Data-Driven Post-Filtering of Acoustics Noise in Atomic Force Microscope Imaging

This paper presents a data-driven dynamics-based filtering approach to eliminate acoustic noise-caused distortion in images of atomic force microscope (AFM). AFM operations are sensitive to external noise as disturbances including acoustic noise as disturbances to the probe-sample interaction directly results in distortions in AFM imaging. Although conventional passive noise cancellation has been employed, limitation exists and residual noise still persists. Advanced online control techniques face difficulty in capturing the complex noise dynamic and limited system bandwidth imposed by the robustness requirement. Therefore, In this work, we propose a finite-impulse-response (FIR) based post-filtering approach to remove the noise-caused distortion in AFM images. Experimental implementation is presented and discussed to illustrate the proposed technique.