A spectrum processing method containing a broadband spectrum and an ellipsometry measurement method

Abstract

The present invention provides a spectrum processing method containing bandwidth spectrum, comprising the steps of: obtaining the ellipsometric spectrum, reflection spectrum, bandwidth of incident light source and number of light intensity distribution nodes of a sample to be tested; interpolating the ellipsometric spectrum and reflection spectrum based on the number of light intensity distribution nodes and the bandwidth of the incident light source to obtain a new ellipsometric spectrum and a new reflection spectrum, and further obtaining a new ellipsometric spectrum vector; obtaining a weight set of light intensity distribution nodes based on the number of light intensity distribution nodes, and constructing a weight matrix according to the weight set; obtaining a weight inverse matrix based on the weight matrix; obtaining a bandwidth-free ellipsometric spectrum based on the weight inverse matrix and the new ellipsometric spectrum vector. The present invention calculates an ideal measurement spectrum without bandwidth factor from an actual measurement spectrum containing bandwidth factor according to the bandwidth of the light source by using a deconvolution method, and uses the ideal measurement spectrum instead of the actual measurement spectrum for analysis, which can effectively avoid time-consuming integral operation on bandwidth in a physical model, and can greatly improve the efficiency of measurement spectrum analysis.

Description

Technical Field

[0001] The present invention relates to the technical field of data analysis of precision optical measuring instruments, and in particular to a spectrum processing method containing a broadband spectrum and an ellipsometric measurement method. Background Art

[0002] Thin film measurement is widely used in the semiconductor industry, biomedicine industry and other fields. The main purpose of the measurement is to obtain information such as the thickness and optical constants of the thin film. In the semiconductor manufacturing industry, faster measurement speed and accurate measurement results are often required. Ellipsometry is currently a commonly used non-destructive and accurate measurement method.

[0003] Ellipsometer is an optical device used to measure film thickness and optical constants. The entire measurement process of ellipsometer is generally divided into two parts:

[0004] (1) Ellipsometry spectrum measurement. Its measurement principle is to use a non-polarized light source to generate polarized light through a polarization state generator. When the light is incident on the sample surface, the polarization state of the reflected light changes. The ellipsometric spectrum of the sample is detected by a polarizer to obtain the data information of the corresponding sample.

[0005] (2) Data analysis and calculation: After obtaining the ellipsometry data, certain analysis and calculation methods are usually used to obtain information such as the thickness and optical constants of the sample.

[0006] The light source used in actual measurement always has a certain bandwidth, that is, the incident light is not ideal monochromatic light, but has a certain spectral structure. For example, 600nm light actually includes all components from 592nm to 608nm. At this time, we say that the bandwidth is 8nm.

[0007] Bandwidth will affect the measurement results of ellipsometry, and the thicker the film, the greater the impact. In the case of bandwidth, the light intensity obtained by each detector will actually be interfered by the light intensity of all wavelengths in a nearby range, and a distribution is generally used to describe the light intensity distribution in this range. For example, when the light intensity is Gaussian, the theoretical calculation generally uses 9-point integration. Therefore, in the subsequent analysis and calculation process, the forward calculation amount will increase to 9 times the previous amount. At the same time, when the bandwidth has a large impact, some initial value algorithms cannot be used, which will also make the analysis complicated and time-consuming, and the efficiency of measuring spectrum analysis is not high. Summary of the invention

[0008] In view of at least one defect or improvement requirement of the prior art mentioned in the background technology, the present invention provides a spectrum processing method containing a bandwidth spectrum, comprising the following steps:

[0009] S1. Obtain the ellipsometric spectrum, reflectance spectrum, bandwidth of the incident light source of the sample to be tested, and the number of light intensity distribution nodes based on the light intensity distribution type;

[0010] S2. interpolating the ellipsometric spectrum and the reflective spectrum based on the number of light intensity distribution nodes and the bandwidth of the incident light source to obtain a new ellipsometric spectrum and a new reflective spectrum;

[0011] S3. Obtaining a new ellipsometric spectrum vector based on the new ellipsometric spectrum and the new reflective spectrum;

[0012] S4. Obtaining a weight set of the light intensity distribution nodes based on the number of light intensity distribution nodes, and constructing a weight matrix according to the weight set;

[0013] S5. Obtaining a corresponding weight inverse matrix based on the weight matrix;

[0014] S6. Obtain a bandwidth-free ellipsometric spectrum based on the inverse weight matrix and the new ellipsometric spectrum vector.

