CN102236261A - Method, device and system for processing off-axis signals based on orthogonalization model - Google Patents

Abstract

The invention discloses a method, device and system for processing off-axis signals based on an orthogonalization model, wherein the phase of aligning signals is rapidly and accurately determined by determining the orthogonalization model, obtaining sampling signals and light intensity sampling signals and accumulating and simplifying the sampling signals, thereby finally determining the aligning position of the aligning signals.

Description

A kind of off-axis signal treatment method, Apparatus and system based on the orthogonalization model

Technical field

The present invention relates to the semiconductor lithography production field, relate in particular to a kind of off-axis signal treatment method, Apparatus and system based on the orthogonalization model.

Background technology

Alignment precision is one of key index of litho machine, in order to realize higher alignment precision, need accurately set up the relation between photo-etching machine silicon chip coordinate system and the worktable coordinate system.Off-axis alignment is to be radiated at the reflected light of the polarization laser on the silicon chip mark again via the aligning between the reference marker (Fig. 2) of diffraction mark (Fig. 1) that forms behind the diffraction and silicon chip, because the silicon chip reference marker is attached on silicon chip or the silicon slice workpiece platform, just can form alignment scanning (Fig. 3) between silicon chip mark and the reference marker by at the uniform velocity mobile silicon slice workpiece platform, can obtain accurate aligned position (Fig. 4) by the position sampling signal of synchronized sampling and luminosity sampling signal are carried out signal Processing.Silicon chip mark is on silicon chip or work stage, and reference marker is positioned at fixed position, work stage top, and in the alignment scanning process, silicon chip mark moves and moves along with work stage, and reference marker is motionless.

Chinese patent CN1794090A discloses a kind of real-time signal-processing method based on linear shape model, its characteristics are to utilize the time interval of sampling that the matrix of coefficients in the normal equation of least square method is progressively found the solution, after sampling finishes fully, only need find the solution and to obtain fitting parameter, thereby determine aligned position normal equation.But this method need be found the solution the matrix on one three rank and (as: promptly find the solution Ax=d, A is a third-order matrix, d is a tri-vector, x is a tri-vector to be asked), this has influenced efficient to a certain extent, this matrix might (conditional number be the parameter that characterizes matrix one specific character owing to conditional number simultaneously, as Ax=d, under the certain situation of A error, if the matrix A conditional number is big more, then x to find the solution the error that draws big more) big and cause the error of result of calculation, thereby influence alignment precision.

Therefore, designing a kind of raising alignment precision and the simple off-axis signal treatment method of computing is very necessary, is one of semiconductor lithography production field problem anxious to be solved at present.

Summary of the invention

The embodiment of the invention provides a kind of off-axis signal treatment method based on the orthogonalization model, Apparatus and system, by determining an orthogonalization model and obtaining the position sampling signal and the luminosity sampling signal, and the sampled signal abbreviation that adds up handled, be that Reduce handles, so that the accurate fast phase place of determining registration signal, thereby finally determine its aligned position.

The embodiment of the invention provides following technical scheme:

A kind of off-axis signal treatment method based on the orthogonalization model, step comprises:

Step 1, determine the orthogonalization model;

Step 2, carry out off-axis alignment scanning, obtain position sampling signal and luminosity sampling signal;

Step 3, position sampled signal and the luminosity sampling signal abbreviation that adds up is in real time handled;

Step 4, judge whether to be last group sampling;

Step 5, the abbreviation result that adds up is found the solution, obtain the orthogonalization model parameter;

Step 6, the orthogonalization model parameter is merged arrangement;

The phase place of step 7, calculating orthogonalization model.

Preferably, the orthogonalization model of above-mentioned steps one is: f (x)=a ₀p ₀(x)+a ₁p ₁(x)+a ₂p ₂(x), (p0 (x), p1 (x), p2 (x)) is the function base of one group of quadrature in the formula, a0, and a1, a2 is parameter to be asked, wherein:

p ₀(x)＝1

p ₁(x)＝cos(Kx)-β ₁

p ₂(x)＝sin(Kx)-β ₂-β ₃p ₁(x)

K is known constant in this model,, β 1, and β 2, and β 3 is parameter to be asked, and x is the independent variable in the function expression.

