Boquan Liu

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.

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.

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.