Abstract: Multilayered product structures are formed on substrates by a combination of patterning steps, physical processing steps and chemical processing steps. An inspection apparatus illuminates a plurality of target structures and captures pupil images representing the angular distribution of radiation scattered by each target structure. The target structures have the same design but are formed at different locations on a substrate and/or on different substrates. Based on a comparison of the images the inspection apparatus infers the presence of process-induced stack variations between the different locations. In one application, the inspection apparatus separately measures overlay performance of the manufacturing process based on dark-field images, combined with previously determined calibration information. The calibration is adjusted for each target, depending on the stack variations inferred from the pupil images.

Abstract: Disclosed is a method and associated apparatus of determining a performance parameter (e.g., overlay) of a target on a substrate, and an associated metrology apparatus. The method comprises estimating a set of narrowband measurement values from a set of wideband measurement values relating to the target and determining the performance parameter from said set of narrowband measurement values. The wideband measurement values relate to measurements of the target performed using wideband measurement radiation and may correspond to different central wavelengths. The narrowband measurement values may comprise an estimate of the measurement values which would be obtained from measurement of the target using narrowband measurement radiation having a bandwidth narrower than said wideband measurement radiation.

Abstract: Overlay error of a lithographic process is measured using a plurality of target structures, each target structure having a known overlay bias. A detection system captures a plurality of images (740) representing selected portions of radiation diffracted by the target structures under a plurality of different capture conditions (?1, ?2). Pixel values of the captured images are combined (748) to obtain one or more synthesized images (750). A plurality of synthesized diffraction signals are extracted (744) from the synthesized image or images, and used to calculate a measurement of overlay. The computational burden is reduced compared with extracting diffraction signals from the captured images individually. The captured images may be dark-field images or pupil images, obtained using a scatterometer.

Abstract: An overlay metrology target (600, 900, 1000) contains a plurality of overlay gratings (932-935) formed by lithography. First diffraction signals (740(1)) are obtained from the target, and first asymmetry values (As) for the target structures are derived. Second diffraction signals (740(2)) are obtained from the target, and second asymmetry values (As?) are derived. The first and second diffraction signals are obtained using different capture conditions and/or different designs of target structures and/or bias values. The first asymmetry signals and the second asymmetry signals are used to solve equations and obtain a measurement of overlay error. The calculation of overlay error makes no assumption whether asymmetry in a given target structure results from overlay in the first direction, in a second direction or in both directions. With a suitable bias scheme the method allows overlay and other asymmetry-related properties to be measured accurately, even in the presence of two-dimensional overlay structure.

Abstract: A property of a target structure is measured based on intensity of an image of the target. The method includes (a) obtaining an image of the target structure; (b) defining a plurality of candidate regions of interest, each candidate region of interest comprising a plurality of pixels in the image; (c) defining an optimization metric value for the candidate regions of interest based at least partly on signal values of pixels within the region of interest; (d) defining a target signal function which defines a contribution of each pixel in the image to a target signal value. The contribution of each pixel depends on (i) which candidate regions of interest contain that pixel and (ii) optimization metric values of those candidate regions of interest.

Abstract: A method and apparatus are described for providing an accurate and robust measurement of a lithographic characteristic or metrology parameter. The method includes providing a range or a plurality of values for each of a plurality of metrology parameters of a metrology target, providing a constraint for each of the plurality of metrology parameters, and calculating, by a processor to optimize/modify these parameters within the range of the plurality of values, resulting in a plurality of metrology target designs having metrology parameters meeting the constraints.

Abstract: A property of a target structure is measured based on intensity of an image of the target. The method includes (a) obtaining an image of the target structure; (b) defining a plurality of candidate regions of interest, each candidate region of interest comprising a plurality of pixels in the image; (c) defining an optimization metric value for the candidate regions of interest based at least partly on signal values of pixels within the region of interest; (d) defining a target signal function which defines a contribution of each pixel in the image to a target signal value. The contribution of each pixel depends on (i) which candidate regions of interest contain that pixel and (ii) optimization metric values of those candidate regions of interest.

Abstract: A property of a target structure is measured based on intensity of an image of the target. The method includes (a) obtaining an image of the target structure; (b) defining (1204) a plurality of candidate regions of interest, each candidate region of interest comprising a plurality of pixels in the image; (c) defining (1208, 1216) an optimization metric value for the candidate regions of interest based at least partly on signal values of pixels within the region of interest; (d) defining (1208, 1216) a target signal function which defines a contribution of each pixel in the image to a target signal value. The contribution of each pixel depends on (i) which candidate regions of interest contain that pixel and (ii) optimization metric values of those candidate regions of interest.

Abstract: A property of a target structure is measured based on intensity of an image of the target. The method includes (a) obtaining an image of the target structure; (b) defining (1204) a plurality of candidate regions of interest, each candidate region of interest comprising a plurality of pixels in the image; (c) defining (1208, 1216) an optimization metric value for the candidate regions of interest based at least partly on signal values of pixels within the region of interest; (d) defining (1208, 1216) a target signal function which defines a contribution of each pixel in the image to a target signal value. The contribution of each pixel depends on (i) which candidate regions of interest contain that pixel and (ii) optimization metric values of those candidate regions of interest.