Methods for determining the position of an object surface

Abstract

The invention relates to a method for determining the position of an object surface (16) with respect to a target position (15) in a measuring device (1) for semiconductor technology, wherein the position is determined on the basis of at least two measured values ​​(E1, E2, E3) representing the position, wherein the determination of the position includes a probability consideration (M, P1, P2, P3).

Description

[0001] The invention relates to a method for determining the position of an object surface, in particular of substrates for semiconductor lithography, such as photolithographic masks and wafers.

[0002] Photolithographic masks and wafers are used in lithography systems or for the fabrication of microstructured components, such as integrated circuits or LCDs (liquid crystal displays). In a lithography or microlithography process, an illumination unit illuminates a photolithographic mask, also known as a photomask or simply a mask. The light passing through or reflecting from the mask is projected by a projection lens onto a wafer coated with a photosensitive layer (photoresist) and positioned in the image plane of the projection lens. This transfers the structural elements of the mask onto the photosensitive coating of the wafer, thus creating the desired structure on the wafer.

[0003] The placement of structural elements on the surface of masks must be highly precise, such that permissible deviations from their specified positions or from a critical dimension (CD) of a structural element are in the nanometer range, preferably in the sub-nanometer range, to prevent defects on wafers during exposure with the corresponding mask. Manufacturing photomasks that meet these requirements is extremely complex, error-prone, and therefore expensive. Masks must therefore be repaired whenever possible if damaged or if they deviate from the desired specifications.

[0004] A key prerequisite for repairing defective masks is the detection and characterization of existing defects, particularly placement defects or errors. Detecting placement defects and / or deviations in critical dimensions is complex and challenging, as these dimensions must be determined with an accuracy in the single-digit nanometer range, preferably in the sub-nanometer range.

[0005] To investigate placement errors and / or critical dimensions, measuring devices such as mask inspection microscopes are used. A fundamental requirement for accurately determining placement effects and / or deviations in critical dimensions is the sharpest possible imaging of the mask's structures. This necessitates positioning the mask's surface as precisely as possible within the focal plane of the measuring device's imaging optics.

[0006] The focal plane is the point at which a flat object, such as the mask surface, must be positioned to be captured with maximum sharpness on a camera. The position of this focal plane in the z-direction perpendicular to the mask surface depends on the distance of the camera from the imaging optics of the mask inspection microscope and on the optical properties of the imaging optics. Its position is therefore determined by the configuration of the mask inspection microscope.

[0007] Despite the term "focal plane," the focal point of the imaging optics is not located in the focal plane. In ray optics terminology, the focal plane is rather a plane at the object distance that corresponds to a fixed image distance (determined by the properties and configuration of the imaging optics and the recording device). The maximum permissible deviation from the focal plane (target position) for capturing a sharp image of the mask surface is determined by the depth of field (usually a few hundred nm) of the imaging optics. It is therefore advantageous to position the object under investigation as precisely as possible within the region of the focal plane, to within a few nm.

[0008] The deviation of a mask surface's position from the focal plane is determined during autofocusing. This occurs after calibrating the mask inspection microscope, determining the thickness of the mask to be measured, and before the actual measurement of the mask, such as determining the precise location or geometry of a structure on the mask. Autofocusing ensures that the mask surface is positioned within the depth of field range described above, or ideally, within the focal plane of the imaging optics, for measuring the structures.

[0009] After calibrating the measuring device and measuring the mask thickness, the mask is positioned so that its surface lies within the focal plane. This positioning is sufficiently precise that, using autofocus systems, the remaining deviation of the mask surface from the focal plane can be determined, and the mask can then be positioned for a subsequent measurement.

[0010] The autofocus systems determine the deviation by evaluating an image of a measurement structure projected onto the mask surface. This image is captured by a recording device, such as a CCD camera, which is also used to capture the mask's structures. The measurement structure is projected onto the mask surface in such a way that, regardless of the mask surface's deviation from the focal plane, a portion of the measurement structure within a predetermined capture area of ​​the imaging optics is sharply imaged onto the recording device by the positioning optics.

