High Precision Focus Error Detection Technology Based on the Astigmatic Method

To improve the detection accuracy of astigmatism-based defocus detection systems, it is crucial to enhance the stability of the four-quadrant detector output signal. This study proposes a joint filtering method that integrates Kalman filtering with wavelet threshold denoising to suppress signal disturbances. Kalman filtering is first employed to mitigate low-frequency fluctuations, after which wavelet threshold denoising is applied to reduce the high-frequency residual errors introduced by the Kalman filter. This combination achieves effective suppression of both low- and high-frequency interferences. Experimental results show that the joint filtering method reduces the root-mean-square error and peak-to-peak error of the acquired signal by more than 70%, significantly improving signal stability. The minimum resolvable displacement is improved from 88 nm to 38 nm, corresponding to a 56.8% increase in detection accuracy. Compared with conventional methods, the proposed digital filtering strategy not only simplifies the optical system but also enhances the robustness and accuracy of signal acquisition.