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Multi-directional DRSS Technique for Indoor Vehicle Navigation

실내 차량 내비게이션을 위한 다방향 DRSS 기술

  • Kim, Seon (Department of Radio and Information Communications Engineering, Chungnam National University) ;
  • Park, Pangun (Department of Radio and Information Communications Engineering, Chungnam National University)
  • Received : 2022.04.28
  • Accepted : 2022.05.26
  • Published : 2022.06.30

Abstract

While indoor vehicle navigation is an essential component in large-scale parking garages of major cities, technical limitations and challenging propagation environments considerably degrade the accuracy of existing localization techniques. This paper proposes a proximity detection scheme using low-cost beacons where a handheld mobile device within a moving vehicle autonomously detects its approximate position and moving direction by only observing Received Signal Strength (RSS) values of beacon signals. The proposed approach essentially exploits the differential RSS technique of multi-directional beams to reduce the impact of the environment, vehicle, and mobile device. A low-cost multi-directional beacon prototype is developed using Bluetooth technology. The localization performance is evaluated using 96 beacons in an underground parking garage within an area of 394.8m×304.3m. Experimental results show that the 90th percentile of the average proximity detection error is 0.8m. Furthermore, our proposed scheme provides robust proximity detection performance with various vehicles and mobile devices.

주요 도시의 대규모 주차장에서 실내 차량 측위는 필수 구성 요소지만, 다양한 기술적 한계 및 불완전한 무선 채널 환경은 기존 측위 기법의 정확도를 심각하게 저하시킨다. 본 논문은 저비용 비콘을 활용하여 실내 공간 내 이동 차량이 비콘의 RSS (Received Signal Strength) 값만을 사용하여 근접 비콘 및 이동 방향을 감지하는 기법을 제시한다. 제안된 근접 감지 기법은 다방향 DRSS (Differential RSS) 기술을 활용하여 주위 환경, 차량 및 모바일 기기의 영향을 최소화한다. 본 논문에서는 저가의 블루투스 모듈을 사용하여 다방향 비콘 프로토타입을 개발하였으며, 측위 성능은 394.8m×304.3m 대규모 면적의 실제 지하 주차장에 96개의 비콘을 설치하여 관련 성능을 평가하였다. 실험 결과 근접 감지 오차의 90번째 백분위수는 0.8m이며, 제안된 기법은 다양한 차량 및 모바일 기기의 영향을 최소화하여 강건한 근접 감지 성능을 보장한다.

Keywords

Acknowledgement

This result was supported by "Regional Innovation Strategy (RIS)" through the National Research Foundation of Korea(NRF) funded by the Ministry of Education(MOE)(2021RIS-004).

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