JPH0663740B2 - Alignment mark position detection method - Google Patents

Description

DETAILED DESCRIPTION OF THE INVENTION [Industrial field of application] The present invention relates to a mask or an alignment mark on a wafer in a proximity aligner or stepper used in an exposure apparatus such as an X-ray exposure apparatus for printing a circuit pattern on a wafer. The present invention relates to a method for detecting the center position of the alignment mark from the detected waveform with high accuracy.

[Conventional technology]

Generally, as a method of obtaining the center position of the alignment mark from the detected waveform with high accuracy, two types of methods, that is, a diffractive element method using a Fresnel zone or the like and a pattern measuring method are used. Among them, the diffraction grating method has a drawback that the detection accuracy is greatly influenced by the variation of the gap between the mask and the wafer, and the alignment mark having a step cannot be detected accurately. On the other hand, the pattern measurement method has a drawback that the accuracy depends on the shape of the pattern of the alignment mark to be detected, and thus the detection accuracy deteriorates due to the deterioration of the pattern shape of the alignment mark. Here, an example in which the diffraction grating method depends on the symmetry of the alignment mark is
I-E-E Transaction on Electron Devices (IEEE TR
ANSACTION ON ELECTRON DEVICES) VOL.
ED-26, No. 4, added "Automatic Alignment System for Opt.
The paper entitled "ical Printing" was proposed by Gijs Bouwhuis and others. Also,
An example in which the pattern measuring method depends on the symmetry of the alignment mark is disclosed in JP-A-62-54918 and JP-A-61-199633.

The pattern measurement method is further roughly classified into a contratos method and an edge detection method.

Among them, the conventional example of the contrast method is disclosed in Japanese Patent Laid-Open No. 61-236117.
It is disclosed in the publication. In this Japanese Patent Laid-Open No. 61-236117, a symmetrical pattern matching process represented by the following equation is performed.

Or However, D (n) is a differential value, M is a comparison range, and n is a position.

The above expression is an application of pattern matching processing in ordinary image processing, and this Japanese Laid-Open Patent Publication No. 61-236117 uses the fact that the pattern of the alignment mark is line symmetric, I am incorporating it. That is, in order to find the center line of a line-symmetric figure, the figure is folded in half and the operation for finding the center line is performed. The place of folding in half is of course an edge, but this uses an edge processed by the edge extraction method by differentiation which is a general image processing method.

As described above, Japanese Patent Laid-Open No. 61-236117 can take in the symmetry of the figure well and obtain the center line by a relatively simple arithmetic expression. By using this symmetric pattern matching process for detecting alignment marks on a mask or a wafer with a proximity aligner or stepper, the relative positional relationship can be obtained from the center line of each alignment mark.

[Problems to be solved by the invention]

However, the method using the symmetrical pattern matching process described in Japanese Patent Laid-Open No. 61-236117 has the following drawbacks.

That is, this method presupposes that the figure is symmetrical. Ideally, the alignment mark (chrome formation mark) on the mask and the alignment mark (resist formation mark or process formation mark) on the wafer are line symmetric, but in reality, the symmetry is broken by various factors. .

For example, in the case of a resist formation mark, the symmetry of the alignment mark is broken due to the irradiation angle of X-rays when exposing the alignment mark, the developing speed of the resist, etc. (see FIG. 2). Further, in the case of the process formation mark, the symmetry of the alignment mark is likely to be broken, and the alignment mark can be easily deformed due to thermal deformation (chemical deformation, deformation due to force) of the process or a thin film applied on the alignment mark. The symmetry of is broken (see Fig. 3).

As is clear from the above description, in an actual alignment mark on EUH, it is extremely difficult to guarantee its symmetry in all layers (layers). Therefore,
The use of data of alignment marks that are not symmetric with respect to the calculation assuming symmetry causes a contradiction, and the calculation result includes an error. That is, as the symmetry of the alignment mark collapses, the error included in the calculation result increases.

Examples of measures for preventing the accuracy from being deteriorated due to the asymmetry of the alignment mark are disclosed in the above-mentioned JP-A-62-54918 and JP-A-61-199633. JP 62-
In Japanese Patent No. 54918, the film thickness distribution of the photoresist coated on the wafer is measured, the wafer alignment pattern position detection error is obtained from the measured film thickness distribution, and the alignment amount is corrected based on the position detection error. . However, this method has a drawback that the processing becomes complicated. Further, in Japanese Patent Laid-Open No. 61-19933, the shape of the alignment mark itself is such that a position detection error is unlikely to occur. However, the alignment mark disclosed in Japanese Patent Laid-Open No. 61-199633 has a drawback that its shape becomes very complicated.

