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Conference Paper Feasibility Analysis on LTE RSRP Fingerprint DB Estimation using Sparse War-Driving Collecting Data for Emergency Location
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Authors
Young-Su Cho, Myung-In Ji
Issue Date
2019-10
Citation
International Symposium on Global Navigation Satellite System (ISGNSS) 2019, pp.51-58
Language
English
Type
Conference Paper
Abstract
In order to improve indoor and outdoor positioning accuracy in various positioning environments (e.g. dense urban/urban/suburban/rural) in case of emergency location service, it is primarily required to enhance LTE signal based positioning technology that provides signal coverage of 99% or more in Korea. Typical LTE Reference Signal Received Power (RSRP) fingerprint positioning method includes the offline phase that generates an LTE RSRP fingerprint DB based on the collected data and the online phase in which the generated DB is compared with the measured value of the terminal to calculate the position. To improve the positioning performance of the LTE RSRP fingerprint DB generated by the offline phase, it is required to collect its location and LTE RSRP data densely, but it is expensive and laborious. As an alternative to this, further research is needed to estimate the LTE RSRP fingerprint DB of non-collecting points based on the data collected roughly through war driving. In this paper, the following technical feasibility on LTE RSRP fingerprint DB estimation for emergency location will be studied and analyzed. First, Analysis of LTE RSRP raw data on a specific LTE cell, which is collected through repeated war-driving in a specific test environment. Next, Estimation of LTE RSRP fingerprint DB on a specific LTE cell using Gaussian process regression. Lastly LTE RSRP error analysis between estimated and measured LTE RSRP fingerprint DB.
KSP Keywords
Collecting data, Data collected, Dense urban, Feasibility Analysis, Fingerprint positioning, Gaussian Process(GP), Gaussian Process Regression(GPR), Outdoor Positioning, Positioning accuracy, Positioning method, Positioning technology