Earticle

초록

영어

Vehicle intelligent position systems based on Received Signal Strength Indicator (RSSI) in WirelessSensor Networks (WSNs) areefficientlyutilized. The vehicle’s position accuracy is of great importance for transportation behaviors, such as dynamic vehicle routing problems and multiple pedestrian routing choice behaviors and so on. Therefore, a precise position and available optimization is necessary for total parameters of conventional RSSI model. In this papar, we investigate the experimental performance of translating the power measurements to corresponding distance between eachpair of nodes. The priori knowledge about the environment interference could impact the accuracy of vehicles’s position and the reliability of paremeters greatly. Based on the real-world outdoor experiments, we compares different regression analysis of the RSSI model, in order to establish a calibration scheme on RSSI model. Empirical experimentation shows that the average errors of RSSI model is able to decrease throughout therules of environmental factor n and shadowing factor ηrespectively. Moreover, the calculation complexity is reduced, as aninnovative approach. Since variation tendency of environmental factor n, shadowing factor η with distance and signal strength could be simulated respectively, RSSI model fulfills the precision of the vehicle intelligent position system.

목차

Abstract
 1. Introduction
 2. Experiment
  2.1 Background
  2.2 Distance Estimation
 3. Model Formulation
  3.1 Influencing Factors of RSSI
  3.2 Diachronic RSSI model[24]and applied environment
  3.3 Comparison of RSSI Model
  3.4 The relationship between influence factors and errors in RSSI model
 4. Experiments’Evaluation
  4.1 The Relationship between Environmental Factor n and Error
  4.2 The relationship between shadowing factor η and error
 5. Conclusions and Future Work
 Acknowledgements
 References
 Appendix list

키워드

저자

• Zhichao Cao [ MOE Key Laboratory for Urban Transportation Complex Systems Theory and Technology, Beijing Jiaotong University ]
• ZhenzhouYuan [ MOE Key Laboratory for Urban Transportation Complex Systems Theory and Technology, Beijing Jiaotong University ]
• Silin Zhang [ MOE Key Laboratory for Urban Transportation Complex Systems Theory and Technology, Beijing Jiaotong University ]

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