Preferably, in the above-mentioned steps three, the sampled signal abbreviation that adds up in real time is treated to each group sampled signal (x _i, I _i) (i=0,1, Lm), m represents total sampling number, order

C _n＝cos(Kx _n)

S _n＝sin(Kx _n)

Add up and obtain following parameters:

b ₁＝∑C _n

b ₂＝∑S _n

${\mathrm{<figure-callout\; id="3"\; label="b"\; filenames="HSA00000110791900041.png"\; state="\{\{state\}\}">b</figure-callout>}}_3={\mathrm{\&Sigma;<figure-callout\; id="2"\; label="C\; n"\; filenames="HSA00000110791900041.png"\; state="\{\{state\}\}">C</figure-callout>}}_n^{}$

$b_4={\mathrm{\&Sigma;<figure-callout\; id="2"\; label="S\; n"\; filenames="HSA00000110791900041.png"\; state="\{\{state\}\}">S</figure-callout>}}_n^{}$

b ₅＝∑S _nC _n

b ₆＝∑I _n

b ₇＝∑I _nC _n

b ₈＝∑I _nS _n

Wherein Xi is the position sampling signal, and Ii is the luminosity sampling signal, Cn, and Sn, b1～b8 are the temporary variable in the computation process.

Preferably, in the above-mentioned steps four, described judgment mode is last and organizes sampled point when equaling default sampling number when the position sampling signal of actual samples and luminosity sampling signal.

Preferably, above-mentioned stating in the step 5 obtained the parameter a of above-mentioned orthogonalization model ₀, a ₁, a ₂, the specific algorithm formula is:

(p ₀，p ₀)＝m

${\mathrm{\&beta;}}_1=\frac{b_1}{m}$

$({\mathrm{<figure-callout\; id="1"\; label="p"\; filenames="HSA00000110791900041.png"\; state="\{\{state\}\}">p</figure-callout>}}_1,p_1)=b_3-2{\mathrm{\&beta;}}_1{\mathrm{<figure-callout\; id="1"\; label="b"\; filenames="HSA00000110791900041.png"\; state="\{\{state\}\}">b</figure-callout>}}_1+{\mathrm{\&beta;}}_1^{2}m$

${\mathrm{\&beta;}}_2=\frac{b_2}{m}$

${\mathrm{\&beta;}}_3=\frac{b_5-{\mathrm{\&beta;}}_1{b}_2}{({\mathrm{<figure-callout\; id="1"\; label="p"\; filenames="HSA00000110791900041.png"\; state="\{\{state\}\}">p</figure-callout>}}_1,p_1)}$

$({\mathrm{<figure-callout\; id="2"\; label="p"\; filenames="HSA00000110791900041.png"\; state="\{\{state\}\}">p</figure-callout>}}_2,p_2)=b_4+{\mathrm{\&beta;}}_2^{2}m+{\mathrm{\&beta;}}_3^2({\mathrm{<figure-callout\; id="1"\; label="p"\; filenames="HSA00000110791900041.png"\; state="\{\{state\}\}">p</figure-callout>}}_1,p_1)-2{\mathrm{\&beta;}}_2{b}_2-2{\mathrm{\&beta;}}_3{b}_5+2{\mathrm{\&beta;}}_1{\mathrm{\&beta;}}_3{\mathrm{<figure-callout\; id="2"\; label="b"\; filenames="HSA00000110791900041.png"\; state="\{\{state\}\}">b</figure-callout>}}_2$

$a_0=\frac{b_6}{(p_0,p_0)}$

$a_1=\frac{b_7-{\mathrm{\&beta;}}_1{b}_6}{({\mathrm{<figure-callout\; id="1"\; label="p"\; filenames="HSA00000110791900041.png"\; state="\{\{state\}\}">p</figure-callout>}}_1,p_1)}$

$a_2=\frac{b_8-{\mathrm{\&beta;}}_2{b}_6-{\mathrm{\&beta;}}_3({\mathrm{<figure-callout\; id="1"\; label="p"\; filenames="HSA00000110791900041.png"\; state="\{\{state\}\}">p</figure-callout>}}_1,I)}{({\mathrm{<figure-callout\; id="2"\; label="p"\; filenames="HSA00000110791900041.png"\; state="\{\{state\}\}">p</figure-callout>}}_2,p_2)}$

Wherein, (p ₀, p ₀), (p ₁, p ₁), (p ₂, p ₂) be the temporary variable in the computation process, β 1, and β 2, and β 3 is parameter to be asked, a0, a1, a2 is parameter to be asked.

