저밀도 USN 환경을 위한 Range-hybrid 기반의 향상된 이동객체 추적기법

An Enhanced Mobile Object Tracking Method based on Range-hybrid for Low-Density USN Environment

  • 박재복 (전북대학교 전자정보공학부) ;
  • 조기환 (전북대학교 컴퓨터공학부, 영상정보신기술연구센터)
  • Park, Jae-Bok (Division of Electronics and Information Engineering, Chonbuk National University) ;
  • Cho, Gi-Hwan (Division of Computer Science & Engineering, Chonbuk National University, CAIIT)
  • 발행 : 2010.03.25

초록

위치측정은 사용자나 사물에게 주변 환경에 대한 인식을 가능케 하는 기본적인 요소이기 때문에 센서네트워크 환경에서는 가장 핵심적인 요소이다. 기존 위치측정 기법은 크게 Range-based방식과 Range-free방식으로 나눌 수 있다. Range-based방식은 전파의 불규칙하고 추가 장비가 필요한 반면에 Range-free방식은 능동적인 통신을 수단으로 위치를 측정하므로 자원제약적인 센서네트워크에서는 적합한 것으로 알려져 있다. 그러나 위치측정의 정확성이 주변노드의 수에 따라 크게 좌우된다. 특히 밀집도가 낮은 센서네트워크 환경에서는 위치측정의 정확성이 매우 낮다. 본 논문에서 제안된 DRTS(Distributed Range-hybrid Tracking Scheme)는 Range-based와 Range-free방식을 혼합하고 주변노드의 위치와 통신범위 및 세기정보를 최대한 활용하여 이동물체를 추적할 수 있는 기법을 제시한다. 특히 주변노드를 최대한 활용한 효율적인 위치측정기법과 제안된 EGP(Estimative Gird Points)의 예측기법을 활용하여 위치추적의 정확성을 획기적으로 개선할 수 있는 방안을 제시한다. 그리고 시뮬레이션 결과를 통해 기존 위치추적 알고리즘 보다 추적의 정확도 관점에서 제안된 기법의 성능이 우수함을 증명하였다.

Localization is the most important feature in the sensor network environment because it is a basic element enabling people and things to aware the circumference environment. Existing localization methods can be categorized as either range-based or range-free. While range-based is known to be not suitable because of the irregularity of radio propagation and the additional device requirement. range-free is much appropriated for the resource constrained sensor network because it can actively locate by means of the communication radio. But its location accuracy is just depended on the density of circumference nodes; it is very low in low-density sensor network environment. This paper proposes a mobile object tracking method, named DRTS(Distributed Range-hybrid Tracking Scheme), with combining range-based and range-free. It is optimally making use of the location, communication range, and received signal strength from circumference nodes. Especially, it can greatly improve the mobile tracking accuracy by adapting a new prediction method, named EGP(Estimative Gird Points) into the proposed location estimation method. The simulation results show that our method outperforms the other localization and tracking methods in the tracking accuracy point of view.

키워드

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