RSS
职位(财务)
到达角
计算机科学
噪音(视频)
算法
无线
测量不确定度
克拉姆-饶行
高斯噪声
信号强度
高斯分布
放松(心理学)
噪声测量
简单(哲学)
数学优化
估计理论
数学
人工智能
统计
电信
哲学
图像(数学)
操作系统
心理学
社会心理学
认识论
量子力学
物理
财务
天线(收音机)
降噪
经济
作者
Qi Wang,Xianshun Jiang,Fēi Li
标识
DOI:10.1109/icftic57696.2022.10075208
摘要
Received signal strength (RSS) and angle of arrival (AOA) measurements have been widely applied in wireless localization due to their specific merits, e.g., easy access of measurements and simple system structure. Recently, these two types of measurements have been successfully combined to achieve better localization accuracy over either AOA-only or RSS-only localization. In the existing work, the anchor positions are usually assumed to exactly known. Unfortunately, in practice, they are inevitably subject to errors, which induces uncertainties for localization. The uncertainties directly affect the localization accuracy, as anchor positions also act as measurements in the localization process. In this paper, we propose a combined RSS-AOA localization method, which is able to deal with anchor position uncertainty. The main idea is to model the position uncertainty as Gaussian noise and formulate the location estimation problem with the maximum likelihood (ML) criterion. Then, tight approximation and proper relaxation are utilized to obtain a convex problem. Numerical examples demonstrate the performance superiority of the proposed method, compared with some state-of-art methods.
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