Abstract: Building of a model profile for a target is disclosed. An embodiment of the method includes importing an image of a known object and superimposing, on this image, either by hand or automatically, an estimated profile. The estimated profile is defined mathematically and adjusted segment by segment in order to match the image such that the adjusted estimated profile may be stored alongside a diffraction spectrum associated with the image. Alternatively or additionally, a user may trace (or free-draw) the profile of a known image and subsequently map a shape-definer of a mathematical function such as a polynomial equation, a spline or a vector onto the estimated profile in order to obtain a profile and one or more variables of that profile that may be used to reconstruct the profile of an unknown object from its diffraction pattern.

Abstract: A method is provided for determining an actual profile of an object printed on a substrate. The method can include receiving an actual spectrum signal associated with the object, selecting a first model profile, and generating a first model spectrum signal associated with the first model profile. The method can further include comparing the first model spectrum signal with the actual spectrum signal. If the first model spectrum signal and the actual spectrum signal do not match a desired tolerance, the aforementioned selecting, generating, and comparing can be repeated with a second model profile. The second model profile can be selected based on the first model spectrum signal having undergone an optimization process based on a number of variable parameters of the first model profile, where the number of variable parameters is reduced by approximating the first model profile to a single shape with a reduced number of variable parameters.

Abstract: Measurement of a profile of a scatterometry object on top of one or more product layers on a substrate is disclosed. To prevent an unknown parameters of one or more product layers having an effect on the measurement of the object profile, the thickness of the one or more product layers is measured prior to measuring the profile of the scatterometry object on the layer(s). In an embodiment, each of a plurality of product layers is measured as it is exposed so that only the degree of freedom of the most recently exposed product layer is unknown at each measurement step. When each of a plurality of product layers has been measured, and a scatterometry object is placed at the top of the layers, only the degrees of freedom of that scatterometry object should be unknown and only the profile of the object should need to be measured.

Abstract: A method is provided for determining an actual profile of an object printed on a substrate. The method can include receiving an actual spectrum signal associated with the object, selecting a first model profile, and generating a first model spectrum signal associated with the first model profile. The method can further include comparing the first model spectrum signal with the actual spectrum signal. If the first model spectrum signal and the actual spectrum signal do not match a desired tolerance, the aforementioned selecting, generating, and comparing can be repeated with a second model profile. The second model profile can be selected based on the first model spectrum signal having undergone an optimization process based on a number of variable parameters of the first model profile, where the number of variable parameters is reduced by approximating the first model profile to a single shape with a reduced number of variable parameters.

Abstract: In target shape reconstruction, in order to determine efficiently and quickly the profile of complex targets on a substrate, the various degrees of freedom or variable parameters of the various shapes of which a single profile is made up can be reduced by linking together the variable parameters using simple formulae or by approximating the shape of the overall profile such that it takes in to account the various shapes making up that profile. Fewer parameters gives rise to fewer iterations of calculations on those parameters, which increases the speed of profile reconstruction.

Abstract: Building of a model profile for a target is disclosed. An embodiment of the method includes importing an image of a known object and superimposing, on this image, either by hand or automatically, an estimated profile. The estimated profile is defined mathematically and adjusted segment by segment in order to match the image such that the adjusted estimated profile may be stored alongside a diffraction spectrum associated with the image. Alternatively or additionally, a user may trace (or free-draw) the profile of a known image and subsequently map a shape-definer of a mathematical function such as a polynomial equation, a spline or a vector onto the estimated profile in order to obtain a profile and one or more variables of that profile that may be used to reconstruct the profile of an unknown object from its diffraction pattern.

Abstract: Measurement of a profile of a scatterometry object on top of one or more product layers on a substrate is disclosed. To prevent an unknown parameters of one or more product layers having an effect on the measurement of the object profile, the thickness of the one or more product layers is measured prior to measuring the profile of the scatterometry object on the layer(s). In an embodiment, each of a plurality of product layers is measured as it is exposed so that only the degree of freedom of the most recently exposed product layer is unknown at each measurement step. When each of a plurality of product layers has been measured, and a scatterometry object is placed at the top of the layers, only the degrees of freedom of that scatterometry object should be unknown and only the profile of the object should need to be measured.

Abstract: In target shape reconstruction, in order to determine efficiently and quickly the profile of complex targets on a substrate, the various degrees of freedom or variable parameters of the various shapes of which a single profile is made up can be reduced by linking together the variable parameters using simple formulae or by approximating the shape of the overall profile such that it takes in to account the various shapes making up that profile. Fewer parameters gives rise to fewer iterations of calculations on those parameters, which increases the speed of profile reconstruction.