Hu Shuo, Guo Lixin, Liu Zhongyu
School of Physics, Xidian University, Xi'an 710071, China.
Sensors (Basel). 2024 Dec 11;24(24):7925. doi: 10.3390/s24247925.
Localization accuracy in non-line-of-sight (NLOS) scenarios is often hindered by the complex nature of multipath propagation. Traditional approaches typically focus on NLOS node identification and error mitigation techniques. However, the intricacies of NLOS localization are intrinsically tied to propagation challenges. In this paper, we propose a novel single-site localization method tailored for complex multipath NLOS environments, leveraging only angle-of-arrival (AOA) estimates in conjunction with a ray-tracing (RT) algorithm. The method transforms NLOS paths into equivalent line-of-sight (LOS) paths through the generation of generalized sources (GSs) via ray tracing. A novel weighting mechanism for GSs is introduced, which, when combined with an iteratively reweighted least squares (IRLS) estimator, significantly improves the localization accuracy of non-cooperative target sources. Furthermore, a multipath similarity displacement matrix (MSDM) is incorporated to enhance accuracy in regions with pronounced multipath fluctuations. Simulation results validate the efficacy of the proposed algorithm, achieving localization performance that approaches the Cramér-Rao lower bound (CRLB), even in challenging NLOS scenarios.
在非视距（NLOS）场景中，定位精度常常受到多径传播复杂特性的阻碍。传统方法通常侧重于NLOS节点识别和误差缓解技术。然而，NLOS定位的复杂性本质上与传播挑战相关联。在本文中，我们提出了一种新颖的单站点定位方法，该方法专为复杂多径NLOS环境量身定制，仅利用到达角（AOA）估计并结合光线追踪（RT）算法。该方法通过光线追踪生成广义源（GS），将NLOS路径转换为等效视距（LOS）路径。引入了一种针对GS的新颖加权机制，当与迭代重加权最小二乘（IRLS）估计器相结合时，可显著提高非合作目标源的定位精度。此外，还引入了多径相似性位移矩阵（MSDM），以提高在多径波动明显区域的精度。仿真结果验证了所提算法的有效性，即使在具有挑战性的NLOS场景中，也能实现接近克拉美罗下界（CRLB）的定位性能。