[0011] The distance from the pixel-based image of the position of highest image sharpness in the projection of the measurement structure to a center line of the measurement structure, which is usually defined in the middle of the measurement structure and calibrated beforehand, corresponds, via a known factor, to the distance of the mask surface from the focal plane of the imaging optics in nm.

[0012] To improve measurement accuracy and avoid measurement errors due to interaction between the projected measurement structure and the structures formed on the mask, the measurement structure comprises at least two, and preferably three, gratings with different periodicities. The deviation of the position of highest image sharpness from the center line is determined independently for each grating. According to the prior art, the assumed deviation of the mask surface from the focal plane is determined from these deviations by simply averaging them. This has the disadvantage that even an erroneous determination of the deviation in one of the gratings can significantly distort the assumed deviation, which can subsequently lead to errors in determining the placement errors and / or the critical dimensions of the structures.

[0013] The object of the present invention is to provide a method which eliminates the disadvantages of the prior art described above.

[0014] This problem is solved by a method having the features of independent claim 1. The dependent claims relate to advantageous further developments and variants of the invention.

[0015] In a method according to the invention for determining the position of an object surface relative to a target position in a measuring device for semiconductor technology, the position is determined based on at least two measured values ​​representing the position. The method according to the invention is characterized in that the determination of the position includes a probability analysis. The target position can, for example, correspond to the z-position of a focal plane of a measuring device designed as a mask inspection microscope.

[0016] Probabilistic analysis results in the measurement values ​​used to determine the position being weighted, so that erroneous individual measurements receive less weight than correct measurements. In particular, probabilistic analysis can also be used to decide not to use individual values, i.e., to assign them a weight of zero.

[0017] This has the advantage that, after determining the position, the object surface can be positioned in its target position with higher accuracy and fewer measurements are required, and subsequent surface measurements, such as determining structure sizes, can achieve higher accuracy, and possible repetitions of the measurement due to large deviations from the target position can be avoided, thus achieving a higher throughput.

[0018] In an advantageous embodiment, for subcombinations of at least three measured values, a mean value of each subcombination can be determined as the combined result. As already mentioned, the measured values ​​can be pixel values, for example, the number of a pixel row or column on a CCD chip, for which the highest image sharpness is determined when imaging a grid.

[0019] In particular, probability functions can be defined for the at least three measured values, and a probability can be determined for each possible combination of the three measured values. Gaussian functions can advantageously be used as probability functions here.

[0020] The combined results are based on the assumption that it is initially unclear how many of, for example, three measurements (in the case of three grids used) are correct. Thus, for instance, only one measurement, two, or all three measurements could be correct.

[0021] This assumption leads to seven combination results for three grids, which correspond to three individual measurements (assumption: only one measurement is correct), three means of two each (assumption: two measurements are correct each) and one means of all three measurements (assumption: all three measurements are correct).

[0022] The individual combination results advantageously represent mean values ​​of the measured values ​​assumed to be correct, or the measured value used (if only one measured value is assumed to be correct).

[0023] To determine the probability of each combination result, the values ​​of the probability functions of the individual measured values ​​used for that combination result can be added together. In one variant of the method according to the invention, a decision regarding the combination result to be used, and thus the most probable position of the object surface, can be made based on this evaluation alone by selecting the combination result for which the addition yields the highest value. This result then represents the most probable position of the object surface in the z-direction.

[0024] The procedure can be improved, in particular, by incorporating a probability function for a metrological expectation into the probability analysis. This function is based on previously determined deviations and the associated experience regarding the distribution of values ​​of typical deviations. Based on this, a probability function for the position of the mask surface before autofocusing is determined. The corresponding probability function thus represents the probability of a specific deviation of the mask surface from its target position after the initial positioning of the mask and before its measurement. The probability function can, for example, be a Gaussian normal distribution and be used to determine the remaining deviation, i.e., the autofocus of the mask.

