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Performance Analysis of Fingerprinting Method for LTE Positioning according to W-KNN Correlation Techniques in Urban Area

도심지역 LTE 측위를 위한 Fingerprinting 기법의 W-KNN Correlation 기술에 따른 성능 분석

  • 권재욱 (경일대학교 IT공학과) ;
  • 조성윤 (경일대학교 로봇.모빌리티전공)
  • Received : 2021.10.12
  • Accepted : 2021.12.17
  • Published : 2021.12.31

Abstract

In urban areas, GPS(Global Positioning System)/GNSS(Global Navigation Satellite System) signals are blocked or distorted by structures such as buildings, which limits positioning. To compensate for this problem, in this paper, fingerprinting-based positioning using RSRP(: Reference Signal Received Power) information of LTE signals is performed. The W-KNN(Weighted - K Nearest Neighbors) technique, which is widely used in the positioning step of fingerprinting, yields different positioning performance results depending on the similarity distance calculation method and weighting method used in correlation. In this paper, the performance of the fingerprinting positioning according to the techniques used in correlation is comparatively analyzed experimentally.

도심지역에서 GPS(Global Positioning System)/GNSS(Global Navigation Satellite System) 신호는 건물과 같은 구조물에 의해 차단되거나 왜곡되어 위치추정에 한계가 존재한다. 이 문제를 보완하기 위해 본 논문에서는 LTE 신호의 RSRP(Reference Signal Received Power) 정보를 사용한 Fingerprinting 기법으로 측위를 수행하고자 한다. Fingerprinting의 측위 단계에서 많이 사용되는 W-KNN(Weighted - K Nearest Neighbors) 기법은 Correlation 시 사용되는 유사도 거리 계산 방법과 가중치 적용 방법 등에 따라 다른 측위 성능의 결과를 생성한다. 본 논문에서는 Correlation 시 사용되는 기법들에 따른 Fingerprinting 측위 성능을 실 데이터 기반으로 비교 분석하고자 한다.

Keywords

Acknowledgement

본 연구는 2019년도 정부(과학기술정보통신부)의 재원으로 정보통신기획평가원의 지원을 받아 수행된 연구입니다. (No. 2019-0-01401, 긴급구조용 측위 품질 제고를 위한 GPS 음영 지역 내 다중신호패턴의 학습기반 3차원 정밀 측위 기술 개발)

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