基于IUPF算法的三维无人机毫米波波束跟踪

doi:10.12305/j.issn.1001-506X.2023.01.30

系统工程与电子技术 ›› 2023, Vol. 45 ›› Issue (1): 257-263.doi: 10.12305/j.issn.1001-506X.2023.01.30

• 通信与网络 • 上一篇

基于IUPF算法的三维无人机毫米波波束跟踪

张俊杰¹, 仲伟志¹^,*, 张璐璐¹, 王俊智¹, 朱秋明²

1. 南京航空航天大学航天学院, 江苏南京 211106
2. 南京航空航天大学电子与信息工程学院, 江苏南京 211106

收稿日期:2021-09-01 出版日期:2023-01-01 发布日期:2023-01-03
通讯作者: 仲伟志
作者简介:张俊杰(1998—), 男, 硕士研究生, 主要研究方向为无人机毫米波的波束跟踪和预测
仲伟志(1980—), 女, 副教授, 博士, 主要研究方向为5G中的毫米波通信、大规模多输入多输出通信技术以及波束成形和波束跟踪技术
张璐璐(1998—), 女, 硕士研究生, 主要研究方向为车联网毫米波通信
王俊智(1999—), 男, 硕士研究生, 主要研究方向为无人机毫米波的波束搜索和跟踪
朱秋明(1979—), 男, 副教授, 博士, 主要研究方向为电磁传播环境测量认知、无人机信道大数据测量应用和航天测控电磁环境评估及模拟
基金资助:
国家自然科学基金重大仪器研制项目(61827801);中央高校基本科研业务费(NS2020063)

3D UAV millimeter-wave beam tracking based on IUPF algorithm

Junjie ZHANG¹, Weizhi ZHONG¹^,*, Lulu ZHANG¹, Junzhi WANG¹, Qiuming ZHU²

1. College of Astronautics, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
2. College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China

Received:2021-09-01 Online:2023-01-01 Published:2023-01-03
Contact: Weizhi ZHONG

摘要/Abstract

摘要：

由于无人机毫米波通信技术具有高速数据传输和广域网络覆盖能力, 因此在军用和民用领域中拥有广阔的应用前景。针对无人机毫米波通信需要进行精确的波束跟踪这一问题, 提出一种基于改进无迹卡尔曼粒子滤波算法的三维波束跟踪方法。该方法首先利用无迹卡尔曼滤波建立建议密度函数并更新采样粒子; 然后计算每一个采样粒子的权值, 并在归一化后再次对粒子进行重采样; 最后计算粒子均值, 得到波束跟踪角度。仿真结果表明, 该方法相较于以往毫米波波束跟踪方法大大降低了估计误差, 显著提高了波束的跟踪精度。

关键词: 无人机通信, 毫米波, 波束跟踪, 改进无迹卡尔曼粒子滤波

Abstract:

Unmanned aerial vehicle millimeter-wave communication technology has broad application prospects in military and civilian fields due to its high-speed data transmission and wide-area network coverage capabilities. Aiming at the problem that the unmanned aerial vehicle mmWave communication needs accurate beam tracking, a three-dimensional beam tracking method based on the improved unscented Kalman particle filter algorithm is proposed. This method, firstly, uses the unscented Kalman filter to establish the proposed density function and updates the sampled particles; then calculates the weight of each sampled particle, and re-samples the particles after normalization; finally calculates the particle average value to obtain the beam tracking angle. The simulation results show that compared with the previous millimeter-wave beam tracking methods, this method greatly lowers the estimation error, and significantly improves the beam tracking accuracy.

Key words: unmanned aerial vehicle communication, millimeter-wave, beam tracking, improved unscented Kalman particle filter (IUPF)

中图分类号:

TN928

张俊杰, 仲伟志, 张璐璐, 王俊智, 朱秋明. 基于IUPF算法的三维无人机毫米波波束跟踪[J]. 系统工程与电子技术, 2023, 45(1): 257-263.

Junjie ZHANG, Weizhi ZHONG, Lulu ZHANG, Junzhi WANG, Qiuming ZHU. 3D UAV millimeter-wave beam tracking based on IUPF algorithm[J]. Systems Engineering and Electronics, 2023, 45(1): 257-263.

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参考文献 31

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仿真参数	数值
跟踪时隙	100
权重影响因子	0.1, 0.2, 0.3, 0.5, 0.8
角度变化方差	(0.5)²
接收端天线数M_r, N_r	8, 16, 24, 32
发射端天线数M_t, N_t	8, 16, 24, 32
EOA, ZOA初始角度/(°)	45
EOD, ZOD初始角度/(°)	45
SNR/dB	20

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基于IUPF算法的三维无人机毫米波波束跟踪

3D UAV millimeter-wave beam tracking based on IUPF algorithm

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