Preferably, in the above-mentioned steps six the orthogonalization model parameter is merged arrangement, specific algorithm is as follows:

DC＝a ₀+β ₁β ₃a ₂-β ₁a ₁-β ₂a ₂

A＝a ₁-β ₃a ₂

B＝a ₂

Wherein, DC is a dark current, and A is a cosine coefficient, and B is a cosine coefficient, and β 1, and β 2, and β 3 is parameter to be asked.

Preferably, the phase place of orthogonalization model is as follows in the described step 7:

Wherein A is a cosine coefficient, and B is a cosine coefficient.

A kind of based on the orthogonalization model from the axis signal treating apparatus, above-mentioned from the axis signal treating apparatus comprise sampling module, the abbreviation processing module that adds up, parameter acquisition module, phase calculation module, the above-mentioned abbreviation processing module that adds up, being used for sampled signal to the sampling module abbreviation that adds up in real time handles, and result is transferred to parameter acquisition module, the phase calculation module is used for calculating according to the orthogonalization model parameter phase place of orthogonalization model.

Preferably, above-mentioned sampling module also comprises a model determination module, and the orthogonalization model is f (x)=a ₀p ₀(x)+a ₁p ₁(x)+a ₂p ₂(x), (p0 (x), p1 (x), p2 (x)) is the function base of one group of quadrature in the formula, a0, and a1, a2 is parameter to be asked, wherein:

p ₀(x)＝1

p ₁(x)＝cos(Kx)-β ₁

p ₂(x)＝sin(Kx)-β ₂-β ₃p ₁(x)

K is known constant in this model,, β 1, and β 2, and β 3 is parameter to be asked, and x is that the change certainly in the function expression is heavy.

Preferably, the above-mentioned abbreviation processing module that adds up is used for sampled signal to the sampling module abbreviation that adds up in real time and handles, to each group sampled signal (x _i, I _i) (i=0,1, L m), m represents total sampling number, order

C _n＝cos(Kx _n)

S _n＝sin(Kx _n)

Add up and obtain following parameters:

b ₁＝∑C _n

b ₂＝∑S _n

${\mathrm{<figure-callout\; id="3"\; label="b"\; filenames="HSA00000110791900041.png"\; state="\{\{state\}\}">b</figure-callout>}}_3={\mathrm{\&Sigma;<figure-callout\; id="2"\; label="C\; n"\; filenames="HSA00000110791900041.png"\; state="\{\{state\}\}">C</figure-callout>}}_n^{}$

${\mathrm{<figure-callout\; id="4"\; label="b"\; filenames="HSA00000110791900041.png"\; state="\{\{state\}\}">b</figure-callout>}}_4={\mathrm{\&Sigma;<figure-callout\; id="2"\; label="S\; n"\; filenames="HSA00000110791900041.png"\; state="\{\{state\}\}">S</figure-callout>}}_n^{}$

b ₅＝∑S _nC _n

b ₆＝∑I _n

b ₇＝∑I _nC _n

b ₈＝∑I _nS _n

Wherein Xi (i=0,1 ... m) be the position sampling signal, Ii (i=0,1 ... m) be the luminosity sampling signal, Cn, Sn, b1～b8 are the temporary variable in the computation process.

Preferably, the above-mentioned parameter acquisition module is used to obtain orthogonalization model parameter a ₀, a ₁, a ₂, concrete formula is:

(p ₀，p ₀)＝m

${\mathrm{\&beta;}}_1=\frac{b_1}{m}$

$({\mathrm{<figure-callout\; id="1"\; label="p"\; filenames="HSA00000110791900041.png"\; state="\{\{state\}\}">p</figure-callout>}}_1,p_1)=b_3-2{\mathrm{\&beta;}}_1{\mathrm{<figure-callout\; id="1"\; label="b"\; filenames="HSA00000110791900041.png"\; state="\{\{state\}\}">b</figure-callout>}}_1+{\mathrm{\&beta;}}_1^{2}m$

${\mathrm{\&beta;}}_2=\frac{b_2}{m}$

${\mathrm{\&beta;}}_3=\frac{b_5-{\mathrm{\&beta;}}_1{b}_2}{({\mathrm{<figure-callout\; id="1"\; label="p"\; filenames="HSA00000110791900041.png"\; state="\{\{state\}\}">p</figure-callout>}}_1,p_1)}$

