车载超短波电台电波传播预测模型研究

doi:10.16180/j.cnki.issn1007-7820.2023.07.009

Abstract

Abstract:

Given the problem that the communication distance and quality of the vehicle-mounted ultrashort wave radio are affected by ground attachments and topography in the actual combat environment, a radio wave propagation prediction model of vehicle-mounted ultrashort wave radio is established based on ray tracing and machine learning. The integrated modeling of armored combat vehicle and vehicle antenna is established to obtain the antenna radiation pattern, and combined with electronic images, the radio wave propagation simulation model based on ray tracing technology is established. Based on the machine learning algorithm of the random forest and data results for the simulation model, the radio wave propagation prediction model based on the random forest was established. Compared with traditional classical radio wave propagation models such as the Egli and Okumura-Hata models, the radio wave propagation prediction model based on the random forest has higher accuracy. The root mean square error reaches 2.190 1 dB, and the coefficient of determination reaches 0.960 1. It can accurately predict radio wave propagation in the tactical communication environment.

Key words: ultrashort wave, path loss, ray-tracing method, radio wave propagation model, machine learning, random forest, electronic images, vehicle antenna

CLC Number:

TN011

LI Min,ZHANG Guangshuo,XU Zhijiang,XIE Hongxing,LU Hongmin. Research on Radio Wave Propagation Prediction Model of Vehicle-Mounted Ultrashort Wave Radio[J].Electronic Science and Technology, 2023, 36(7): 64-69.

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References 19

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模型	参数名称	参数取值
随机森林	决策树个数	180
	内部节点分裂的最小样本数	2
	叶子节点的最小样本数	1
	叶子节点中样本的最小权重	0
	树的最大深度	10
k近邻	所选用的近邻数	3
	预测的权函数	权重是距离的倒数
	向量距离算法	欧氏距离
BP神经网络	隐藏层神经元个数	11

模型	RMSE/dB	R²
随机森林	2.190 1	0.960 1
k近邻	3.703 9	0.885 9
BP神经网络	5.927 5	0.707 8
线性回归	8.555 1	0.391 4
自由空间	15.266 8	-0.938 2
Egli	22.634 8	-3.260 4
Okumura-Hata	24.405 2	-3.952 9
ITU-R P.1546	25.742 2	-8.196 0

Research on Radio Wave Propagation Prediction Model of Vehicle-Mounted Ultrashort Wave Radio

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