Three-dimensional localization methods could provide important position information for various application systems, including PHM (Prognostics and Health Management), aerospace, emergency scheduling, rescue and relief, and many other related location-based services systems. Due to the negative influence of various uncertain factors on the localization accuracy, the localization result may lead to wrong navigation result, or even could not be utilized. So except for the localization result, the uncertainty of localization result should be evaluated, which could provide important priori information for later processing procedure or decision-making. For this problem, this paper analyzes the uncertainty propagation mechanism during a three-dimensional least square localization method, which is referred to as a guide to represent uncertainty in measurement (GUM). In this method, we make a comprehensive uncertainty propagation analysis during three-dimensional least square localization, and provide important uncertain information of localization result. We first analyze the uncertain sources of three-dimensional least square localization. Then we analyze the sensitivity and propagation mechanism of uncertainty during least square localization computation. Finally, we output the localization result and its uncertainty through synthesizing all the input uncertainties. The simulation and experimental results illustrate that the proposed method could provide localization result with accurate uncertain information.

Additional Metadata
Keywords Least Square, Propagation mechanism, Sensitivity, Uncertainty analysis, uncertainty synthesis, Wireless Localization
Persistent URL dx.doi.org/10.1109/PHM-Paris.2019.00015
Conference 2019 Prognostics and System Health Management Conference, PHM-Paris 2019
Citation
Yan, X. (Xiaozhen), Luo, Q. (Qinghua), Zhou, P. (Pengtai), & Liu, J. (2019). An Uncertainty Propagation Mechanism Analysis Method for Three-Dimensional Quadrilateral Localization. In Proceedings - 2019 Prognostics and System Health Management Conference, PHM-Paris 2019 (pp. 39–44). doi:10.1109/PHM-Paris.2019.00015