$({\mathrm{<figure-callout\; id="2"\; label="p"\; filenames="HSA00000110791900041.png"\; state="\{\{state\}\}">p</figure-callout>}}_2,p_2)={\mathrm{<figure-callout\; id="4"\; label="b"\; filenames="HSA00000110791900041.png"\; state="\{\{state\}\}">b</figure-callout>}}_4+{\mathrm{\&beta;}}_2^{2}m+{\mathrm{\&beta;}}_3^2({\mathrm{<figure-callout\; id="1"\; label="p"\; filenames="HSA00000110791900041.png"\; state="\{\{state\}\}">p</figure-callout>}}_1,p_1)-2{\mathrm{\&beta;}}_2{b}_2-2{\mathrm{\&beta;}}_3{b}_5+2{\mathrm{\&beta;}}_1{\mathrm{\&beta;}}_3{\mathrm{<figure-callout\; id="2"\; label="b"\; filenames="HSA00000110791900041.png"\; state="\{\{state\}\}">b</figure-callout>}}_2$

$a_0=\frac{b_6}{(p_0,p_0)}$

$a_1=\frac{b_7-{\mathrm{\&beta;}}_1{b}_6}{({\mathrm{<figure-callout\; id="1"\; label="p"\; filenames="HSA00000110791900041.png"\; state="\{\{state\}\}">p</figure-callout>}}_1,p_1)}$

$a_2=\frac{b_8-{\mathrm{\&beta;}}_2{b}_6-{\mathrm{\&beta;}}_3({\mathrm{<figure-callout\; id="1"\; label="p"\; filenames="HSA00000110791900041.png"\; state="\{\{state\}\}">p</figure-callout>}}_1,I)}{({\mathrm{<figure-callout\; id="2"\; label="p"\; filenames="HSA00000110791900041.png"\; state="\{\{state\}\}">p</figure-callout>}}_2,p_2)}$

Wherein, (p ₀, p ₀), (p ₁, p ₁), (p ₂, p ₂) be the temporary variable in the computation process, β 1, and β 2, and β 3 is parameter to be asked.

Described phase calculation module comprises that also a parameter merges sorting module, is used for the orthogonalization model parameter is merged arrangement, and concrete formula is:

DC＝a ₀+β ₁β ₃a ₂-β ₁α ₁-β ₂a ₂

A＝a ₁-β ₃a ₂

B＝a ₂

Wherein, DC is a dark current, and A is a cosine coefficient, and B is a cosine coefficient, and β 1, and β 2, and β 3 is parameter to be asked.

Preferably, above-mentioned phase calculation module is used to calculate the phase place of orthogonalization model,

Promptly

Wherein A is a cosine coefficient, and B is a cosine coefficient.

A kind of based on the orthogonalization model from the axis signal disposal system, comprise above-mentioned any one described from the axis signal treating apparatus.

A kind of off-axis signal treatment method provided by the invention, Apparatus and system based on the orthogonalization model, by determining an orthogonalization model and obtaining the position sampling signal and the luminosity sampling signal, and the sampled signal abbreviation that adds up handled, so that the accurate fast phase place of determining registration signal, thereby finally determine its aligned position.

Description of drawings

In order to be illustrated more clearly in the embodiment of the invention or technical scheme of the prior art, to do to introduce simply to the accompanying drawing of required use in embodiment or the description of the Prior Art below, apparently, accompanying drawing in describing below only is some embodiments of the present invention, for those of ordinary skills, under the prerequisite of not paying creative work, can also obtain other accompanying drawing according to these accompanying drawings.

Fig. 1 is the diffraction mark synoptic diagram of silicon chip;

Fig. 2 is the reference marker synoptic diagram of silicon chip;

Fig. 3 is the scanning synoptic diagram of diffraction mark with respect to reference marker;

Fig. 4 is the change curve synoptic diagram of light intensity with the position;

The off-axis signal treatment method process flow diagram that Fig. 5 embodiment of the invention provides based on the orthogonalization model;

Fig. 6 embodiment of the invention provide based on the orthogonalization model from axis signal treating apparatus synoptic diagram;

Embodiment

The embodiment of the invention provides a kind of off-axis signal treatment method based on the orthogonalization model, Apparatus and system, by determining an orthogonalization model and obtaining the position sampling signal and the luminosity sampling signal, and sampled signal is carried out Reduce handle, the abbreviation that promptly adds up is handled, so that the accurate fast phase place of determining registration signal, thereby finally determine its aligned position.For making purpose of the present invention, technical scheme and advantage clearer, the embodiment that develops simultaneously with reference to the accompanying drawings, the present invention is described in more detail.

