Accurate and ubiquitous localization is crucial for a variety of applications such as logistics, navigation, intelligent transport, monitoring, control, and also for the benefit of communications. Exploiting millimeter-wave (mmWave) signals in 5G and Beyond 5G systems can provide accurate localization with limited infrastructure. We consider the single base station (BS) localization problem and extend it to 3D position and 3D orientation estimation of an unsynchronized multi-antenna user equipment (UE), using downlink multiple-input multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) signals. Through a Fisher information analysis, we show that the problem is often identifiable, provided that there is at least one multipath component in addition to the line-of-sight (LoS), even if the position of corresponding incidence point (IP) is a priori unknown. Subsequently, we pose a maximum likelihood (ML) estimation problem, to jointly estimate the 3D position and 3D orientation of the UE as well as several nuisance parameters (the UE clock offset and the positions of IPs corresponding to the multipath). The ML problem is a high-dimensional non-convex optimization problem over a product of Euclidean and non-Euclidean manifolds. To avoid complex exhaustive search procedures, we propose a geometric initial estimate of all parameters, which reduces the problem to a 1-dimensional search over a finite interval. Numerical results show the efficiency of the proposed ad-hoc estimation, whose gap to the Cram\'er-Rao bound (CRB) is tightened using the ML estimation.
翻译:对后勤、导航、智能运输、监测、控制等各种应用以及通信而言,准确和无处不在的本地化至关重要。在5G和5G以上系统使用毫米波信号(mmWave)可以提供有限的基础设施的准确本地化。我们认为单一基站(BS)本地化问题,并将其扩大到3D位置和3D方向估算,即一个不同步的多保险用户设备(UE),使用下链接多输入参数、多输出、高输出或高频率多功能(MIMO-OFDM)信号,对通信有好处。通过对Fisher信息进行分析,我们发现问题往往可以辨别,条件是除了直观(LOS)之外至少有一个多路方组件。即使相应的事件点(IP)的位置是未知的。随后,我们提出了最大的可能性(ML)估算问题,联合估计了多输入的多输出、高输出或多位频率显示多路透度(MI-C)的估计值(IM-C) 初步估算结果,而IMC的深度(IMFL) 显示一个不甚高的磁点(IML) 的深度分析结果,对IML) 的深度(IMC) 和深度分析过程的深度分析过程显示一个不测点的深度(IML)。