基于遗传算法的声表面波回波频率估计

Wireless passive surface acoustic wave resonator is widely used in temperature, pressure, torque sensor. The sensor parameters are usually detected by measuring the surface acoustic wave sensing echo signal frequency, therefore, the accuracy of echo signal frequency estimation directly affects the performance of the sensor.Since the echo signal is exponentially decaying, the duration is generally about 10 us. The conventional frequency-domain analysis method is limited by the sampling frequency and the number of data points, and the resolution of frequency estimation is greatly limited.This paper combined time domain fitting with genetic algorithm to estimate SAW echo signal frequency.For the problem that the conventional genetic algorithm needs to estimate the amplitude, phase, frequency and envelope of the signal at the same time leads to the slow speed of the estimation and the poor real time, the Hilbert transform is used to remove the signal envelope and estimate its amplitude and the segmented FFT method is used to analyze the initial phase of the signal. Based on that, the genetic algorithm is optimized to achieve the SAW echo signal frequency estimation under a single parameter.The measurement of frequency detection system based DSP shows that the frequency estimation error is less than 3KHz, the frequency estimation time is less than 1s, and the efficiency is obviously higher than that of the conventional genetic algorithm under the condition of sampling points is only 80 points.