[0015] According to the spectrum processing method containing a bandwidth spectrum provided by the present invention, the ellipsometry spectrum includes an N spectrum, a C spectrum and an S spectrum formed by obtaining spectrum parameters in the form of NCS of the reflected light of the sample to be tested.

[0016] N = cos 2Ψ,

[0017] C = sin 2ΨcosΔ,

[0018] S=sin 2ΨsinΔ,

[0019] Among them, Ψ is the amplitude ratio angle of the reflected light, Δ is the phase difference angle of the reflected light, and N, C and S are the three dimensions of the spectral parameters;

[0020] The reflection spectrum includes a reflectance R spectrum.

[0021] According to the spectrum processing method containing bandwidth spectrum provided by the present invention, the formula of the interpolation interval of the interpolation processing is: d=2bw÷(nums-1),

[0022] Wherein, d is the interpolation interval, bw is the bandwidth of the incident light source, and nums is the number of light intensity distribution nodes;

[0023] The new ellipsometric spectrum includes a new N spectrum NN, a new C spectrum CN, and a new S spectrum SN. The new reflectivity spectrum includes a new reflectivity R spectrum RN. In the new ellipsometric spectrum and the new reflectivity spectrum, the number of wavelength points M of each is: M=D÷d,

[0024] Wherein, D is the wavelength range width of the incident light source.

[0025] According to the spectrum processing method containing bandwidth spectrum provided by the present invention, the new ellipsometry spectrum vector includes component vectors NR, CR, and SR in three dimensions N, C, and S. The calculation formulas of the component vectors NR, CR, and SR are respectively:

[0026] NR(j)=2×NN(j)×RR(j),

[0027] CR(j)=2×CN(j)×RR(j),

[0028] SR(j)=2×SN(j)×RR(j),

[0029] Among them, j is a wavelength point in the wavelength range width, NR(j), CR(j), SR(j) are the values ​​of the component vectors NR, CR, SR corresponding to the j-th wavelength point, NN(j), CN(j), SN(j), RR(j) are the corresponding spectral parameter values ​​in the new N spectrum NN, new C spectrum CN, new S spectrum SN, new reflectivity R spectrum RN corresponding to the j-th wavelength point, respectively, 1≤j≤M.

[0030] According to the spectrum processing method containing bandwidth spectrum provided by the present invention, the step of obtaining the weight set of light intensity distribution nodes based on the number of light intensity distribution nodes specifically includes:

[0031] Map the bandwidth interval to the interval of [-1,1], and divide the interval of [-1,1] into (nums-1) equal intervals based on the number of light intensity distribution nodes nums, that is, obtain nums light intensity distribution nodes, and the probability density f(x i ) is calculated as:

[0032] f(x i )=exp(-(2x i ) 2 ),

[0033] Among them, 1≤i≤nums, x i represents the i-th light intensity distribution node, x i ∈[-1,1];

[0034] The weight value w of each light intensity distribution node i The calculation formula is:

[0035]

[0036] The weight set of the light intensity distribution nodes includes a set consisting of weight values ​​of each of the light intensity distribution nodes.

[0037] According to the spectrum processing method containing bandwidth spectrum provided by the present invention, constructing a weight matrix according to the weight set includes:

[0038] Assign values ​​to each row of the weight matrix. For the i-th row, assign nums weight values ​​w in sequence starting from the i-th digit of the i-th row. i Assign values ​​in sequence, except for the nums digits in the i-th row, all other digits are 0, and the processing of other rows is similar; the size of the weight matrix W is M×(M+nums-1), M is the number of wavelength points, and nums is the number of light intensity distribution nodes.