[0025] By using the value of the probability function for the metrological expectation for the respective combined result, a plausibility check can be performed in addition to the preceding evaluation of the probability functions of the individual measured values, which can be considered a consistency check. The closer the measured value is to the expected position, the higher the probability value assigned to it, which advantageously means that significantly deviating measurements are given less weight in determining the position.

[0026] To determine the overall probability for a combination result, the value of the probability function for the metrological expectation can be added to the already available result, in particular - possibly with a factor.

[0027] The combination result with the highest probability can then be selected as a measure for the position to be determined.

[0028] The position determined on the basis of probability considerations thus ensures that the subsequent positioning of the mask surface is always or almost always within the depth of field necessary for a successful measurement of the structure, thereby minimizing or even completely avoiding measurement errors, which can, for example, increase the throughput of a mask inspection microscope.

[0029] In another embodiment of the method, a standard deviation for the probability function can be determined via a sensitivity analysis when defining at least one probability function for the individual measured values. In this sensitivity analysis, for example, one of the three probability functions can be shifted within a range of + / - 100 pixels in the representation of the measurement structure. The maximum overall probability of all combination results is continuously determined and plotted across the pixels. In a second diagram, the position determined by the maximum overall probability—i.e., the combination result with the highest probability—is also plotted across pixels.The function of the specific location can exhibit at least two jumps due to the shift of one probability function across the entire range. A jump always occurs when the combination result with the maximum overall probability changes due to a switch from one combination result to a second combination result with a different composition of the measurements used for the combination result. For example, the combination result with the maximum overall probability may initially be formed from the mean of two measurements, one of which is the measurement whose probability function is shifted in the sensitivity analysis.In the further course of the sensitivity analysis, the shifting process can lead to a situation where the overall probability of the shifted measurement becomes greater than that of the mean. This means the measurement, rather than the mean of the two measurements, defines the deviation. This results in the jump described above. Depending on the distance between the measured values ​​and the width of the probability functions, more than two jumps can occur within the area considered in the sensitivity analysis. In this case, the standard deviation can be adjusted, thereby reducing the width of the probability function and changing the position of the jumps.

[0030] In particular, the standard deviation can be chosen such that the position determined in the sensitivity analysis based on probability considerations remains continuous within a predetermined range. This range could, for example, be + / - 50 pixels. Adjusting the standard deviation to determine the width of the probability function can be seen as a weighting of the two probability functions used to determine the position, where the influence of the metrological expectation has a greater weight in determining the position than the uncertainty of the measurement itself. In the limiting case, the standard deviation can be zero, meaning that the position can be determined solely based on the probability function of the metrological expectation.

[0031] This method can be used, in particular, for measuring substrates for semiconductor lithography. This could include, for example, the previously described measurement, or registration, of a mask for a projection exposure system. The method can also be used for positioning wafers prior to measurement or for other surfaces that have high requirements for precise positioning in their target orientation.

[0032] Exemplary embodiments and variants of the invention are explained in more detail below with reference to the drawing. The drawing shows Fig. 1 a schematic representation of a prior art mask inspection microscope with which the method according to the invention can be carried out, Fig. 2 a schematic representation of an autofocus system of a mask inspection microscope, Fig. 3 a diagram to illustrate the determination of the location, and Fig. 4a,b each a diagram to explain the determination of the standard deviation for a probability function of individual measured values.

[0033] Fig. Figure 1 shows a schematic representation of a measuring device known from the prior art, designed as a mask inspection microscope 1, for measuring an object designed as a photomask or mask 7 for semiconductor lithography. The mask inspection microscope 1 comprises two light sources 3, 4, wherein a first light source 3 is configured for measuring the mask 7 in reflection and a second light source 4 for measuring the mask 7 in transmission. The mask 7 is arranged on a stage 6, which can position the mask 7 laterally (xy-direction) and vertically (z-direction) in the sub-nanometer range. The positioning accuracy can be in the range of less than 500 pm, particularly less than 250 pm.

