Wavelet Denoising Method Based On Labview Rfid Rf Signal

LabVIEW is a graphical programming language and development environment, launched by National Instrument of the United States. It has the characteristics of easy to learn, convenient and intuitive, powerful function and so on. LabVIEW is a powerful data acquisition and processing software, which can achieve real-time signal acquisition and processing, so that data acquisition, data analysis and data display can be integrated into a single environment seamlessly.Radio Frequency Identification technology (RFID) is a non-contact automatic identification technology, which achieve communication using radio frequency (RF) signal. It owns many virtues:efficient, fast, reliable, non line of sight reading and applied to work under atrocious conditions. So it is widely used in data acquisition and product recognition and other fields. The RF signal will introduce noise during the communication between readers and tags. Therefore, it is vitally necessary to reduce noise before the related operation on received RF signal.The current denoising methods are the traditional fast Fourier transform (FFT) filtering and wavelet denoising method. FFT denoising method is only suitable for stationary random signal and the case of separation of signal and noise, and the entropy of the signal increases after changes, so it is difficult to get the correlation of signal. RF signal is non-stationary signal, so the traditional FFT denoising method can not achieve good noise reduction.The wavelet analysis method has obvious advantages in denoising, which can be used for non-stationary signal denoising with the characteristics of multi-resolution analysis. The method can not only effectively remove noise, but also better preserve the abrupt change point of the signal.To reduce the noise in received RF signal and then improve the performance of RFID system, a novel denoising method of wavelet analysis in RFID system was proposed in this paper, and the effect of the denoising method was tested via simulation experiment. The paper studied RFID and wavelet transform theories, and analyzed wavelet denoising method and FFT denoising method. Wavelet threshold denoising method was introduced in detail. In view of non-stationary signal, the rectangular signal added Gaussian white noise was denoised with two threshold functions and four threshold selection forms in Matlab, and the denoising results were compared. In LabVIEW according to the standard ISO/IEC14443 RF signal at 13.56MHz was simulated using modulation toolbox, and the simulated RF signal with noise was denoised by wavelet transform method and FFT method respectively. Simulation results show wavelet denoising method has better effect, compared with traditional FFT denoising method. The research on application of wavelet analysis in RF signal denoising is significant and practical. That wavelet analysis is applied to the field of virtual instrument can provide people with more accurate and convenient testing, and has good application prospects in engineering applications.