[0039] According to the spectrum processing method containing bandwidth spectrum provided by the present invention, the formula for obtaining the corresponding weight inverse matrix based on the weight matrix is:

[0040] W inv =(W H W+λI) -1 W H ,

[0041] Among them, W H represents the transposed matrix of the weight matrix W, I is the identity matrix of size M×M, λ is the regularization coefficient, W inv is the inverse weight matrix, whose size is (M+nums-1)×M.

[0042] According to the spectrum processing method with bandwidth spectrum provided by the present invention, the formula for obtaining the bandwidth-free ellipsometric spectrum based on the inverse weight matrix and the new ellipsometric spectrum vector is:

[0043] S1=W inv *NR

[0044] S2=W inv *CR

[0045] S3=W inv *SR,

[0046] Where S1, S2, S3 represent the three parameters of the Stokes quantity of the bandwidthless ellipsometry spectrum, * is the matrix multiplication, W inv is the inverse weight matrix.

[0047] According to any of the above-mentioned spectrum processing methods containing bandwidth spectrum provided by the present invention, the light intensity distribution type is Gaussian distribution.

[0048] The present invention also provides an ellipsometric measurement method, comprising: establishing a theoretical spectrum library, obtaining a measurement spectrum, and finding a theoretical spectrum that best matches the measurement spectrum from the theoretical spectrum library, wherein the measurement spectrum is a spectrum obtained by using any of the above-mentioned spectrum processing methods.

[0049] The present invention provides a spectrum processing method and ellipsometric measurement method containing bandwidth spectrum. According to the bandwidth of the light source in the measuring instrument, the deconvolution method is used to calculate the ideal measurement spectrum without bandwidth factor from the actual measurement spectrum containing bandwidth factor, or to greatly improve the effect of bandwidth influence, which is then used for ellipsometric analysis, etc. In the measurement spectrum analysis stage based on the physical model, the ideal measurement spectrum is used instead of the actual measurement spectrum for analysis, which can effectively avoid the time-consuming integral operation of the bandwidth in the physical model, thereby greatly improving the measurement spectrum analysis efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] In order to more clearly illustrate the technical solution of the present invention, the following is a brief introduction to the drawings required for use in the embodiments. Obviously, the drawings described below are for some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0051] Figure 1 is a flow chart of a spectrum processing method containing a bandwidth spectrum provided by an embodiment of the present invention;

[0052] Figure 2 It is a comparison diagram of a certain spectrum with bandwidth provided by an embodiment of the present invention and its theoretical spectrum without bandwidth;

[0053] Figure 3 It is a comparison diagram of the deconvolved spectrum provided by an embodiment of the present invention and its theoretical bandwidth-free spectrum. DETAILED DESCRIPTION

[0054] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0055] The present invention is based on the bandwidth of the light source and utilizes the deconvolution method to calculate an ideal measurement spectrum without bandwidth factors from an actual measurement spectrum containing bandwidth factors. Specifically, a single-layer model of a sample to be tested is taken as an example to illustrate the application of the deconvolution method in the present application to process a spectrum containing bandwidth spectrum to obtain an ideal measurement spectrum without bandwidth factors. The substrate of the single-layer model is silicon, on which a silicon dioxide film with a thickness of 2137nm is attached. The wavelength range of the measuring light source is 245nm to 1000nm, the incident angle is 65°, and the bandwidth is 9.6nm. In one embodiment, Figure 1 As shown, the spectrum processing method containing a bandwidth spectrum includes the following steps S1-S6:

[0056] S1. Obtain the ellipsometric spectrum, reflectance spectrum, bandwidth of the incident light source, number of light intensity distribution nodes and other data of the thin film sample to be tested.