[0034] In a transmission measurement, the measuring light 13 from the illumination unit 14, which comprises the light source 4 and an illumination optic designed as a condenser 5, passes through the condenser 5, which generates a desired light distribution on the mask 7. The measuring light 13 then passes through the mask 7, a magnifying imaging optic 8, and a tube 10, reaching a recording device 2, which in the example shown is designed as a CCD camera. The semi-transparent mirror 9, arranged between the imaging optic 8 and the tube 10, is used for the measurement in reflection and has no influence on the measurement in transmission.

[0035] In a measurement by reflection, the measuring light 12 emitted by the light source 3 is reflected by the semi-transparent mirror 9 and then passes through the imaging optics 8, illuminating the mask surface 16. The illuminated mask surface 16 is then magnified and projected onto the recording device 2 by the imaging optics 8, just as in the case of a measurement by transmission.

[0036] The recording device 2, the object stage 6, the imaging optics 8 and the light sources 3, 4 are connected to a control unit 11, which controls or regulates the interaction of the individual components 2, 3, 4, 6, 8 and is also designed to process the captured images.

[0037] Further shown in the Fig. 1 is the so-called focal plane 15. The focal plane 15 is the location where a flat object, such as the mask surface 16, must be positioned to be imaged with maximum sharpness on the recording device 2. The position of this focal plane 15 in the z-direction depends on the distance of the recording device 2 from the imaging optics 8 and the optical properties of the imaging optics 8. Its position is therefore determined by the configuration of the mask inspection microscope 1. Despite the name "focal plane," the focal point of the imaging optics 8 is not located in the focal plane. In the terminology of ray optics, the focal plane is rather a plane at the object distance that corresponds to a fixed image distance (determined by the properties and configuration of the imaging optics 6 and the recording device 2).

[0038] In the Fig. In the embodiment shown in Figure 1, the mask surface 16 is indeed roughly located within the focal plane 15; however, the deviation in the z-direction is so large that the image of the mask surface 16 captured by the recording device 2 is not sufficiently sharp to allow subsequent image analysis for determining the edges of the structures. It is therefore necessary to optimize the position of the mask surface 16 so that it lies as close as possible to the focal plane 15 in the z-direction, i.e., to perform so-called autofocusing.

[0039] For this autofocus (see Fig. 2), i.e., the positioning of the mask surface 16 in the focal plane 15, an autofocus system 23 with a measuring structure 17 and an additional optic 18 is swung into the beam path 19 of the measuring light 12 of the reflection measurement between the light source 3 and the semi-transparent mirror 9. The additional optic 18 ensures that the central area of ​​the measuring structure 17 is sharply imaged into the focal plane 15 by the imaging device 8. In this case, the beam direction relative to the imaging device 8 is reversed compared to the measuring operation of the mask inspection microscope 1; thus, an image of the measuring structure 17 is generated where the mask surface 16 is located in normal operation. The image plane of the measuring structure 17 corresponds to the focal plane 15 of the image of the mask 7 onto the recording device 2.

[0040] The measurement structure 17 is tilted relative to the beam path 19. Consequently, the image of the measurement structure is also tilted within the focal plane 15. The mask surface 16 serves as the projection surface for the measurement structure 17. If the central area of ​​the measurement structure 17 is also sharply imaged centrally on the mask surface 16, the mask surface 16 is located exactly in the focal plane 15, i.e., in an optimal z-position for imaging the mask surface 16. Lateral deviations of the sharply imaged portions of the measurement structure 17 on the mask surface 16 are a measure of the deviation of the z-position of the mask surface 16 from the focal plane. The lateral displacement of the sharply imaged portions relative to the central area of ​​the mask surface 16 can thus be directly converted into a deviation of the current z-position of the mask surface 16 from the focal plane 15.

