In this paper, a recursive least squares (RLS)-based demodulator is proposed for Electrical Tomography (ET) that employs sinusoidal excitation. The new demodulator can output preliminary demodulation results on amplitude and phase of a sinusoidal signal by processing the first two sampling data, and the demodulation precision and signal-to-noise ratio can be further improved by involving more sampling data in a recursive way. Thus trade-off between the speed and precision in demodulation of electrical parameters can be flexibly made according to specific requirement of an ET system. The RLS-based demodulator is suitable to be implemented in a field programmable gate array (FPGA). Numerical simulation was carried out to prove its feasibility and optimize the relevant parameters for hardware implementation, e.g., the precision of the fixed-point parameters, sampling rate, and resolution of the analog to digital convertor. A FPGA-based capacitancemeasurement circuit for electrical capacitancetomography was constructed to implement and validate the RLS-based demodulator. Both simulation and experimental results demonstrate that the proposed demodulator is valid and capable of making trade-off between demodulation speed and precision and brings more flexibility to the hardware design of ET systems.
Received 03 January 2013Accepted 22 March 2013Published online 10 April 2013
The authors gratefully acknowledge the financial support from the National Natural Science Foundation of China (Grant Nos. 61001135, 61121003, and 61225006) and the Fundamental Research Funds for the Central Universities (YWF-11-03-Q-072).
Article outline: I. INTRODUCTION II. METHODOLOGY A. Mathematical model B. RLS-based demodulator III. IMPLEMENTATION AND PARAMETERS OPTIMIZATION A. Read only memory (ROM)-based implementation of the RLS-based demodulator in FPGA B. Parameters optimization 1. Round-off error 2. Sampling rate of the ADC 3. Resolution of the ADC IV. RESULTS AND DISCUSSION A. Hardware description B. Experiment and results C. Discussion V. CONCLUSION
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