A Successive Region Setting Algorithm Using Signal Strength Ranking from Anchor Nodes for Indoor Localization in the Wireless Sensor Networks

실내 무선 센서 네트워크에서의 측위를 위하여 고정 노드 신호들의 크기 순위를 사용한 순차적 구역 설정 알고리즘

  • Received : 2011.02.14
  • Accepted : 2011.06.15
  • Published : 2011.06.25

Abstract

Researches on indoor localization using the wireless sensor network have been actively carried out to be used for indoor area where GPS signal is not received. Computationally efficient WCL(Weighted Centroid Localization) algorithm is shown to perform relatively well. However, to get the best performance for WCL all the anchor nodes must send signal with power to cover 96% of the network. The fact that outside the transmission range of the fixed nodes drastic localization error occurs results in large mean error and deviation. Due to these problems the WCL algorithm is not easily applied for use in the real indoor environment. In this paper we propose SRS(Succesive Region Setting) algorithm which sequentially reduces the estimated location area using the signal strength from the anchor nodes. The proposed algorithm does not show significant performance degradation corresponding to transmission range of the anchor nodes. Simulation results show that the proposed SRS algorithm has mean localization error 5 times lower than that of the WCL under free space propagation environment.

GPS 신호를 수신할 수 없는 실내 지역에 적용하기 위하여 무선 센서 네트워크를 이용한 측위 연구가 진행 중이며 많은 알고리즘들이 제안되고 있다. 기존 알고리즘들 중 WCL(Weighted Centroid Localization)은 하드웨어적으로 제한된 무선 센서 네트워크의 특성을 고려하여 간단한 연산으로 사용자 노드의 좌표를 계산하면서 성능 면에서도 우수함이 입증되어 있다. 그러나 최적의 성능을 얻기 위하여 항상 고정 노드들이 전체 네트워크 범위의 96%로 신호를 전송해야 하는 점과 각 고정 노드의 전송 범위 외곽지역에서 급격한 측위 오차가 발생하여 평균 오차와 편차가 크다는 단점이 있어 실제 실내 환경에 적용시키기 어려운 측면이 있다. 본 논문에서는 각 고정 노드의 신호 세기를 비교하여 사용자 노드가 존재할 가능성이 있는 추정 구역을 순차적으로 좁혀 나가는 측위 알고리즘을 제안하였다. 추정 구역을 최소화 하여 사용자 노드의 위치를 계산함으로써 고정 노드의 전송 범위에 따른 성능 저하와 외곽지역에서 발생하는 최대 오차 문제를 해결하였으며, 평균 오차도 자유공간 전파 환경에서 WCL 알고리즘 보다 5배 정도 감소하는 것을 시뮬레이션을 통해 검증하였다.

Keywords

References

  1. G. Mao and B. Fidan, "Localization Algorithms and Strategies for Wireless Sensor Networks," Information Science Reference, pp.257-258, 2009.
  2. J. Blumenthal, et al., "Weighted centroid localization in Zigbee-based sensor networks," IEEE International Symposium on Intelligent Signal Processing (WISP 2007), pp.1-6, 2007.
  3. R. Behnke, D. Timmermann, "AWCL: Adaptive Weighted Centroid Localization as an Efficient Improvement of Coarse Grained Localization", Proceedings of the 5th Workshop on Positioning, Navigation and Communication, pp.243-250, 2008.
  4. N. Bulusu, J. Heidemann and D. Estrin, "GPS-less Low Cost Outdoor Localization For Very Small Devices," IEEE Personal Communications Magazine, 7, 5, pp. 28-34, October 2000. https://doi.org/10.1109/98.878533
  5. T. He, C. Huang, JA Stankovic, and BM. Blum, "Range-free localization and its impact on large scale sensor networks," ACM transactions on embedded computing systems, Vol.4, no.4, p.877, 2005. https://doi.org/10.1145/1113830.1113837
  6. G. Mao and B. Fidan, Localization Algorithms and Strategies for Wireless Sensor Networks: Information Science Reference, p.136, 2009.
  7. G. P. Yost, S. Panchapakesan, "Improvement in Estimation of Time of Arrival (ToA) from timing advance (TA)," ICUPC 98, Vol 2, pp. 1367-1372, Florence, Italy, October 1998.
  8. A. Harter, A. Hopper, P. Steggles, A. Ward and P. Webster, "The Anatomy of a Context-Aware Application," Mobile Computing and Networking, pp. 59-68, 1999
  9. L. Zhu, J. Zhy, "A New model and Its Performance for TDOA Estimation," VTS2001, Vol 4, pp. 2750-2753, Mariana Del Rey, Ca, USA, October. 2001.
  10. 김동혁, 송승헌, 박경순, 성태경, "TDOA 측정치를 이용한 가중치 추정방식의 QCLS 측위 방법," 전자공학회논문지-SC, pp. 236-242, July 2007.
  11. D. Niculescu and B. Nath, "Ad hoc Positioning System (APS) using AOA," INFOCOM 2003, pp. 1734-1743, Hayatt Regency, CA, USA, March 2003.
  12. Chuan-Chin Pu, Wan-Young Chung, "An Integrated Approach for Positioin Estimation using RSSI in Wireless Sensor Network," Journal of Ubiquitous Convergence Technology, Vol 2, No. 2, pp. 78-87, November 2008.
  13. J. Blumenthal, F. Reichenbach and D. Timmermann, "Position Estimation in Ad hoc Wireless Sensor Networks with Low Complexity," Joint 2nd Workshop on Positioning, Navigation and Communication and 1st Ultra-Wideband Expert Talk, pp. 41-49, March 2005.
  14. S. Pandey, F. Anjum, B. Kim and P. Agrawal, "A low-cost robust localization scheme for WLAN," Proceedings of the 2nd Int.'l Workshop on Wireless Internet, 2006.
  15. D. Niculescu and B. Nath, "DV Based Positioning in Ad hoc Networks," IEEE Telecommunication Systems Vol 1. pp. 267-280, 2003.
  16. R. Nagpal, "Organizing a global coordinate system from local information on an amorphous computer," Technical Report AI Memo No. 1666, MIT A.I. Laboratory, 1999.
  17. T. He et al., "Range-free localization and its impact on large scale sensor networks," Transactions on Embedded Computing Systems, 4, 4, pp. 877-906, 2005. https://doi.org/10.1145/1113830.1113837
  18. E. Elnahrawy, X. Li and R. P. Martin, "Using Area-Based Presentations and Metrics for Localization Systems in Wireless LANs." IEEE International Conference on Local Computer Networks (LCN'04), Washington, USA, 2004.
  19. C.A Balanis, "Antenna Theory: Analysis and Design," John Wiley & Son, pp. 94-96, 2005.
  20. D. Ganesan, B. Krishnamachari, A. Woo, D. Culler, D. Estrin and S. Wicker,"Complex Behavior at Scale: An Experimental Study of Low-Power Wireless Sensor Networks," Technical Report CSD-TR 02-0013, UCLA, February, 2002.