Passive wireless surface acoustic wave (SAW) resonant sensors are suitable for applications in harsh environments. The traditional SAW resonant sensor system requires, however, Fourier transformation (FT) which has a resolution restriction and decreases the accuracy. In order to improve the accuracy and resolution of the measurement, the singular value decomposition (SVD)-based frequency estimation algorithm is applied for wireless SAW resonant sensor responses, which is a combination of a single tone undamped and damped sinusoid signal with the same frequency. Compared with the FT algorithm, the accuracy and the resolution of the method used in the self-developed wireless SAW resonant sensor system are validated.

Purpose: This paper aims to propose a noise-robust method to estimate the frequency of the reflective echo to reduce the negative effects of noise and improve the accuracy and resolution of a resonant surface acoustic wave (SAW) sensor. Design/methodology/approach: The proposed approach exploits the singular value decomposition to obtain the frequency information of a SAW response signal and overcome the noise influences. Findings: Compared with the commonly used Fourier transform (FT) method, the accuracy and resolution improvement of the proposed method used in the SAW sensor is validated. Originality/value: The system using the proposed method delivers lesser standard deviation, that is, delivers higher performance than the conventional system using the fast FT method.

Purpose: This paper aims to present an context evaluation and frequency measurement method for surface acoustic wave (SAW) resonant sensor. Design/methodology/approach: This method is based on a signal subspace construction, which, along with assembling optional value set, provides the results. Findings: The method can assess the application context and improve the resolution and accuracy of the passive wireless SAW resonator sensor system. Originality/value: Passive wireless SAW resonators have been used as sensor elements for different physical parameters such as temperature, pressure and force in a number of industrial and medical applications. Various wireless channel environments introduce different application contexts.