫米波雷达的云中积冰区域研究<br>Study on Ice Accumulation Area in Cloud Based on Millimeter Wave Radar
%A 肖安虹
%A 王金虎
%A 谢槟泽
%A 王昊亮
%A 史嘉琪
%A 许俊辉
%J Modeling and Simulation
%P 1011-1019
%@ 2324-870X
%D 2022
%I Hans Publishing
%R 10.12677/MOS.2022.114093
%X 飞机产生结冰现象会严重威胁飞机飞行安全。毫米波雷达具有高精度、高分辨率等优点且广泛分布在各大机场，极大地提升了业务人员的判别速度。本文尝试利用遗传算法优化后的BP神经网络建立雷达观测数据与积冰指数间的非线性关系，同时与支持向量机(SVM)分类结果进行对比，结果表明通过遗传算法优化的BP神经网络具有较高的正确率、较低的虚警率以及漏报率，为飞机能够穿越云层提供了安全保障。<br />
Aircraft icing will seriously threaten aircraft flight safety. Millimeter wave radar has the advantages of high precision and high resolution and is widely distributed in major airports, which greatly improves the discrimination speed of business personnel. This paper attempts to use the BP neural network optimized by genetic algorithm to establish the nonlinear relationship between radar observation data and icing index. At the same time, it is compared with the classification results of support vector machine (SVM). The results show that the BP neural network optimized by genetic algorithm has higher accuracy, lower false alarm rate and missing alarm rate, which provides a security guarantee for the aircraft to cross the clouds.
%K 毫米波雷达，神经网络，飞机积冰，支持向量机<br>Millimeter Wave Radar
%K Neural Network
%K Aircraft Icing
%K Support Vector Machine
%U http://www.hanspub.org/journal/PaperInformation.aspx?PaperID=53549