The dust scattering data measured by photovoltaic panels are affected by various noise and interference factors, resulting in large errors in the measured data. For the sake of accurate detection results, a signal denoising method is proposed, combining Kalman filtering and digital phase-locked amplification technology to denoise the dust scattering signal of photovoltaic panels mixed with noise. The denoising performance of the joint algorithm is verified by simulation experiments and denoises the measured dust scattering signal of photovoltaic panels, and calculates the signal-to-noise ratio, root-mean-square error and smoothness. The results show that the signal-to-noise ratio of Kalman filter combined with digital lock-in amplifier denoising algorithm is 36% higher than that of single digital lock-in amplifier denoising algorithm, which can effectively reduce the noise interference in photoelectric detection system and improve the accuracy and stability of photoelectric detection system.