• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.10
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• pp.1861-1868
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• 2008

In this paper, Passive Telemerty RF Sensor System using Unscented Kalman Filter algorithm(UKF) is proposed. General Passive Telemerty RF Sensor System means that it should be "wireless", "implantable" and "batterless". Conventional Passive Telemerty RF Sensor System adopts Integrated Circuit type, but there are defects like complexity of structure and limit of large power consumption in some cases. In order to overcome these kinds of faults, Passive Telemetry RF Sensor System based on inductive coupling principle is proposed in this paper. Because passive components R, L, C have stray parameters in the range of high frequency such as about 200[KHz] used in this paper, Passive Telemetry RF Sensor System considering stray parameters has to be derived for accurate model identification. Proposed Passive Telemetry RF Sensor System is simple because it consists of R, L and C and measures the change of environment like pressure and humidity in the type of capacitive value. This system adopted UKF algorithm for estimation of this capacitive parameter included in nonlinear system like Passive Telemetry RF Sensor System. For the purpose of obtaining learning data pairs for UKF Algorithm, Phase Difference Detector and Amplitude Detector are proposed respectively which make it possible to get amplitude and phase between input and output voltage. Finally, it is verified that capacitive parameter of proposed Passive Telemetry RF Sensor System using UKF algorithm can be estimated in noisy environment efficiently.

• Journal of Advanced Marine Engineering and Technology
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• v.28 no.4
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• pp.569-576
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• 2004

In this paper, passive telemetry capacitive humidity sensor system using a RLSE(Recursive Least Square Estimation) technique is proposed. To overcome the problem like power limits and complications that general passive telemetry sensor system including IC chip has, the principle of inductive coupling is applied to model the sensor system. Specially. by applying the forgetting factor we show that the accuracy of its estimation can be improved even in the case of time varying parameter and also the convergence time can be reduced.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.5
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• pp.858-865
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• 2008

In this paper, Capacitive Telemetry RF Sensor System using Recursive Least Square (RLS) algorithm was proposed. General Telemetry RF Sensor System means that it should be "wireless", "implantable" and "batterless". Conventional Telemetry RF Sensor System adopts Integrated Circuit type, but there are many defects like complexity of structure and the limitation of large power consumption in some cases. In order to overcome these disadvantages, Telemetry RF Sensor System based on inductive coupling principle was proposed in this paper. Proposed Telemetry RF Sensor System is very simple because it consists of R, L and C and measures the changes of environment like pressure and humidity in the type of capacitive value. This system adopted RLS algorithm for estimation of this capacitive parameter. For the purpose of applying RLS algorithm, proposed system was mathematically modelled with phasor method and was quasi-linearized. As two parameters such as phase and amplitude of output voltage for estimation were needed, Phase Difference Detector and Amplitude Detector were proposed respectively which were implemented using TMS320C2812 made by Texas Instrument. Finally, It is verified that the capacitance of proposed telemetry RF Sensor System using RLS algorithm can be estimated efficiently under noisy environment.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.04a
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• pp.495-498
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• 2004

In this paper, passive telemetry capacitive humidity sensor system using a RLSE(Recursive Least Square Estimation) technique Is proposed. To overcome the problem like power limits and complications that general passive telemetry sensor system including IC chip has, the principle of inductive coupling is applied to model the sensor system. Specially, by applying the forgetting factor, we show that the accuracy of its estimation can be improved even in the case of time varying parameter and also the convergence time can be reduced.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.10a
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• pp.515-520
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• 2004

In this paper, a passive telemetry RF capacitive humidity sensor system using a RLSE(Recursive Least Square Estimation) technique is proposed. To overcome these trouble problems such as a power limitation and a estimation complexity that the general passive telemetry sensor system including It chip has, the principle of inductive coupling was applied to the modeling of a passive telemetry RF capacitive humidity sensor system and its capacitance was estimatedd by the RLSE algorithm. Specially, by introducing the optimal forgetting factor, we showed that the accuracy of its estimation was improved even in the time varying system and also the convergence time was reduced.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2007.11a
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• pp.131-137
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• 2007

본 연구에서는 RLS(Rescursive Least Square) 추정 알고리즘을 이용하여 정전용량형 센서를 사용한 원격 RF 센서 시스템을 구현하고자 한다. IC 칩 형태의 원격 RF 센서 시스템이 가지는 구성의 복잡성 그리고 전력소모 문제를 해결하기 위해 보다 간단한 유도결합모델이 제안된다. 원격 RF 시스템은 페이저법을 이용하여 수학적으로 모델링되며, 모델기반의 RLS 알고리즘을 적용하기위해 시스템의 파라메타를 재배열한다. 오차 제곱합의 수렴특성을 가진 RLS 알고리즘을 이용하여 정전용량 파라메타를 추정한다. 실제 위상차를 측정하기 위해 Exclusive OR를 이용한 위상차 감지 장치를 제안한다. 센서로는 각종 환경 측정-습도, 압력 등-에 실제 활용되고 있는 정전용량형 센서를 채택한다. 잡음을 내포한 측정 데이터에 대한 추정 성능을 확인함으로써 그 유효성을 검증하고자 한다.

• Proceedings of the KIEE Conference
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• 2007.04c
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• pp.29-33
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• 2007

In this paper, time-varying parameter of passive telemetry RF sensor system is estimated using RLS(Rescursive $\leq$* Square) algorithm. In order to overcome the problems such as power limits and complication that general RF sensor system including IC chip has, the principle of inductive coupling is applied to model sensor system The model parameter is rearranged for applying RLS algorithm based on mathematical model to the derived model using inductive coupling principle. Time variant parameter of rearranged model is estimated using forgetting factor, and in case measured data is contaminated by noise and modelling error, the performance of RLS algorithm characterized by the convergence of squared error sum is verified by simulation.