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.