한국ITS학회 논문지 (The Journal of The Korea Institute of Intelligent Transport Systems)

  • 제19권1호
  • /
  • Pages.94-106
  • /
  • 2020
  • /
  • 1738-0774(pISSN)
  • /
  • 2384-1729(eISSN)
한국ITS학회 (The Korea Institute of Intelligent Transport Systems)
권호 표지
DOI QR코드

DOI QR Code

GPS 음영 환경에서 무선랜 기반 차량 위치 추정 연구

Wireless LAN-based Vehicle Location Estimation in GPS Shading Environment

  • 이동훈 (국민대학교 자동차공학전문대학원) ;
  • 민경인 (국민대학교 자동차공학전문대학원) ;
  • 김정하 (국민대학교 자동차 IT 융합학과)
  • Lee, Donghun (Graduate School of Automotive Engineering, Kookmin University) ;
  • Min, Kyungin (Graduate School of Automotive Engineering, Kookmin University) ;
  • Kim, Jungha (Department of Automobile and IT Convergence, Kookmin University)
  • 투고 : 2019.06.20
  • 심사 : 2020.01.02
  • 발행 : 2020.02.28
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

근래의 위치 측위 방법으로 GPS(Global Positioning System) 위성정보를 활용하는 전파항법 방식을 많이 사용하고 있다. GPS 활용범위가 넓어지고 다양한 측위 정보를 기반으로 하는 분야가 생기면서 보다 높은 정확도를 얻기 위한 새로운 방법들이 요구되고 있다. 자율주행차의 경우 IMU(Inertial Measurement Unit)를 사용한 항법 시스템인 INS(Inertial Navigation System)와 차량 내부 센서를 이용한 DR(Dead Reckoning) 알고리즘을 사용하여 GPS의 정확도 저하나 음영지역에서의 위치 측정방법으로 사용하고 있다. 그러나 이러한 측위 방법은 대형화되는 빌딩 지역, 터널, 지하 주차장 등 다양한 음영지역과 시간이 지남에 따라 오차가 계속 증가하는 누적 기반 위치추정 방법의 한계로 인해 많은 문제 요소가 있다. 본 논문은 GPS 음영지역에서 차량의 위치 측위를 위해, 대중적 무선 통신인 WLAN을 이용한 Fingerprint 기법을 4개의 Anchor 형태로 AP(Access Point)와 지향성 안테나를 위치하여 넓은 지하 주차공간에서 효율적인 측위 방법을 제시하고 시간이 지남에 따라 주차된 차량이 이동하는 환경에서도 변화가 없는 위치 측위 결과를 입증하였다.

Recently, the radio navigation method utilizing the GPS(Global Positioning System) satellite information is widely used as the method to measure the position of objects. As GPS applications become wider and fields based on various positioning information emerge, new methods for achieving higher accuracy are required. In the case of autonomous vehicles, the INS(Inertial Navigation System) using the IMU(Inertial Measurement Unit), and the DR(Dead Reckoning) algorithm using the in-vehicle sensor, are used for the purpose of preventing degradation of accuracy of the GPS and to measure the position in the shadow area. However, these positioning methods have many elements of problems due not only to the existence of various shaded areas such as building areas that are continually enlarged, tunnels, underground parking lots and but also to the limitations of accumulation-based location estimation methods that increase in error over time. In this paper, an efficient positioning method in a large underground parking space using Fingerprint method is proposed by placing the AP(Access Points) and directional antennas in the form of four anchors using WLAN, a popular means of wireless communication, for positioning the vehicle in the GPS shadow area. The proposed method is proved to be able to produce unchanged positioning results even in an environment where parked vehicles are moved as time passes.

키워드

참고문헌

  1. Jung J., Kim K., Yoo S., Lee S. and Kim H.(2014), "Indoor Localization based on the observation of distance using RSSI value," Communications of the Korean Institute of Information Scientists and Engineers, pp.379-380.
  2. Kim H., Kim Y. and Park B.(2018), "Selecting a Landmark for Repositioning Driving Vehicle in a Tunnel," The Korea Institute of Intelligent Transport Systems, vol. 17, pp.200-209. https://doi.org/10.12815/kits.2018.17.5.200
  3. Kim S., Moon J. and Bae I.(2015), "Review and Future Perspectives on the Indoor Positioning Technology for Indoor Navigation and Autonomous Parking Service," The Korean Society of automotive Engineers, vol. 37, pp.35-42.
  4. Lee S. and Moon N.(2018), "Design and Implementation of Indoor Location Recognition System based on Fingerprint and Random Forest," The Korean Institute of Broadcast and Media Engineers, vol. 23, pp.154-161.
  5. Lim J. and Choi G.(2011), "A Study on a Location Determination System using Infrastructure Information of a WLAN Network," The Korea Institute of Intelligent Transport Systems, vol. 10, pp.98-107.
  6. Nam D. and Han H.(2008), "Indoor Positioning System Using Fingerprinting Technique," The Korea Institute of Intelligent Transport Systems, vol. 7, pp.1-9.
  7. Park H., Min G., Zin H., Kim Y. and Kim C.(2015), "An effective AP alignment for the Wi-Fi signal based location," Communications of the Korean Institute of Information Scientists and Engineers, pp.1205-1207.
  8. Paul A. S. and Wan E. A.(2009), "Rssi-based indoor localization and tracking using sigma-point kalman smoothers," IEEE Transactions on Mobile Computing, vol. 3. pp.860-873.
  9. Pu Y. C. and You P. C.(2018), "Indoor positioning system based on BLE location fingerprinting with classification approach," Applied Mathematical Modelling, vol. 62, pp.654-663. https://doi.org/10.1016/j.apm.2018.06.031
  10. Sheu J., Chen P. and Hsu C.(2008), "A Distributed Localization Scheme for Wireless Sensor Network with Improved Grid-Scan and Vector-based Refinement," IEEE Transactions on Mobile Computing, vol. 7, pp.1110-1123. https://doi.org/10.1109/TMC.2008.35
  11. Son S., Park Y., Kim B. and Baek Y.(2013), "Wi-Fi Fingerprint Location Estimation System Based on Reliability," The Korean Institute of Communications and Information Sciences, vol. 38, pp.531-539.
  12. Wang Y., Xu Y., Yutian Z., Yue L. and Cuthbert L.(2013), "Bluetooth positioning using RSSI and triangulation methods," IEEE 10th Consumer Communications and Networking Conference(CCNS), pp.837-842.