Fringe 2005 2006
DOI: 10.1007/3-540-29303-5_3
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Interpreting interferometric height measurements using the instrument transfer function

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Cited by 60 publications
(62 citation statements)
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“…There are different approaches to characterize the lateral resolution of microscopic 3D-measuring systems. 9,10 However, none of these corresponds to the measuring results we obtained from a UV illuminated Linnik type SWLI.…”
Section: Introductionmentioning
confidence: 73%
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“…There are different approaches to characterize the lateral resolution of microscopic 3D-measuring systems. 9,10 However, none of these corresponds to the measuring results we obtained from a UV illuminated Linnik type SWLI.…”
Section: Introductionmentioning
confidence: 73%
“…Illuminating with 600 nm the interferometer should not be able to resolve the 1.2 μm nor the 0.6 μm pitch length. According to the ITF as defined by de Groot et al 9 the measured normalized modulation depth should be clearly below one at a pitch length of 1.2 μm and close to zero at 0.6 μm pitch. Due to non-linear transfer characteristics of the interferometer the measurement results differ from the theoretical considerations.…”
Section: Experimentamentioning
confidence: 90%
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“…The limited numerical aperture of our objective (NA=0.3) prevents the light scattered at an angle larger than arcsin(NA) to be observed. Reducing the scattering angle cone corresponds to the operation of filtering out from the complex scattered field the spatial frequencies above NA/λ [21,22]. In the fitting routine, when computing f, we take into account this effect by filtering out frequency components larger than the cutoff value.…”
Section: Methodsmentioning
confidence: 99%
“…The starting point for these simulations is a physical model F(x x i ;p p k )~y of the measurement process, wherex x i represents the measurement condition for the ith data point andp p k contains the model parameters (e.g., critical dimension (CD), height, side wall angle (SWA), etc.). All known influences that contribute to the formation of the measured quantity have to be taken into account; this includes the light source, instrument transfer function, 12 aberrations and sensor features. Having a simulation model of the measurement system makes it possible to create a database filled with templates that represent different measurement configurations (x x ) or variations in the structure parameters (p p).…”
Section: Solving the Inverse Problem By Model-based Feature Reconstrumentioning
confidence: 99%