基于ICA盲源分离的声表面波无线传感器信号抗干扰方法

针对声表面波传感器无线信号易受环境中同频信号干扰的问题,设计了基于独立分量分析(ICA)盲源分离的抗干扰算法。该算法对传感器和同频干扰的混合信号进行分离,然后基于分离信号波形的衰减和等幅特征对信号进行判别。MATLAB仿真结果表明,算法能够有效分离混合信号并且保留了源信号的时域波形特征和频域信息。将抗干扰算法在基于数字信号处理器的信号采集和处理平台上实现并进行分离实验,设置不同的传感器信号和干扰信号强度并记录分离和判别结果,实验结果表明,在源信号的信号强度较为接近(信扰比在0.8~1.4范围内)且噪声影响可忽略的情况下,可达到95%以上的传感器信号准确判别率,有效地抑制了同频干扰。

Anti-interference method for signal of wireless surface acoustic wave sensor based on ICA blind source separation

Aiming at the problem that the wireless signal of surface acoustic wave sensor is easily interfered by the same frequency signal in the environment, an anti-interference algorithm based on ICA blind source separation theory is designed. This algorithm separates the the mixed signal of the sensor the same frequency interference, and then distinguishes the signal based on the attenuation and constant amplitude characteristics of the separated signal waveform. MATLAB simulation results show that the algorithm can effectively separate mixed signals and retain the time-domain waveform characteristics and frequency-domain information of the source signal. The anti-interference algorithm is implemented on a DSP-based signal acquisition and processing platform on which signal separation experiments are carried out. Different sensor signals and interference signal amplitudes are set and the separation and discrimination results are recorded. The experimental results show that when the signal strength of the source signal is relatively close(the signal-to-interference ratio is in the range of 0.8~1.4) and the noise effect is negligible, an accurate discrimination rate of more than 95% of the sensor signal can be achieved, effectively suppressing the same frequency interference.