[0041] Fig. Figure 2 shows a schematic representation of an autofocus system 23 to describe the autofocus procedure.

[0042] As already mentioned, the autofocus ensures that the mask surface 16 is positioned in the optimal z-position before measuring the mask 7.

[0043] As mentioned above, the mask inspection microscope 1 is calibrated before autofocusing, and the mask surface 16 is measured with respect to the coordinate system of the mask inspection microscope 1. This ensures that the mask surface 16, used as the projection surface for the measurement structure 17, is located within the area of ​​the obliquely oriented image of the measurement structure 17 before autofocusing.

[0044] The tilting of the measurement structure 17 ensures that a portion of the measurement structure 17 is always sharply imaged within a predetermined capture area of ​​approximately ±1 µm around the focal plane 15. As mentioned previously, the lateral displacement of the sharply imaged portion relative to the center line of the measurement structure 17 is a measure of the deviation of the mask surface 16 from the focal plane 15. In the example shown, the measurement structure 17 comprises several gratings 20.1, 20.2, 20.3 with different periodicities. The periodicities of the three gratings 20.1, 20.2, 20.3, relative to the projection onto the mask surface 16, are in the micrometer range. The different periodicities serve to avoid interference with similar structures on the mask 7.

[0045] Additionally, during the recording of the measurement structure 17 projected onto the mask surface 16, the mask 7 is moved laterally, i.e. in the direction of the periodicities in the x-direction, so that the structures of the mask 7 in the image are blurred in contrast to the stationary projection of the measurement structure 17, which at least greatly reduces or minimizes measurement errors.

[0046] To determine the deviation of the z-position of the mask surface 16 from the focal plane 15, the values ​​for gratings 20.1, 20.2, 20.3 are taken from the data in the Fig. The location of maximum image sharpness for the individual gratings 20.1, 20.2, 20.3 is determined by the contrast gradients 22.1, 22.2, 22.3 shown to the right of the image of the measurement structure 17. This sub-area, shown sharply in the image of the measurement structure 17, is in the Fig. 2. Each grid is marked with an arrow for clarity. The measured values, representing the positions of the maximum image sharpness of the three grids 20.1, 20.2, 20.3, typically differ from each other due to measurement inaccuracies.

[0047] According to the invention, the determination of the deviation of the z-position of the mask 7 from the determined lateral positions of the maximum image intensities of the three grids 20.1, 20.2, 20.3 comprises a probability analysis, which is based on the Fig. 3 is described in detail. The positional deviation of the location of the maximum image sharpness thus determined from the center line 21 of the measurement structure 17, which is determined in pixels of the CCD camera, is, as mentioned, a measure of the deviation in nm along the z-direction of the mask inspection microscope 1, whereby the number of pixels is converted into nm via a predetermined factor.

[0048] Fig. Figure 3 shows a diagram illustrating the determination of the position of the mask surface 16 in relation to its target position determined by the focal plane 15, based on a probability analysis of the determined measured values ​​( Fig. 2) and the mean values ​​determined from them. The horizontal axis represents the width of the CCD camera image in pixels, and the vertical axis represents the probability. The values ​​in the Fig. The curve M, shown in bold and solid, describes the probability function of the metrological expectation in the form of a Gaussian normal distribution. This is based on a large number of measurements from a mask inspection microscope 1 and represents the expectation that the location of an area with maximum image sharpness is normally within a range of + / - 300 pixels around the center line of the measurement structure 17, which is located at 700 pixels in the diagram. Fig. Figure 3 is represented as a bold dashed line. The probability function, in particular, prevents the remaining third, likely correct measurement from being overruled if two erroneous measurements are far outside the metrological expectations. The standard deviation of the probability function is chosen such that the probability is greater than zero across the entire width of the figure.

