The resonant surface acoustic wave (SAW) sensors have advantages in the harsh application environments. However, the burst noise in the same frequency range, signal shadowing and a range of weather conditions introduce strong interferences to the wireless measurement system. Inspired by the theory of low-rank matrix completion generalized from the compress sensing, an algorithm suitable for passive wireless SAW temperature sensor system, which requires none of system modeling, probability distribution assumption, and extra sensors to obtain the corrected current frequency, is used to correct errors in the resonant frequency measurement. The proposed method suitable for passive wireless SAW resonant sensor system is employed to correct the frequency estimation errors in the measuring process. The performance and its validity are verified by simulations and experiments.
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