Various types of interference signals are available in the working environment of passive wireless surface acoustic wave (SAW) sensors. Among these kinds of interference, co-channel interference is difficult to suppress. To solve this problem, a SAW sensor anti-interference technology was proposed to improve the reliability of the SAW sensor. Wavelet denoising method was used to denoise SAW resonator (SAWR) response, which can maintain the envelope characteristics of the SAW response. The entropy energy model of the SAW response signal was established, and the signal envelope was extracted from the proposed entropy energy function. The waveform envelope and the entropy energy curve were adopted as the signal characteristics to form two-dimensional points. The K-Means algorithm was used to classify the two-dimensional points to distinguish the SAW response from sinusoidal interference. Simulation results showed that the SAW response can be detected with a rate of more than 85% when the signal-to-noise ratio was greater than 4 dB, whereas the false detection rate of the sinusoidal interference signal was less than 8%. Finally, the proposed algorithm was used to detect the actual SAW response and sinusoidal interference signal. The experimental results showed that the proposed method can clearly distinguish the SAW response from the co-channel interference signal. Moreover, the proposed method can be used as the anti-interference technology to improve the stability of the SAW sensor.

中文翻译：

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基于K-Means聚类算法的表面声波传感器抗干扰技术

在无源无线表面声波（SAW）传感器的工作环境中，可以使用各种类型的干扰信号。在这些干扰中，同频道干扰难以抑制。为了解决这个问题，提出了一种声表面波传感器抗干扰技术，以提高声表面波传感器的可靠性。用小波去噪方法对SAW谐振器的响应进行去噪，可以保持SAW响应的包络特性。建立了声表面波响应信号的熵能模型，并从提出的熵能函数中提取了信号包络。采用波形包络和熵能曲线作为信号特征，形成二维点。使用K-Means算法对二维点进行分类，以将SAW响应与正弦波干扰区分开。仿真结果表明，当信噪比大于4 dB时，声表面波响应的检出率可达到85％以上，而正弦干扰信号的误检率小于8％。最后，该算法被用于检测实际的声表面波响应和正弦干扰信号。实验结果表明，所提出的方法可以从同信道干扰信号中清楚地区分出声表面波响应。此外，所提出的方法可以用作抗干扰技术以提高SAW传感器的稳定性。仿真结果表明，当信噪比大于4 dB时，声表面波响应的检出率可达到85％以上，而正弦干扰信号的误检率小于8％。最后，该算法被用于检测实际的声表面波响应和正弦干扰信号。实验结果表明，所提出的方法可以从同信道干扰信号中清楚地区分出声表面波响应。此外，所提出的方法可以用作抗干扰技术以提高SAW传感器的稳定性。仿真结果表明，当信噪比大于4 dB时，声表面波响应的检出率可达到85％以上，而正弦干扰信号的误检率小于8％。最后，该算法被用于检测实际的声表面波响应和正弦干扰信号。实验结果表明，所提出的方法可以从同信道干扰信号中清楚地区分出声表面波响应。此外，所提出的方法可以用作抗干扰技术以提高SAW传感器的稳定性。该算法被用来检测实际的声表面波响应和正弦干扰信号。实验结果表明，所提出的方法可以从同信道干扰信号中清楚地区分出声表面波响应。此外，所提出的方法可以用作抗干扰技术以提高SAW传感器的稳定性。该算法被用来检测实际的声表面波响应和正弦干扰信号。实验结果表明，所提出的方法可以从同信道干扰信号中清楚地区分出声表面波响应。此外，所提出的方法可以用作抗干扰技术以提高SAW传感器的稳定性。