Issue |
JNWPU
Volume 42, Number 6, December 2024
|
|
---|---|---|
Page(s) | 1144 - 1151 | |
DOI | https://doi.org/10.1051/jnwpu/20244261144 | |
Published online | 03 February 2025 |
Electromagnetic target detection model for unmanned aerial vehicle platforms based on Bayesian detection
基于贝叶斯检测的无人机平台电磁探测模型
PLA Information Engineering University, Zhengzhou 450000, China
Received:
25
December
2023
Existing models for target detection on unmanned aerial vehicle platforms largely rely on the Boolean perception model. However, aiming at electromagnetic radiation sources, the Boolean perception model fails to accurately reflect the propagation and detection characteristics of electromagnetic wave signals. To address this issue, this paper, grounded in the Bayesian signal detection theory and utilizing the distributional characteristics of antenna pattern diagrams, constructs an electromagnetic detection model for unmanned aerial vehicle platforms. The performance of the novel model is derived and analyzed under a scanning coverage search algorithm. Analytical and simulation results indicate that the proposed model effectively describes the process of electromagnetic target detection. In coverage search tasks, when the unmanned aerial vehicle is equipped with the KSHA-BJ32-10-NH antenna, the new model has a shorter range compared to the Boolean perception model, and the advantage of the new model becomes more pronounced as the search area expands. The increase in the required range for the unmanned aerial vehicle to complete the task is only 85.41% of that of the traditional Boolean model.
摘要
现有的目标探测无人机平台建模大多基于布尔感知模型(Boolean perception model)。然而, 在针对电磁波辐射源的探测任务中, 布尔感知模型无法充分体现电磁波信号的传播与检测特性。为了克服这一局限性, 以贝叶斯信号检测理论为基础, 基于天线方向图的分布特性, 构建了无人机平台电磁探测模型, 并推导分析了新模型在扫描式覆盖搜索算法下的性能特点。分析与仿真结果显示, 新模型有效描述了电磁目标探测过程。在覆盖搜索任务中, 当无人机搭载KSHA-BJ32-10-NH型天线时, 相较于布尔感知模型, 新模型的航程更短。随着搜索区域的扩大, 新模型的航程优势愈加明显, 无人机完成任务所需航程的增速仅为传统布尔模型的85.41%。
Key words: unmanned aerial vehicle / electromagnetic radiation sources / target detection / Bayesian signal detection
关键字 : 无人机 / 电磁波辐射源 / 目标探测 / 贝叶斯信号检测
© 2024 Journal of Northwestern Polytechnical University. All rights reserved.
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