[0049] The three other curves P1, P2, and P3 describe the probability functions of the three specific measured values, where the value of each measured value lies at the respective maximum of the corresponding probability function. These probability functions are intended to account for the uncertainty of the measured values ​​due to measurement inaccuracies. The standard deviations of the probability functions for the specific measured values ​​are identical in the example shown and are based on a function defined in the Fig. 4a and Fig. The sensitivity analysis described in more detail in section 4b was used to determine the values. From the three measured values, combination results E1 to E7 are first generated and evaluated based on probability considerations. The most probable combination result is then selected as the basis for determining the deviation of the mask surface 16 from the target position. In the example shown, E1 to E7 are pixel values ​​on the abscissa of the graph shown in the diagram. Fig. 3 diagrams shown.

[0050] In a first step, seven possible combination results E1 to E7 are determined from the three specified measurements, namely - first, the three determined measured values ​​themselves as individual values ​​E1, E2, E3 (associated assumption: only one of the three determined values ​​is correct within the limits of measurement accuracy) - the mean values ​​from any two of the three determined measurements as E4, E5, E6 (associated assumption: only two of the determined values ​​are correct) - and the mean of all three determined measurements as E7 (associated assumption: all determined values ​​are correct).

[0051] These combination results E1 to E7, represented in pixels, are evaluated for their probability W using the diagram or mathematically as follows. GE From that perspective, it's the right result. WGE1=0.5*M(E1)+0.5*P1(E1) WGE2=0.5*M(E2)+0.5*P2(E2) WGE3=0.5*M(E3)+0.5*P3(E3) WGE4=0.5*M(E4)+0.5*Root((P1(E4))2+(P2(E4))2) WGE5=0.5*M(E5)+0.5*Root((P1(E5))2+(P3(E5))2) WGE6=0.5*M(E6)+0.5*Root((P2(E6))2+(P3(E6))2) WGE7=0.5*M(E7)+0.5*Root((P1(E7))2+(P2(E7))2+(P3(E7))2) where E1 = specific measured value 1 E2 = specific measured value 2 E3 = specific measured value 3 E4 = Average of specific measured values ​​1 and 2 E5 = Average of specific measurements 1 and 3 E6 = Average of specific measurements 2 and 3 E7 = Average of specific measurements 1, 2, 3 M(E) = the probability function M of the metrological expectation P1(E) = the probability function P1 of the specific measured value 1 P2(E) = the probability function P2 of the specific measured value 2 P3(E) = the probability function P3 of the specific measured value 3.

[0052] As an example, the overall probability W will first be calculated purely qualitatively. GE7 for the in Fig. The case shown in the diagram (dashed line) can be estimated. As shown in the diagram, the mean value E7 – assuming all three measurements are correct – is approximately 900 pixels. However, in this case, all three probability functions P1, P2, and P3 have values ​​close to zero, so the square root term in the formula above for W GE7This also contributes only close to zero to the overall probability. The contribution of the function M, representing the metrological expectation at 900 pixels, is approximately 0.65, so the resulting overall probability should be in the range of approximately 0.4.

[0053] The situation is different if we assume that P2 and P3 represent correct measurements. A mean value of approximately 690 pixels is assumed for E6 (not shown). Here, the square root term of W is... GE6 a value in the range of 1.4. M(E6) is in the range of 1, so the overall probability should be in the range of 1.2 and the value E6 is therefore far more likely to be correct than the value E7.

[0054] The calculation is not normalized, so values ​​greater than 1 for the total probabilities W GEx 1 can certainly occur.

[0055] Fig. 4a and Fig. Figure 4b shows a diagram illustrating the determination of the optimal standard deviation of the probability functions of the specified measured values ​​using a sensitivity analysis. The criterion for choosing the standard deviation is that the function of the position determined by the probability analysis remains continuous over the widest possible range as a function of an offset of the probability functions around the x-axis (i.e., when the respective probability function is shifted by a certain number of pixels or nanometers).

