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Noise Reducing of Multi-sensor RFID System by Improved Kalman Filter

  • Yeosun Kyung
  • Seung Joon Lee
  • Minchul Kim
  • Chang Won Lee
  • Kyung Kwon Jung
  • Ki-Hwan Eom
Conference paper
  • 749 Downloads
Part of the Communications in Computer and Information Science book series (CCIS, volume 195)

Abstract

For reducing noise in multi-sensor RFID (Radio Frequency Identification) system, we proposed the GA-Kalman Filter method in this paper. The proposed method is that membership functions of the fuzzy logic system are optimized by genetic algorithm (GA) under off-line, and then fuzzy logic system is constructed by the optimization parameters under on-line. Multi-sensors, humidity, oxygen and temperature, are used to our experiments, and are impacted by correlated noises. One of the most important factors of RFID sensor network system is accuracy in sensor data measurement. However, correlated noises are occurred in multi-sensor system. Kalman Filter has been widely applied to solve the noise problem which is occurred sensor data measurement. In this paper, the proposed GA-Fuzzy Kalman Filter method has the noise reducing compared to the general Kalman Filter method.

Keywords

Multi-Sensor System Kalman Filter RFID GA-Fuzzy Kalman Filter Noise Reducing 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Yeosun Kyung
    • 1
  • Seung Joon Lee
    • 1
  • Minchul Kim
    • 1
  • Chang Won Lee
    • 1
  • Kyung Kwon Jung
    • 2
  • Ki-Hwan Eom
    • 1
  1. 1.Electronic EngineeringDongguk UniversitySeoulKorea
  2. 2.U-embedded Convergence Research CenterKorea Electronics Technology InstituteGyeonggi-doKorea

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