面向分布式空地通感一体化网络的无人机3D定位算法  

A 3D Localization Algorithm for Unmanned Aerial Vehicles in Distributed Air-Ground Integrated Sensing and Communication Networks

作　　者：黄逸 邹锐卓 石运梅 HUANG Yi;ZOU Ruizhuo;SHI Yunmei(Department of Information and Communication Engineering,Tongji University,Shanghai 201804,China)

机构地区：[1]同济大学信息与通信工程系,上海201804

出　　处：《电子与信息学报》2025年第4期1085-1092,共8页Journal of Electronics & Information Technology

基　　金：国家自然科学基金(62201391,62101386)。

摘　　要：无人机定位不仅能够提高无人机操作的安全性和效率,还为各种低空经济活动提供了技术保障。传统蜂窝定位技术依赖于专用的定位导频,不仅需要大量的导频开销,且在3D定位精度上存在限制。针对该问题,该文提出了一种空地协同的通感一体化网络中的多基站分布式无人机3D定位方法,根据多信号分类算法(MUSIC)得到多个发射信号经过目标无人机折射并到达接收站的时延估计,进而利用椭圆定位算法得到无人机的3D位置估计。进一步地,推导了基于分布式通感一体化网络的无人机3D位置估计的误差克拉美罗下界(CRLB),并与所提位置估计算法的蒙特卡洛性能仿真进行对比,验证了所提算法的性能在高信噪比(SNR)区域能够逼近CRLB。研究结果表明,所提算法能够在无需定位导频的情况下保证目标无人机的3D定位精度,并且利用无人机基站作为通感信号收发机和边缘计算中心辅助地面基站进行目标无人机的3D定位,相较于仅依赖地面基站的传统定位算法,可以有效地提高目标无人机高度的估计精度。Objective The low-altitude economy,driven by the widespread adoption of drones and other unmanned aerial vehicles(UAVs),supports a range of applications across industries such as aerial imaging,precision agriculture,disaster response,and logistics.Precise Three-Dimensional(3D)positioning is essential to ensure the safety and efficiency of UAV operations in these scenarios.However,conventional cellular-based positioning approaches rely heavily on dedicated pilot signals,which impose significant overhead and limit 3D positioning accuracy.Integrated sensing and communication(ISAC)technology offers a promising alternative by enabling receivers to extract positioning information from reflected communication signals,thereby reducing dependence on pilot signals.Furthermore,a distributed network of ISAC transceivers can enhance sensing coverage and data diversity,improving localization performance.Building on these principles,this study proposes a 3D positioning algorithm based on distributed ISAC networks.The algorithm achieves high positioning accuracy without additional pilot signal overhead,demonstrating strong potential to support UAV applications within the lowaltitude economy.Methods Motivated by the principles of distributed radar systems,this study proposes a cooperative 3D positioning method for UAVs within a distributed ISAC network comprising both ground base stations(BSs)and UAV-mounted BSs.Firstly,each ISAC receiver—whether ground-based or UAV-mounted—independently collects communication signals reflected by the target UAV from multiple ISAC transmitters.Secondly,each ISAC receiver serves as an edge computing node and derives a coarse estimate of the UAV’s 3D coordinates.Specifically,the receiver applies the MUltiple SIgnal Classification(MUSIC)algorithm to estimate the time delays of Orthogonal Frequency-Division Multiplexing(OFDM)signals refracted by the UAV.This is accomplished by exploiting the common delay steering vector structure across different ISAC transmitters.The resulting time-delay estim

关 键 词：通感一体化网络 空地协同网络 3D定位 分布式感知 

分 类 号：TN929.5[电子电信—通信与信息系统]