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Improved Kalman Filter Method for Measurement Noise Reduction in Multi Sensor RFID Systems
Department of Electronic Engineering, Dongguk University, 26, Pil-dong 3-ga, Jung-gu, 100-715, Seoul, Korea
* Author to whom correspondence should be addressed.
Received: 12 October 2011; in revised form: 24 October 2011 / Accepted: 24 October 2011 / Published: 28 October 2011
Abstract: Recently, the range of available Radio Frequency Identification (RFID) tags has been widened to include smart RFID tags which can monitor their varying surroundings. One of the most important factors for better performance of smart RFID system is accurate measurement from various sensors. In the multi-sensing environment, some noisy signals are obtained because of the changing surroundings. We propose in this paper an improved Kalman filter method to reduce noise and obtain correct data. Performance of Kalman filter is determined by a measurement and system noise covariance which are usually called the R and Q variables in the Kalman filter algorithm. Choosing a correct R and Q variable is one of the most important design factors for better performance of the Kalman filter. For this reason, we proposed an improved Kalman filter to advance an ability of noise reduction of the Kalman filter. The measurement noise covariance was only considered because the system architecture is simple and can be adjusted by the neural network. With this method, more accurate data can be obtained with smart RFID tags. In a simulation the proposed improved Kalman filter has 40.1%, 60.4% and 87.5% less Mean Squared Error (MSE) than the conventional Kalman filter method for a temperature sensor, humidity sensor and oxygen sensor, respectively. The performance of the proposed method was also verified with some experiments.
Keywords: smart RFID tags; Kalman filter; neural network; multi-sensing environment; measurement noise reduction
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Cite This Article
MDPI and ACS Style
Eom, K.H.; Lee, S.J.; Kyung, Y.S.; Lee, C.W.; Kim, M.C.; Jung, K.K. Improved Kalman Filter Method for Measurement Noise Reduction in Multi Sensor RFID Systems. Sensors 2011, 11, 10266-10282.
Eom KH, Lee SJ, Kyung YS, Lee CW, Kim MC, Jung KK. Improved Kalman Filter Method for Measurement Noise Reduction in Multi Sensor RFID Systems. Sensors. 2011; 11(11):10266-10282.
Eom, Ki Hwan; Lee, Seung Joon; Kyung, Yeo Sun; Lee, Chang Won; Kim, Min Chul; Jung, Kyung Kwon. 2011. "Improved Kalman Filter Method for Measurement Noise Reduction in Multi Sensor RFID Systems." Sensors 11, no. 11: 10266-10282.