[Means for solving problems]

The alignment mark position detecting method according to the present invention is such that an alignment mark is obtained by converting an analog image signal obtained by capturing an image of the alignment mark with an image pickup device into a digital image signal and processing the digital image signal obtained by the conversion. In the method of obtaining the center position of the above, the alignment mark is composed of at least two mark portions having a shape such that when one mark portion is translated, the alignment mark is overlapped with the other mark portion. This is a process of differentiating a digital image signal and performing similarity pattern matching on the differentiated signal, and recognizing the position where the processing result is maximum as the center position of the alignment mark.

〔Example〕

Hereinafter, embodiments of the present invention will be described with reference to the drawings.

First, the principle of the present invention will be described.

The present invention has a feature that a part of the pattern matching method generally applied in the field of pattern measurement is modified. The flow of processing is a procedure for performing edge extraction of a pattern by operating a differential operator on an input image, and performing similarity pattern matching on the edge-extracted data. The definition of similarity pattern matching and its method will be gradually clarified by the following explanation. In the similarity pattern matching, an expression obtained by modifying a part of the known autocorrelation function is used.

In normal pattern matching or waveform data processing, the autocorrelation is defined by the following equation.

Here, i = 0, 1, ..., N−1, x (i) is a finite number N of sample values, and Rx (i) is an autocorrelation function.

By applying the above equation to data or signal waveform for the purpose of matching, it is possible to obtain a correlation result of a pattern or signal waveform serving as a certain reference. As is clear from this equation, this calculation requires a product-sum calculation of the relative number of times, and thus the calculation takes time. For this reason, the autocorrelation function is suitable for batch processing, but cannot fully support real-time processing.

For example, when the above formula is used for alignment processing of an X-ray exposure apparatus or the like, the long calculation time means that the control processing system including the X / Y stage also uses the alignment processing result as a feedback signal. It becomes a big obstacle. Further, the long calculation time may cause a fatal defect that is not the largest cause of reducing the throughput of the entire apparatus.

Therefore, in the present invention, in order to shorten the calculation result of the autocorrelation function represented by the above equation to several hundredths after devising the shape of the alignment mark, the following modification of the autocorrelation function equation is performed. I went like.

(1) Deviation of alignment mark shape An alignment mark shape that allows a general overlay method using an autocorrelation function in a data signal whose edges have been extracted by operating a first-order differential operator on the input image of the alignment mark. And That is,
The alignment mark is composed of at least two mark portions, and if one mark portion is moved in parallel on the data signal, the alignment mark is formed so as to overlap with the other mark portion. For example, if the alignment mark has a rectangular shape as shown in FIG. 3, it is impossible to superimpose with the autocorrelation function (see FIG. 4). On the other hand, as shown in FIG. 5, an alignment mark composed of two rectangular mark portions arranged close to each other can be superposed by an autocorrelation function.

(2) Deformation of autocorrelation function formula In the present invention, in order to deform the formula of autocorrelation function, attention is paid to the feature of the alignment mark used in the exposure apparatus,
A signal (edge pattern) obtained by applying a first-order differential operator to an analog image signal (input image) obtained by picking up an alignment mark with an image pickup device is basically different from a normal signal waveform. Transforms as.

[1] The distance W between two edge patterns for pattern matching is basically a constant value, and the variation of the distance W due to the process is extremely small.

[2] The range for pattern matching may be set only near the edge pattern.

Based on these features [1] and [2], the process of modifying the equation of the autocorrelation function will be described below.

The autocorrelation function for discrete values is expressed by the following equation as described above.

However, i = 0, 1, ..., N−1.

Here, in order to simplify the expansion, the normalization coefficient 1 / N is omitted.

The equation (2) is used for the data shown in FIG. 6 (same as FIG. 5). In this figure, the horizontal axis represents the pattern distance. For image input, use the one captured by a two-dimensional camera,
The discrete distance is represented by the number of pixels (j) on the image pickup tube surface of the two-dimensional camera. The vertical axis represents the result of converting the analog image signal captured by the two-dimensional camera into a digital image signal and applying a first-order differential operator to the digital image signal obtained by this conversion. ), It is represented by V '. Therefore, in FIG. 6, the equation (2) can be replaced with the following equation.

From the feature [1], the width W of the left pattern and the right pattern forming one alignment mark is basically a constant value, and the width W corresponds to the delay time i in the equation (3).

Equation (4) finds the correlation with respect to the width W of the left and right patterns in the entire area of j in FIG.