[0057] Exemplarily, to obtain the ellipsometric spectrum of the sample to be tested, the spectral parameters in the form of NCS of the reflected light of the sample to be tested can be obtained by an optical measuring device to form the ellipsometric spectrum, that is, the ellipsometric spectrum includes N spectrum, C spectrum, and S spectrum:

[0058] N=cos 2Ψ

[0059] C=sin 2ΨcosΔ

[0060] S=sin 2ΨsinΔ

[0061] Among them, Ψ is the amplitude ratio angle of the reflected light, Δ is the phase difference angle of the reflected light, and N, C and S are the three dimensions of the spectral parameters.

[0062] The spectral parameters in the form of NCS are an indirect measurement technology. Generally, the measured spectral data information cannot be directly converted into the film thickness and optical constants of the sample, so it is often necessary to establish a suitable model fitting analysis.

[0063] In addition, the ellipsometry spectrum can be expressed by Stokes quantities, that is, S0, S1, S2, and S3. The values ​​of these four quantities can be directly measured. The relationship between this expression method and the NCS form is:

[0064]

[0065]

[0066]

[0067] in,

[0068] Obtaining the reflectance spectrum of the sample to be tested includes collecting the reflectance R spectrum of the surface of the sample to be tested.

[0069] The number of light intensity distribution nodes is determined based on the type of light intensity distribution. The light intensity distribution can be Gaussian distribution, T distribution, uniform distribution, or the distribution of the actual measured light intensity. Here, Gaussian distribution is preferably used. In this embodiment, the light intensity distribution adopts Gaussian distribution, and the corresponding number of light intensity distribution nodes nums is 9, that is, Gaussian 9-point integral and rectangular summation formula are used to approximate the Gaussian distribution integral of the light intensity to obtain the light intensity value.

[0070] S2. interpolating the ellipsometric spectrum and the reflective spectrum based on the number of light intensity distribution nodes and the bandwidth of the incident light source to obtain a new ellipsometric spectrum and a new reflective spectrum.

[0071] The formula of the interpolation interval of the interpolation processing is: d = 2bw ÷ (nums-1);

[0072] Wherein, d is the interpolation interval, bw is the bandwidth of the incident light source, and nums is the number of light intensity distribution nodes.

[0073] Based on this, the number of wavelength points M in the new ellipsometric spectrum and the new reflectance spectrum can also be calculated: M = D ÷ d;

[0074] Wherein, D is the wavelength range width of the incident light source, and d is the interpolation interval. According to the number of distribution nodes nums=9 and the bandwidth bw=9.6nm, the ellipsometric spectrum and the reflectance spectrum are interpolated, and the interpolation interval d is 2×9.6nm÷(9-1)=2.4nm, that is, the spectrum from 245nm to 1000nm is interpolated into multiple segments with an interval of 2.4nm, and the number of wavelength points of the interval M=D÷d=(1000nm-245nm)÷2.4nm≈315, that is, the data of 315 wavelength points can be obtained in the ellipsometric spectrum and the reflectance spectrum respectively, wherein 1000nm-245nm=755nm is the wavelength range width D, and a new ellipsometric spectrum and a new reflectance spectrum can be obtained based on the above interpolation processing. Exemplarily, after interpolation, the N spectrum, C spectrum, S spectrum in the ellipsometric spectrum and the reflectance R spectrum can obtain a new N spectrum, a new C spectrum, a new S spectrum and a new reflectance R spectrum, which are respectively recorded as: NN, CN, SN, RN.

[0075] S3. Obtain a new ellipsometric spectrum vector based on the new ellipsometric spectrum and the new reflective spectrum. The new ellipsometric spectrum vector includes component vectors NR, CR, and SR in three dimensions N, C, and S. The specific calculation formula for obtaining the component vectors NR, CR, and SR is:

[0076] NR(j)=2×NN(j)×RR(j)

[0077] CR(j)=2×CN(j)×RR(j)

[0078] SR(j)=2×SN(j)×RR(j)

[0079] Among them, j represents a wavelength point in the wavelength range width D, NR(j), CR(j), and SR(j) are the values ​​of the component vectors NR, CR, and SR corresponding to the j-th wavelength point, respectively, NN(j), CN(j), SN(j), and RR(j) are the corresponding spectral parameter values ​​in the new N spectrum NN, new C spectrum CN, new S spectrum SN, and new reflectivity R spectrum RN corresponding to the j-th wavelength point, respectively, 1≤j≤M, that is, the length of the NR, CR, and SR vectors is consistent with the value of the wavelength point number M.