The embodiment of the invention provides a kind of off-axis signal treatment method based on the orthogonalization model, and as shown in Figure 5, concrete steps comprise:

Step 1, determine the orthogonalization model;

Particularly, the orthogonalization model is f (x)=a ₀p ₀(x)+a ₁p ₁(x)+a ₂p ₂(x), (p0 (x), p1 (x), p2 (x)) is the function base of one group of quadrature in the formula, a0, and a1, a2 is parameter to be asked, wherein:

p ₀(x)＝1

p ₁(x)＝cos(Kx)-β ₁

p ₂(x)＝sin(Kx)-β ₂-β ₃p ₁(x)

K is known constant in this model, and β 1, and β 2, and β 3 is parameter to be asked, and x is the independent variable in the function expression.

Step 2, carry out off-axis alignment scanning, obtain position sampling signal and luminosity sampling signal;

Particularly, (x _i, I _i) (i=0,1, Lm) the position sampling signal and the luminosity sampling signal of the some groups of correspondences that sampling obtains in the off-axis alignment scanning process carried out in expression.

Step 3, position sampled signal and the luminosity sampling signal abbreviation that adds up is in real time handled;

Particularly, to each group sampled signal (x _i, I _i) (i=0,1, Lm) (the position sampling signal and the luminosity sampling signals of the some groups of correspondences that sampling obtains in the off-axis alignment scanning process), m represents total sampling number, order

C _n＝cos(Kx _n)

S _n＝sin(Kx _n)

Add up and obtain following parameters:

b ₁＝∑C _n

b ₂＝∑S _n

${\mathrm{<figure-callout\; id="3"\; label="b"\; filenames="HSA00000110791900041.png"\; state="\{\{state\}\}">b</figure-callout>}}_3={\mathrm{\&Sigma;<figure-callout\; id="2"\; label="C\; n"\; filenames="HSA00000110791900041.png"\; state="\{\{state\}\}">C</figure-callout>}}_n^{}$

${\mathrm{<figure-callout\; id="4"\; label="b"\; filenames="HSA00000110791900041.png"\; state="\{\{state\}\}">b</figure-callout>}}_4={\mathrm{\&Sigma;<figure-callout\; id="2"\; label="S\; n"\; filenames="HSA00000110791900041.png"\; state="\{\{state\}\}">S</figure-callout>}}_n^{}$

b ₅＝∑S _nC _n

b ₆＝∑I _n

b ₇＝∑I _nC _n

b ₈＝∑I _nS _n

b ₁=∑ C _nSummation adds up behind the position data complementation string that expression obtains all samplings.

Wherein Xi is the position sampling signal, and Ii is the luminosity sampling signal, Cn, and Sn, b1～b8 are the temporary variable in the computation process.

Step 4, judge whether to be last group sampling;

Particularly, not last group sampling as judged result, then repeating step three, are last group samplings as judged result, and then the parameter found the solution of step 3 finishes execution in step five.

Whether be that last group sampling is judged in the following way: judgment mode is last and organizes sampled point when equaling default sampling number when the position sampling signal of actual samples and luminosity sampling signal.

Step 5, the abbreviation result that adds up is found the solution, obtain the orthogonalization model parameter;

Particularly, utilize the abbreviation result that adds up (being b1-b8) of step 3, obtain the parameter a of orthogonalization model shown in step 1 ₀, a ₁, a ₂, the specific algorithm formula is:

(p ₀，p ₀)＝m

${\mathrm{\&beta;}}_1=\frac{b_1}{m}$

$({\mathrm{<figure-callout\; id="1"\; label="p"\; filenames="HSA00000110791900041.png"\; state="\{\{state\}\}">p</figure-callout>}}_1,p_1)=b_3-2{\mathrm{\&beta;}}_1{\mathrm{<figure-callout\; id="1"\; label="b"\; filenames="HSA00000110791900041.png"\; state="\{\{state\}\}">b</figure-callout>}}_1+{\mathrm{\&beta;}}_1^{2}m$

