The System Of RFID Hopping Spectrum Spread Spectrum Time Frequency Analysis Based On S Transform

"The internet of things" was known as the third wave of global information industry after computer and internet. RFID system was applied as the important component, which play an important role in it. With the diffusion and application of the RFID technology, more and more attention was paid to safety and reliability properties of RFID system. The signal was often disturbed by noise during transmission and restoring it at reception, so that deteriorates the communication quality of system. RFID spread spectrum system was extensively used for modern communication system due to their low detection rate, large capability and capabilities overcome multi-path interference. Many new methods based on joint time-frequency were presented in order to help us extracted signal features, such as fast Fourier transform, Wavelet transform and Wigner-Ville distribution, but all of them have some disadvantages to some extend.This paper proceed form the present state of RFID technology, the principle of RFID frequency-hopping spread spectrum system was discussed and the present state of joint time-frequency analysis was described. In the chapter two, the basic principle of direct sequence spread spectrum systems and frequency-hopping spread spectrum systems were researched, and their implement methods were stated. By simulation, the results show that the larger the carrier rate, the lower error rate when pseudorandom sequence was the same; the higher speed of pseudorandom sequence, the lower error rate when the carrier rate and pseudorandom sequence were the same. In the third chapter, three typical joint time-frequency analysis methods were researched. Such as fast Fourier transform, Wavelet transform and Wigner-Ville distribution, then analyze the advantage and disadvantage of them. With consideration of limitation of the one-dimensional time-frequency filtering and the cross-term interference, the basic principle of S-transform was introduced in the fourth chapter; some measures were taken to improve S-transform using add regulatory factors, and to make its time-frequency resolution better. In that case, the concept of generalized S-transform was presented. According to the characteristics of hopping-frequency spread spectrum systems, S-transform was adopted for joint time-frequency analysis, what’s more, two dimensional time-frequency filtering using generalization S-transform was presented. Compared with one-dimensional filtering, two dimensional time-frequency filtering of S transform has better performance. Generalized S transform has higher resolution than S transform. The simulation results show that the method is accurate and effective.