3D Localization Algorithm Based on Linear Regression and Least Squares in NLOS Environments
Author(s) -
Jiang Li,
Lei Zhang
Publication year - 2018
Publication title -
computer and information science
Language(s) - English
Resource type - Journals
eISSN - 1913-8997
pISSN - 1913-8989
DOI - 10.5539/cis.v11n4p1
Subject(s) - non line of sight propagation , computer science , algorithm , base station , terminal (telecommunication) , linear regression , property (philosophy) , time of arrival , mean squared error , statistics , mathematics , telecommunications , wireless , machine learning , philosophy , epistemology
Based on the positive bias property of the time of arrival(TOA) measurement error caused by the non-line-of-sight(NLOS) propagation, a simple and effective three dimensional(3D) geometrical localization algorithm was proposed, the algorithm needs no prior knowledge of time delay distribution of TOA, and only linear regression was used to estimate the parameters of the relationship between the NLOS distance error and the true distance, thus, the approximate real distance between mobile terminal (MT) and base station (BS) was reduced, then, the 3D geometric localization of mobile terminal was carried out by the least square method. The experimental results shows the effectiveness of the algorithm, and the positional accuracy is far higher than the required accuracy by E-911 in NLOS environments.
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