${\mathrm{\&beta;}}_2=\frac{b_2}{m}$

${\mathrm{\&beta;}}_3=\frac{b_5-{\mathrm{\&beta;}}_1{b}_2}{({\mathrm{<figure-callout\; id="1"\; label="p"\; filenames="HSA00000110791900041.png"\; state="\{\{state\}\}">p</figure-callout>}}_1,p_1)}$

$({\mathrm{<figure-callout\; id="2"\; label="p"\; filenames="HSA00000110791900041.png"\; state="\{\{state\}\}">p</figure-callout>}}_2,p_2)={\mathrm{<figure-callout\; id="4"\; label="b"\; filenames="HSA00000110791900041.png"\; state="\{\{state\}\}">b</figure-callout>}}_4+{\mathrm{\&beta;}}_2^{2}m+{\mathrm{\&beta;}}_3^2({\mathrm{<figure-callout\; id="1"\; label="p"\; filenames="HSA00000110791900041.png"\; state="\{\{state\}\}">p</figure-callout>}}_1,p_1)-2{\mathrm{\&beta;}}_2{b}_2-2{\mathrm{\&beta;}}_3{b}_5+2{\mathrm{\&beta;}}_1{\mathrm{\&beta;}}_3{\mathrm{<figure-callout\; id="2"\; label="b"\; filenames="HSA00000110791900041.png"\; state="\{\{state\}\}">b</figure-callout>}}_2$

$a_0=\frac{b_6}{(p_0,p_0)}$

$a_1=\frac{b_7-{\mathrm{\&beta;}}_1{b}_6}{({\mathrm{<figure-callout\; id="1"\; label="p"\; filenames="HSA00000110791900041.png"\; state="\{\{state\}\}">p</figure-callout>}}_1,p_1)}$

$a_2=\frac{b_8-{\mathrm{\&beta;}}_2{b}_6-{\mathrm{\&beta;}}_3({\mathrm{<figure-callout\; id="1"\; label="p"\; filenames="HSA00000110791900041.png"\; state="\{\{state\}\}">p</figure-callout>}}_1,I)}{({\mathrm{<figure-callout\; id="2"\; label="p"\; filenames="HSA00000110791900041.png"\; state="\{\{state\}\}">p</figure-callout>}}_2,p_2)}$

Wherein, (p ₀, p ₀), (p ₁, p ₁), (p ₂, p ₂) be the temporary variable in the computation process, β 1, and β 2, and β 3 is parameter to be asked, a0, a1, a2 is parameter to be asked.

Step 6, the orthogonalization model parameter is merged arrangement;

Particularly, will be changed to model as the orthogonalization model of step 1

F (x)=DC+Acos (Kx)+Bsin (Kx), wherein:

DC＝a ₀+β ₁β ₃a ₂-β ₁a ₁-β ₂a ₂

A＝a ₁-β ₃a ₂

B＝a ₂

Wherein, DC is a dark current, and A is a cosine coefficient, and B is a cosine coefficient, and β 1, and β 2, and β 3 is parameter to be asked.

The phase place of step 7, calculating orthogonalization model;

Promptly

Particularly,

$f\left(x\right)=\mathrm{DC}+A\cos \left(\mathrm{Kx}\right)+B\sin \left(\mathrm{Kx}\right)$

Aligned position is

Wherein A is a cosine coefficient, and B is a cosine coefficient.

Through emulation relatively, only find the solution 40% of symmetric matrix the working time of the technical scheme of the embodiment of the invention for present general square-root method.

In addition, the embodiment of the invention also provide a kind of based on the orthogonalization model from the axis signal treating apparatus.As shown in Figure 6, for the embodiment of the invention provide a kind of based on the orthogonalization model from axis signal treating apparatus synoptic diagram.

A kind of based on the orthogonalization model from the axis signal treating apparatus, comprise sampling module 11, the abbreviation processing module 22 that adds up, parameter acquisition module 33, phase calculation module 44.

Sampling module 11 is used to carry out off-axis alignment scanning, obtains position sampling signal and luminosity sampling signal;

Particularly, sampling module 11 also comprises a model determination module, and the orthogonalization model is f (x)=a ₀p ₀(x)+a ₁p ₁(x)+a ₂p ₂(x), (p0 (x), p1 (x), p2 (x)) is the function base of one group of quadrature in the formula, a0, and a1, a2 is parameter to be asked, wherein:

p ₀(x)＝1

p ₁(x)＝cos(Kx)-β ₁

p ₂(x)＝sin(Kx)-β ₂-β ₃p ₁(x)

K is known constant in this model, and β 1, and β 2, and β 3 is parameter to be asked, and x is that the change certainly in the function expression is heavy.

