Earticle

초록

영어

RFID-based location awareness is becoming the most important issue in many fields in recent years, such as ubiquitous computing, mobile computing. In indoor localization systems RSSI-based methods are usually used in office buildings. However, RSSI is susceptible to external influences, and performances unstably due to the environmental factors affecting signal propagation. In this paper, we propose a new hybrid localization method for tracking moving object using the two typical methods which are signal propagation model and fingerprinting. According to a threshold which is defined as an effective working distance of signal propagation model between target tag and RFID reader, we choose the different localization algorithm to estimate the location of moving object. The threshold is obtained by calculating the slop of signal attenuation curve. If the distance is within the effective reading range of RFID reader, we revise signal propagation model by maximum likelihood estimation and use it to calculate the object position by minimum cumulative error. Otherwise, the fingerprinting location method is used in the external area, and the particle filter is also used as the core algorithm. The experimental results show that our method not only reduces the computation complexity but also ensures the accuracy in large indoor area.

목차

Abstract
 1. Introduction
 2. Hybrid Location Approach
  2.1. The Signal Propagation Mode
  2.2. Fingerprinting Location Approach
  2.3. Determine the Border of the Propagation Model
 3. Experiment Analysis
 4. Conclusions
 Acknowledgements
 References

키워드

저자

• Junhuai Li [ School of Computer Science & Engineering,Xi'an University of Technology, Xi'an 710048,China ]
• Bo Zhang [ School of Computer Science & Engineering,Xi'an University of Technology, Xi'an 710048,China ]
• Hailing Liu [ College of Electronic Information Engineering,Chongqing University of Science and Technology,Chongqing 400050,China. ]
• Lei Yu [ School of Computer Science & Engineering,Xi'an University of Technology, Xi'an 710048,China ]
• Zhixiao Wang [ School of Computer Science & Engineering,Xi'an University of Technology, Xi'an 710048,China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Smart Home

• 간기

  격월간

• pISSN

  1975-4094

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605