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

被引：0

作者：

Kyung, Yeosun ^{[1
]}

Lee, Seung Joon ^{[1
]}

Kim, Minchul ^{[1
]}

Lee, Chang Won ^{[1
]}

Jung, Kyung Kwon ^{[2
]}

Eom, Ki-Hwan ^{[1
]}

机构：

[1] Dongguk Univ, 26 Pil Dong,3 Ga, Seoul, South Korea

[2] Korea Elect Technol Inst, U Embedded Convergence Res Ctr, Seongnam, South Korea

来源：

ADVANCED COMPUTER SCIENCE AND INFORMATION TECHNOLOGY | 2011年 / 195卷

关键词：

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

D O I：

暂无

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

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.

引用

页码：170 / +

页数：2

共 8 条

[1]

Buettner M., 2008, P 6 ACM C EMB NETW S

[2]

Chen H., 2011, J NETWORK COMPUTER A, V34

[3]

Driankov Dimiter., 1996, INTRO FUZZY CONTROL, Vsecond

[4]

Gen M., 1999, GENETIC ALGORITHMS E, V7