However, from the feature [2], the pattern for obtaining the correlation (superposition) only needs to be set for the portion where the edge pattern exists, and as is clear from FIG. 6, the range where the left and right patterns exist is finite. Is.

In FIG. 6, assuming that the range in which the left pattern exists is the correlation section R and the starting point of the correlation section is P, the range of correlation is the range from j = P to j = P + R in FIG. Limited. This is shown in FIG.

From this, the equation (4) is modified as follows.

In addition, although the expression (5) is defined as a function of the width W,
From the feature [2] of the alignment mark, the correlation section R and the start point P of the correlation section are also parameters of A.
Therefore, if the correlation section R and the start point P of the correlation section are also parameters, the equation (5) is converted as follows.

From the above expansion, the equation (2) of the autocorrelation function can finally obtain the equation (6) by considering the features [1] and [2] of the alignment mark. Expression (6) can be regarded as a basic definition expression for similarity pattern matching, and the following six expressions can be considered as expansion expressions thereof.

In other words, A (W, P, R) does not have W, P, R as parameters at the same time, and one of the three parameters is
This is an equation for similarity pattern matching with one or a combination thereof as a parameter.

In fact, when applying the similarity pattern matching expressed by the equation (6) to the process type mark, in most cases, it is not necessary to have the three parameters W, P and R at the same time. Because the mark width W and the pattern width R can be regarded as constants because of the features [1] and [2], in most cases the expression (6) is a function A with P as a parameter.
It is defined as the equation (6-1) of (P). Alternatively, when the mark width W due to the process type mark changes to some extent, the equation (6) is defined and used as the equation (6-5) of the function A (W, P).

Next, the number of calculations is compared between the autocorrelation functions (2) and (6).

The number of data is assumed to be 1000. In the case of the autocorrelation function (2), the number of integrations is 999 and the number of additions is 9 for each data.
Since it is 98 times, (999 + 99
8) × 1000 = 1997000 times of calculation. On the other hand, the number of calculations of the equation (6) is calculated based on the following assumption.

Considering a certain process formation mark, assuming that the mark width R and the pattern existence range (pattern width) W are constant, the equation (6) is a function of only P, that is, (6−
It becomes the formula 1). Here, assuming that each pixel is 0.1 μm, the range of the starting point P is ± 1.5 μm, the mark width R is 5 μm, and the pattern width W is 20 μm, the range of the starting point P, the mark width R, and the pattern width W are , 30, 50 and 200 respectively
It becomes a point. Therefore, the equation (6-1) is expressed by the following equation.

In the case of equation (6-1), the cumulative number of times is 50 for each data.
The total number of calculations is (50+
49) × 30 = 2970 times. Therefore, it is reduced to about 1/670. Actually, this number of times can be calculated in less than 1 ms even if a digital signal processing (DSP) filter is used. In addition, recently used for multiply-accumulate operation (MAC:
If a mulutiplier-accumulator) chip is used, the speed can be further increased.

As described above, by applying the autocorrelation function only to the alignment mark, the number of calculations can be extremely reduced.

Further, in the present invention, the symmetry of the pattern is not presupposed from the expression (6), but depends on the similarity of the left and right patterns. This has the feature that it is relatively strong against the wafer process dependency.

For example, in the case of a resist formation mark, it is assumed that the symmetry of the resist formation mark is broken due to the irradiation angle of X-rays or the like and the conditions such as development, as shown in FIG. In this case, according to the present invention, when the patterns on the left and right of the resist formation mark are close to each other (20 μm, as shown in FIG. 8).
(Before and after), the changes are relatively similar. That is, the left and right patterns are deformed while maintaining the similarity. Further, as shown in FIG. 3, even when a thin film is applied to the upper surface of the process forming mark in the process forming mark, the left and right patterns are close to each other as shown in FIG. Since the conditions of are almost the same, they are applied while maintaining the similarity.

As is clear from the above description, since the expression (6) is a pattern matching method that utilizes the property that the similarity is well maintained regardless of the symmetry of the alignment marks, it is called similarity pattern matching. .

FIG. 10 shows an example of the processing result A (P) with W = 200, R = 50 and P as a parameter in the similarity pattern matching defined by the equation (6).

In FIG. 10, the position of P indicating the first peak value of A (P) is defined as P1, the position of the pattern is recognized, and P
In the −A (P) coordinate, the position of the pattern is used as the center position of the alignment mark, and is calculated by the following equation.

