Optimization of resonant frequency measurement algorithm for wireless passive SAW sensors

The paper is devoted to reduction of random errors in the wireless measurement of the resonant frequency of a SAW resonant sensor. It is achieved by using weighted averaging of multiple measurement results where the weights depend on the strength of the SAW responses picked up by the interrogation receiver. Optimum weights are found either by analytical method based on statistical information collected for a wireless tire pressure monitoring system (TPMS) or by means of genetic optimization algorithm using numerical model of the sensor. The optimized weights allow reduction of the time needed for averaging by at least a factor of two in comparison with simple averaging required to achieve the same standard deviation of the measured frequency.