Spectrum Fitting Approach for Passive Wireless SAW Sensor Interrogation Using Software-Defined Radio
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Updated: Sep 18, 2025

Effective Analysis of Human Exposure Conditions with Body-worn Dosimeters in the 2.4 GHz Band
Published on: May 2, 2018
Shihao Wang1, Qi Wang1, Guopeng Zhu1
1Information & Telecommunications Company, State Grid Shandong Electric Power Company, Jinan 250013, China.
Abstract:
Passive wireless surface acoustic wave (SAW) sensors are widely adopted for monitoring the safety status of industrial equipment due to their compact size and maintenance-free operation. Replacing traditional discrete-component interrogators with software-defined radio (SDR) architectures offers lower cost and greater flexibility. However, conventional frequency estimation methods often rely on iterative algorithms with high computational complexity, limiting their real-time applicability. This paper presents an SAW sensing system based on an SDR platform and a non-iterative spectrum-fitting method for SAW frequency measurement. The feasibility of the proposed method is theoretically analyzed, and its performance under different window functions and length of fast Fourier transform (FFT) configurations is evaluated through simulations and experimental measurements. The results demonstrate a favorable trade-off between time efficiency and SAW frequency measurement accuracy. Compared to traditional approaches, the proposed method reduces complexity while maintaining ± 3kHz peak-to-peak accuracy with only 4096-point FFT length according to experimental results.
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