Further, in FIG. 10, when the position of P where the second peak value of A (P) is shown is P2, as is clear from FIG. 10, the P of the actual peak of A (P) is Position is P1
Exists between P2 and P2. In this case, the first peak value and the second
The peak position existing between P1 and P2 can be obtained by performing the interpolation calculation with the peak value of. When the peak position obtained by the interpolation calculation is P1-2, the center position of the alignment mark is obtained by the following equation.

Mark center position = P1-2 + 125 (8) Equation (7) or Equation (8) is obtained for the mask alignment mark and the wafer alignment mark to obtain the positional relationship between the mask and the wafer.

Next, examples of the present invention will be described.

Referring to FIG. 1, first, in this embodiment, the alignment mark is composed of two mark portions, and the shape thereof has such a shape that when one mark portion is translated, the other mark portion overlaps with the other mark portion. The mark portion of this embodiment has a rectangular shape as shown. This alignment mark is imaged by a two-dimensional camera (imaging device) (not shown),
Obtain an analog image signal. The analog image signal is converted into a digital image signal by an analog-digital converter (not shown). Here, the number of gradations for digitization is 6
The number of bits is not less than, preferably 8 bits. By synchronously integrating this digital image signal, noise is removed, the S / N ratio is increased, and at the same time, data compression is performed. Here, the number of times of integration may be any number. Next, the noise-removed and data-compressed digital image signal is differentiated to obtain the edge (contour) of the alignment mark.
To extract. Similarity pattern matching processing represented by equation (6) is performed on the differentiated data. The position where the result of this similarity pattern matching processing is maximum is recognized as the center position of the alignment mark.

Needless to say, the shape of the alignment mark is not limited to this embodiment, and may be any shape as long as the data obtained by processing the input image with the differential operator maintains the similarity.

By combining this method with a processing device of "position detection device for two objects separated by a minute distance", an alignment system in an exposure device such as an X-ray exposure device can be configured. This alignment system enables to set an arbitrary gap and to realize a highly accurate and high throughput alignment system with extremely small process dependency.

Further, the applicable range of the present invention is not limited to the exposure apparatus, but can be applied to those in which the shape and distance of the pattern are estimated in advance in other application fields of pattern recognition. In this case, by providing appropriate parameters in the similarity pattern matching formula, the calculation time can be shortened to several hundredth of that in the case of using the conventional autocorrelation function or cross-correlation function.

〔The invention's effect〕

As is apparent from the above description, according to the present invention, the alignment mark is composed of at least two mark portions, and when one mark portion is moved in parallel, the alignment mark is overlapped with the other mark portion. Since the similarity pattern matching is performed with respect to the signal obtained by differentiating, the effect that the center position of the alignment mark can be recognized with high accuracy and with simple processing even if the symmetry of the alignment mark is broken. Therefore, throughput can be improved, which can greatly contribute to simplification of the production process and improvement of production efficiency.

[Brief description of drawings]

FIG. 1 is a diagram for explaining a method of detecting the position of an alignment mark according to an embodiment of the present invention, FIG. 2 is a diagram for explaining the breaking of the symmetry of a conventional resist formation mark, and FIG. 3 is a conventional diagram. FIG. 5 is a diagram for explaining the breaking of the symmetry of the process forming mark, FIG. 4 is a diagram for explaining that the superposition by the autocorrelation function is impossible in the case of the conventional alignment mark shape, FIG. 5 Is a diagram for explaining that the alignment mark shape of the present invention can be superposed by an autocorrelation function, and FIG. 6 is a first differential value V ′ and 2 of the video signal of the alignment mark of FIG. FIG. 7 shows the width W between two patterns, FIG. 7 shows the start point P of the correlation section and the correlation section R in FIG. 6, and FIG. 8 shows that the resist formation marks of this embodiment maintain similarity. 9 is a diagram for explaining FIG. Is a diagram showing figures, an example of Figure 10 the process result of the similarity pattern matching according to the invention for explaining that the process forming the mark of this embodiment keeps the similarity.

Claims (1)

[Claims] 1. A method of obtaining a center position of an alignment mark by converting an analog image signal obtained by picking up an image of an alignment mark by an image pickup device into a digital image signal and processing the digital image signal obtained by the conversion. In the above, the alignment mark comprises at least two mark portions having a shape such that when one mark portion is moved in parallel, the alignment mark overlaps with the other mark portion, and the processing of the digital image signal differentiates the digital image signal. , Is a process of performing similarity pattern matching represented by the following formula on the differentiated signal, (Here, V '(j) is the differential value of the digital image signal,
(R is a correlation section, P is a start point of the correlation section, and W is a distance between two mark portions adjacent to each other.) A position where the processing result is maximum is recognized as the center position of the alignment mark. Alignment mark position detection method.