[0056] The Fig. Figure 4a shows the course of the maximum overall probability (vertical axis) for the most probable combination outcome during this sensitivity analysis. The probability function P2 of the Fig. 3 is moved by + / - 100 pixels (horizontal axis) during the sensitivity analysis. The total probability W G is in the in the Fig. The embodiment shown in 4a is not standardized, so values ​​greater than 1 are also possible.

[0057] The Fig. Figure 4b shows the value (vertical axis) of the most probable combination result for the deviation during the sensitivity analysis. The horizontal axis, in turn, shows the movement of the probability function P2 by + / - 100 pixels. A jump in the curve indicates a change in the combination result E1-E7 as the most probable outcome. The standard deviation is advantageously chosen such that, within the relevant range of the autofocus measurement, which is typically + / - 50 pixels, no jump occurs in the value of the most probable combination result, i.e., the position used. This criterion is defined in the Fig. The case shown in 4b is given, in which the continuous range 24 of the deviation is approximately + / -75 pixels. Reference symbol list 1 mask inspection microscope 2 Recording device, CCD camera 3 Light source reflection 4 Light source transmitted light 5 condenser 6 object table 7 Mask 8 Imaging Optics 9 Semi-transparent mirror 10 tubes 11 Control 12 Measuring light reflection 13 Measuring light transmitted light 14 lighting units 15 Focus level 16 mask surface 17 Measurement structure 18 Optics Autofocus system 19 Beam path Reflection 20.1-20.3 Grid 21 Centerline Measurement Structure 22.1, 22.2, 22.3 Contrast gradient 23 Autofocus system 24 Continuous Area Location P1 Probability function Grid 1 P2 Probability Function Grid 2 P3 Probability Function Grid 3 M probability function metrological expectations E1 Result Combination 1 E2 Result Combination 2 E3 Result Combination 3 E4 Result combination 4 E5 Result combination 5 E6 Result combination 6 E7 Result combination 7

Claims

[1] Method for determining a position of an object surface (16) with respect to a desired position (15) in a measuring device (1) for semiconductor technology, wherein the position is determined on the basis of at least two measured values ​​(E1, E2, E3) representing the position, characterized by that the determination of the position includes a probability consideration (M, P1, P2, P3). [2] Method according to claim 1, characterized by that the target position is the position of a focal plane (15) of the measuring device (1). [3] Method according to one of claims 1 or 2, characterized by that for sub-combinations of at least three measured values ​​(E1, E2, E3) a mean value of the respective sub-combination is determined as the combination result (E1-E7). [4] Method according to claim 3, characterized by that probability functions (P1,P2,P3) are defined for at least three measured values ​​(E1,E2,E3) and each has a probability (W GEx) for possible combination results of the three measured values. [5] Method according to claim 4, characterized by that for the determination of the probability (W GEx ) an addition of the values ​​of the probability functions (P1,P2,P3) for the respective combination result (E1-E7) is carried out. [6] Method according to one of the preceding claims, characterized by that a probability function (M) for a metrological expectation is included in the probability consideration. [7] Method according to claim 6, characterized by that the value of the probability function (M) is used for the metrological expectation for the respective combination result (E1-E7). [8] Method according to one of claims 5 to 7, characterized by that for the determination of the probability (W Gex) the value of the probability function (M) for the metrological expectation for the respective determined combination result (E1-E7) is added. [9] Method according to one of claims 3 to 8, characterized by that the combination result (E1-E7) with the highest probability (W Gex ) is selected as the measure for the position to be determined (Ex). [10] Method according to one of claims 4 to 9, characterized by that when defining at least one probability function (P1,P2,P3), a standard deviation for the probability function (P1,P2,P3) is determined via a sensitivity analysis. [11] Method according to claim 10, characterized by that the standard deviation is chosen in such a way that the value of the most probable position determined in the sensitivity analysis on the basis of the probability consideration (M,P1,P2,P3) is continuous within a predetermined range.

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