Cramer-Rao Lower Bound Analysis of Data Fusion for Fingerprinting Localization in Non-Line-of-Sight Environments

Cramer-Rao Lower Bound Analysis of Data Fusion for Fingerprinting Localization in Non-Line-of-Sight Environments

This paper proposes a novel framework for analyzing the localization accuracy of data fusion for fingerprinting approaches in non-line-of-sight (NLOS) environments. Using simulation data generated for two very different NLOS environments (a suburban area of 3.3km × 3.3km in Santa Clara, C...

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Bibliographic Details
Main Authors: Jun Li, I-Tai Lu, Jonathan Lu
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Localization
NLOS
5G
weighted K-nearest neighborhood
RSS
TOA
Online Access:https://ieeexplore.ieee.org/document/9334994/

Internet

https://ieeexplore.ieee.org/document/9334994/

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