[0080] S4. Obtaining a weight set of the light intensity distribution nodes based on the number of light intensity distribution nodes, and constructing a weight matrix according to the weight set. Specifically including:

[0081] Map the bandwidth interval to the interval [-1,1], and divide the interval [-1,1] into (nums-1) equal intervals based on the number of light intensity distribution nodes nums, that is, obtain nums light intensity distribution nodes. The probability density f(x i ) is calculated as:

[0082] f(x i )=exp(-(2x i ) 2 ),

[0083] Among them, 1≤i≤nums, x i represents the i-th light intensity distribution node, x i ∈[﹣1,1]. The coefficients before the probability density are omitted here because normalization is required later and the coefficients do not affect normalization.

[0084] Correspondingly, the weight value w of each light intensity distribution node is i The calculation formula is:

[0085]

[0086] The weight set of the light intensity distribution node is a set of weight values ​​of each distribution node.

[0087] In this embodiment, the bandwidth of 9.6nm, that is, the interval [-9.6,9.6], is mapped to the interval [-1,1]. This mapping does not mean that the variance is 1, but it is mapped to a Gaussian distribution with a variance of 1 / 8 and a mean of 0. At this time, the probability of the interval [-1,1] is almost close to 1, and the difference does not exceed 10 to the power of -15. When mapped to the interval [-1,1], the positions of the 9 Gaussian distribution nodes are X = [-1, -0.75, -0.5, -0.25, 0, 0.25, 0.5, 0.75, 1], and the weight set obtained by calculating the 9 Gaussian distribution nodes is w = [0.0052, 0.0298, 0.1039, 0.22, 0.2824, 0.22, 0.1039, 0.0298, 0.0052], which corresponds to the position of each Gaussian distribution node in X respectively.

[0088] After calculating the weight set, it is necessary to construct a weight matrix W, and the size of the weight matrix W is M×(M+nums-1). In this embodiment, the size of the weight matrix W is: 315×(315+9-1)=315×323.

[0089] The specific method of constructing the weight matrix W according to the weight set is: for the i-th row of the weight matrix W, starting from the i-th digit of the i-th row, the nums weight values ​​w i The values ​​are assigned in order, and the remaining digits are all assigned to 0. In this embodiment, nums = 9. For example, for the first row, the values ​​are assigned starting from the first digit of the first row, that is, the digits from 1 to 9 are assigned to the 9 weight values ​​of the weight set w in order, and the remaining digits are all assigned to 0; for the second row, the digits from the 2nd to the 10th of the second row are assigned to the 9 weight values ​​of the weight set w in order, and the remaining digits are all assigned to 0; for the i-th row, the digits from the i-th to the i+9-1th of the i-th row are assigned to the 9 weight values ​​of the weight set w in order, and the remaining digits are all assigned to 0, and the processing method of the other rows of the weight matrix W is similar.

[0090] S5. Obtain a corresponding weight inverse matrix based on the weight matrix.

[0091] After obtaining the weight matrix W, it is necessary to solve the corresponding weight inverse matrix W inv , can be solved by using Moore-Penrose generalized inverse or other generalized inverse definitions, or by using regularization methods. Regularization methods are used to solve the problem that in actual measurements, due to noise and other factors, the data is biased, making the inverse problem an ill-posed problem, which leads to abnormal solutions. There are many regularization methods, such as Landweber iteration method, generalized Newton iteration method, regularized Gauss-Newton iteration method, etc. This embodiment adopts Tikhonov regularization method,

[0092] W inv =(W H W+λI) -1 W H ,

[0093] Among them, W H represents the transposed matrix of the weight matrix W, I is the unit matrix of M×M=315×315, λ is the regularization coefficient, which is generally between 0.00001 and 0.01 and can be adjusted according to the calculation effect of the measured data, W inv is the weight inverse matrix, and its size is (M+nums-1)×M=(315+9-1)×315=323×315.

