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arXiv 2301.09248eess.SP
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用于联合定位定向的靶载智能反射面

Target-Mounted Intelligent Reflecting Surface for Joint Location and Orientation Estimation

Peilan Wang, Weidong Mei, Jun Fang, Rui Zhang

摘要:

智能反射面(IRS)是一种有效的电磁环境重构技术,被广泛认为有利于无线通信性能。在本文中,我们提出了一个新的应用IRS的无设备的目标感知通过联合位置和方向估计。特别是,不同于现有的作品,使用IRS作为一个额外的锚节点定位/传感,我们考虑安装IRS的传感目标,从而估计IRS的位置和方向的目标,利用IRS的可控信号反射。为此,我们首先提出了一种基于张量的方法来获取IRS和传感发射器以及一组分布式传感接收器之间的基本角度信息。其次,基于估计的角度信息,我们分别建立了两个优化问题来估计IRS/目标的位置和方向,并通过调用两种迭代算法,即梯度下降法和流形优化,获得了它们的局部最优解。特别是,我们表明,方向估计问题承认在一个特殊的情况下,通常在实践中持有的封闭形式的解决方案。此外,理论分析进行绘制所提出的传感系统的设计和性能的重要见解。仿真结果验证了我们的理论分析,并表明,所提出的方法可以达到很高的估计精度,这是接近理论界。

英文摘要:

Intelligent reflecting surface (IRS) has been widely recognized as an efficient technique to reconfigure the electromagnetic environment in favor of wireless communication performance. In this paper, we propose a new application of IRS for device-free target sensing via joint location and orientation estimation. In particular, different from the existing works that use IRS as an additional anchor node for localization/sensing, we consider mounting IRS on the sensing target, whereby estimating the IRS's location and orientation as that of the target by leveraging IRS's controllable signal reflection. To this end, we first propose a tensor-based method to acquire essential angle information between the IRS and the sensing transmitter as well as a set of distributed sensing receivers. Next, based on the estimated angle information, we formulate two optimization problems to estimate the location and orientation of the IRS/target, respectively, and obtain the locally optimal solutions to them by invoking two iterative algorithms, namely, gradient descent method and manifold optimization. In particular, we show that the orientation estimation problem admits a closed-form solution in a special case that usually holds in practice. Furthermore, theoretical analysis is conducted to draw essential insights into the proposed sensing system design and performance. Simulation results verify our theoretical analysis and demonstrate that the proposed methods can achieve high estimation accuracy which is close to the theoretical bound.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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