Journal of the Korea Institute of Information and Communication Engineering (한국정보통신학회논문지)

The Korea Institute of Information and Commucation Engineering (한국정보통신학회)
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High Accuracy Indoor Location Sensing Solution based on EMA filter with Adaptive Signal Model in NLOS indoor environment

NLOS 실내 환경 하에서 측위 정확도 개선을 위한 EMA 필터 적용 적응적 신호 모델 기반 위치 센싱 솔루션

  • Ha, Kyunguk (Department of Electronic Engineering, Dong-A University) ;
  • Cha, Myeonghun (Department of Electronic Engineering, Dong-A University) ;
  • Kim, Dongwan (Department of Electronic Engineering, Dong-A University)
  • Received : 2019.04.24
  • Accepted : 2019.05.09
  • Published : 2019.07.31
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Abstract

In this paper, we proposed a new trilateration technique based on exponential moving average (EMA) filter with adaptive signal model which enhances accuracy of positioning system even if the RSSI changes randomly due to movement of obstacles or blind node in indoor environment. In the proposed scheme, three fixed transmitters sent out the signal to blind node. The transmitter decides the location of the blind node based on RSSI and it estimates the cause of RSSI fluctuation which is interference of obstacle or movement of blind node. When the path between blind node and transmitter has become NLOS path because of obstacles, the transmitter ignores the measured RSSI in NLOS path and replace estimated RSSI in LOS environment. In the other case, the transmitter updated the new RSSI to represent of movement of blind node. The proposed scheme has been verified on a ZigBee testbed and we proved the improved positioning accuracy compared to the existing indoor position system.

본 논문에서는 실내 환경에서 blind 노드가 이동하거나 움직이는 장애물 (ex. 사람)로 인하여 RSSI가 급격히 변하더라도 정확한 blind 노드 측위를 가능하게 하는 exponential moving average (EMA) 필터 적용 적응적 신호 모델 기반 삼변측량기법을 제안한다. 제안된 EMA 필터 적용 적응적 신호 모델 기반 삼변측량기법은 고정된 세 개의 전파 송신 노드와 blind 노드 간 얻어진 RSSI를 통해 blind 노드의 위치를 측정한다. 또한 외부 환경 요인으로 인해 RSSI가 급격히 변화할 경우 non-LOS (NLOS) 환경인 것인지 혹은 blind 노드의 이동으로 인한 RSSI 변화인지를 판별한다. Blind 노드와 전파 송신 노드 사이 경로가 NLOS 환경이 되었다고 판단될 경우 LOS 환경에서 측정된 RSSI를 기반으로 NLOS 환경에서 측정된 RSSI를 보정하여 blind 노드의 좌표를 도출하고, blind 노드가 이동하였다고 판단된다면 실시간 측정된 RSSI를 이용하여 blind 노드의 좌표를 도출한다. 제안 기법은 ZigBee 기반 testbed를 통해 검증하였으며, NLOS 환경 혹은 blind 노드가 이동하는 환경 하에서 기존 기법 대비 개선된 위치 인식 정확도를 가짐을 증명하였다.

Keywords

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Fig. 1 Trilateration technique

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Fig. 2 Evaluation of EMA filter in LOS environment (a) Fixed node, (b) Moving node

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Fig. 3 RSSI value between LOS environment and human existing

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Fig. 4 Cases that the people exist in the paths between transmitters and blind node (a) Case 1 that the people exist in the one path (b) Case 2 that the people exist in the two paths (c) Case 3 that the people exist in the three paths (d) Distance change by moving nodes

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Fig. 5 Algorithm of Trilateration technique based on EMA filter with adaptive signal model

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Fig. 6 Compare coordinates between existing methods and proposed method. (a) 1 path, (b) 2 paths, (c) 3 paths

Table. 1 Evaluation of filter performance – fixed node in LOS environment

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Table. 2 Evaluation of filter performance – moving node in LOS environment

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Table. 3 Results of proposed scheme. actual coordinate of blind node is (2,1)

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