[0094] S6. Obtain a bandwidth-free ellipsometric spectrum based on the inverse weight matrix and the new ellipsometric spectrum vector. The specific calculation formula is:

[0095] S1=W inv *NR

[0096] S2=W inv *CR

[0097] S3=W inv *SR

[0098] Among them, S1, S2, S3 represent the three parameters in the Stokes quantity of the bandwidthless ellipsometry spectrum. The bandwidthless ellipsometry spectrum can be obtained by converting S1, S2, S3 into the representation of the ellipsometry parameters NCS; * is matrix multiplication, W inv is the weight inverse matrix, and its size is (M+nums-1)×M=(315+9-1)×315=323×315; NR, CR, and SR are the component vectors of the new ellipsometric spectrum vector in the three dimensions of N, C, and S, respectively, and they are all vectors with a length of M=315.

[0099] Figure 2 It is a comparison diagram of a certain spectrum with bandwidth provided by an embodiment of the present invention and its theoretical spectrum without bandwidth; Figure 3 : This is a comparison diagram of the spectrum after deconvolution provided by the embodiment of the present invention and its theoretical spectrum without bandwidth. It is a comparison of the spectrum after deconvolution, the dotted line is the result of deconvolution, and the solid line is the spectrum without bandwidth obtained by theoretical calculation of the model. Other ellipsometric parameters can be obtained from S1, S2, and S3, and then used for conventional ellipsometric analysis.

[0100] An embodiment of the present invention also provides an ellipsometric measurement method, comprising: establishing a theoretical spectrum library, acquiring a measurement spectrum, and finding a theoretical spectrum that best matches the measurement spectrum from the theoretical spectrum library, wherein the measurement spectrum is a spectrum obtained by using any of the above-mentioned spectrum processing methods.

[0101] Note that the above are only some preferred embodiments of the present invention. Those skilled in the art should understand that the present invention is not limited to these specific embodiments, and that various obvious modifications, readjustments, equivalent substitutions or improvements that can be made within the spirit and principles of the present invention should be included in the protection scope of the present invention. Therefore, although the present invention has been described in more detail through the above embodiments, the present invention is not limited to the above embodiments, and may include more other equivalent embodiments without departing from the concept of the present invention, and the scope of the present invention is determined by the scope of the appended claims.

Claims

1. A spectrum processing method containing a bandwidth spectrum, characterized in that: The steps include: S1. Obtain the ellipsometric spectrum, reflectance spectrum, bandwidth of the incident light source of the sample to be tested, and the number of light intensity distribution nodes based on the light intensity distribution type; S2. interpolating the ellipsometric spectrum and the reflective spectrum based on the number of light intensity distribution nodes and the bandwidth of the incident light source to obtain a new ellipsometric spectrum and a new reflective spectrum; S3. Obtaining a new ellipsometric spectrum vector based on the new ellipsometric spectrum and the new reflective spectrum; S4. Obtaining a weight set of the light intensity distribution nodes based on the number of light intensity distribution nodes, and constructing a weight matrix according to the weight set; S5. Obtaining a corresponding weight inverse matrix based on the weight matrix; S6. Acquire a bandwidth-free ellipsometric spectrum based on the inverse weight matrix and the new ellipsometric spectrum vector; The formula for the interpolation interval of the interpolation process is: d = 2bw ÷ (nums - 1), Wherein, d is the interpolation interval, bw is the bandwidth of the incident light source, and nums is the number of light intensity distribution nodes; In the new ellipsometric spectrum and the new reflectance spectrum, the number of wavelength points M of each is: M=D÷d, where D is the wavelength range width of the incident light source; The step of obtaining a weight set of light intensity distribution nodes based on the number of light intensity distribution nodes specifically includes: Map the bandwidth interval to the interval of [-1,1], and divide the interval of [-1,1] into (nums-1) equal intervals based on the number of light intensity distribution nodes nums, that is, obtain nums light intensity distribution nodes, and the probability density f(x i ) is calculated as: f(x i )=exp(-(2x i ) 2 ), Among them, 1≤i≤nums, x i represents the i-th light intensity distribution node, x i ∈[-1,1]; The weight value w of each light intensity distribution node i The calculation formula is: The weight set of the light intensity distribution nodes includes a set composed of weight values ​​of each of the light intensity distribution nodes; The constructing a weight matrix according to the weight set comprises: Assign values ​​to each row of the weight matrix. For the i-th row, assign nums weight values ​​w in sequence starting from the i-th digit of the i-th row. i Assign values ​​in sequence, except for the nums digits in the i-th row, all other digits are 0, and the processing of other rows is similar; the size of the weight matrix W is M×(M+nums-1), M is the number of wavelength points, and nums is the number of light intensity distribution nodes.

