Atomic force microscopy (AFM) plays an important role in nanoscale imaging application. AFM works by oscillating a microcantilever on the surface of the sample being scanned. In this process, estimating the amplitude of the cantilever deflection signal plays an important role in characterizing the topography of the surface. Existing approaches on this topic either have slow dynamic response e.g., lock-in-amplifier or high computational complexity e.g., Kalman filter. In this context, gradient estimator can be considered as a trade-off between fast dynamic response and high computational complexity. However, no constructive tuning rule is available in the literature for gradient estimator. In this paper, we consider small-signal modeling and tuning of gradient estimator. The proposed approach greatly simplifies the tuning procedure. Numerical simulation and experimental results are provided to demonstrate the suitability of the proposed tuning procedure.
Keywords: amplitude estimation; atomic force microscopy; gradient estimator; sensor signal processing; small-signal modeling.