2. The spectrum processing method containing a bandwidth spectrum according to claim 1, characterized in that: The ellipsometry spectrum includes an N spectrum, a C spectrum and an S spectrum formed by obtaining spectral parameters in the form of NCS of the reflected light of the sample to be tested, N=cos2Ψ, C=sin2ΨcosΔ, S=sin2ΨsinΔ, Among them, Ψ is the amplitude ratio angle of the reflected light, Δ is the phase difference angle of the reflected light, and N, C and S are the three dimensions of the spectral parameters; The reflection spectrum includes a reflectance R spectrum.

3. The spectrum processing method containing a bandwidth spectrum according to claim 2, characterized in that: The new ellipsometric spectrum includes a new N spectrum NN, a new C spectrum CN, and a new S spectrum SN. The new reflectance spectrum includes a new reflectance R spectrum RN.

4. The spectrum processing method containing a bandwidth spectrum according to claim 3, characterized in that: The new ellipsometry spectral vector includes component vectors NR, CR, and SR in three dimensions N, C, and S. The calculation formulas of the component vectors NR, CR, and SR are respectively: NR(j)=2×NN(j)×RR(j), CR(j)=2×CN(j)×RR(j), SR(j)=2×SN(j)×RR(j), Among them, j is a wavelength point in the wavelength range width, NR(j), CR(j), SR(j) are the values ​​of the component vectors NR, CR, SR corresponding to the j-th wavelength point, NN(j), CN(j), SN(j), RR(j) are the corresponding spectral parameter values ​​in the new N spectrum NN, new C spectrum CN, new S spectrum SN, new reflectivity R spectrum RN corresponding to the j-th wavelength point, respectively, 1≤j≤M.

5. The spectrum processing method containing a bandwidth spectrum according to claim 1, characterized in that: The formula for obtaining the corresponding weight inverse matrix based on the weight matrix is: W inv =(W H W+λI) -1 W H , Among them, W H represents the transposed matrix of the weight matrix W, I is the identity matrix of size M×M, λ is the regularization coefficient, W inv is the weight inverse matrix, whose size is (M+nums-1)×M.

6. The spectrum processing method containing a bandwidth spectrum according to claim 5, characterized in that: The formula for obtaining the bandwidth-free ellipsometric spectrum based on the inverse weight matrix and the new ellipsometric spectrum vector is: S1=W inv *NR, S2=W inv *CR, <h2 style=";text-align:left;direction:ltr">S3=W<h2 style=";text-align:left;direction:ltr"> inv <h2 style=";text-align:left;direction:ltr"> *SR, Among them, S1, S2, S3 represent the three parameters of the Stokes quantity of the bandwidthless ellipsometry spectrum, * is the matrix multiplication, W inv is the inverse weight matrix.

7. The spectrum processing method containing a bandwidth spectrum according to any one of claims 1 to 6, characterized in that: The light intensity distribution type is Gaussian distribution.

8. An ellipsometric measurement method, characterized in that: include: A theoretical spectrum library is established, a measured spectrum is obtained, and a theoretical spectrum that best matches the measured spectrum is found from the theoretical spectrum library, wherein the measured spectrum is a spectrum obtained by the spectrum processing method according to any one of claims 1 to 7.

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