Sampling module 11 is used to carry out off-axis alignment scanning, obtains position sampling signal and luminosity sampling signal;

Particularly, (x _i, I _i) (i=0,1, L m) expression carries out in the off-axis alignment scanning process position sampling signal and the luminosity sampling signal of the some groups of correspondences that sampling obtains.

The abbreviation processing module 22 that adds up is used for the sampled signal abbreviation that adds up is in real time handled;

Particularly, to each group sampled signal (x _i, I _i) (i=0,1, Lm) (the position sampling signal and the luminosity sampling signals of the some groups of correspondences that sampling obtains in the off-axis alignment scanning process), m represents total sampling number, order

C _n＝cos(Kx _n)

S _n＝sin(Kx _n)

Add up and obtain following parameters:

b ₁＝∑C _n

b ₂＝∑S _n

${\mathrm{<figure-callout\; id="3"\; label="b"\; filenames="HSA00000110791900041.png"\; state="\{\{state\}\}">b</figure-callout>}}_3={\mathrm{\&Sigma;<figure-callout\; id="2"\; label="C\; n"\; filenames="HSA00000110791900041.png"\; state="\{\{state\}\}">C</figure-callout>}}_n^{}$

${\mathrm{<figure-callout\; id="4"\; label="b"\; filenames="HSA00000110791900041.png"\; state="\{\{state\}\}">b</figure-callout>}}_4={\mathrm{\&Sigma;<figure-callout\; id="2"\; label="S\; n"\; filenames="HSA00000110791900041.png"\; state="\{\{state\}\}">S</figure-callout>}}_n^{}$

b ₅＝∑S _nC _n

b ₆＝∑I _n

b ₇＝∑I _nC _n

b ₈＝∑I _nS _n

b ₁=∑ C _nSummation adds up behind the position data complementation string that expression obtains all samplings.

Wherein Xi (i=0,1 ... m) be the position sampling signal, Ii (i=0,1 ... m) be the luminosity sampling signal, Cn, Sn, b1～b8 are the temporary variable in the computation process.

Parameter acquisition module 33 is used to obtain the orthogonalization model parameter;

Particularly, parameter acquisition module 33 also comprises a judge module, and described judge module is used to judge whether be last group sampling;

Particularly, not last group sampling as judged result, then continue sampling, be last group sampling as judged result, illustrate then that sampling parameter is all sampled to finish.

Whether be that last group sampling is judged in the following way: before off-axis alignment scanning, can specify sampling number, count when reaching preassigned sampling number, can think last group sampling when actual samples.

Parameter acquisition module is obtained the orthogonalization model parameter;

Particularly, utilize the abbreviation result (being b1-b8) that adds up, obtain the parameter a of orthogonalization model ₀, a ₁, a ₂, the specific algorithm formula is:

(p ₀，p ₀)＝m

${\mathrm{\&beta;}}_1=\frac{b_1}{m}$

$({\mathrm{<figure-callout\; id="1"\; label="p"\; filenames="HSA00000110791900041.png"\; state="\{\{state\}\}">p</figure-callout>}}_1,p_1)=b_3-2{\mathrm{\&beta;}}_1{\mathrm{<figure-callout\; id="1"\; label="b"\; filenames="HSA00000110791900041.png"\; state="\{\{state\}\}">b</figure-callout>}}_1+{\mathrm{\&beta;}}_1^{2}m$

${\mathrm{\&beta;}}_2=\frac{b_2}{m}$

${\mathrm{\&beta;}}_3=\frac{b_5-{\mathrm{\&beta;}}_1{b}_2}{({\mathrm{<figure-callout\; id="1"\; label="p"\; filenames="HSA00000110791900041.png"\; state="\{\{state\}\}">p</figure-callout>}}_1,p_1)}$

$({\mathrm{<figure-callout\; id="2"\; label="p"\; filenames="HSA00000110791900041.png"\; state="\{\{state\}\}">p</figure-callout>}}_2,p_2)={\mathrm{<figure-callout\; id="4"\; label="b"\; filenames="HSA00000110791900041.png"\; state="\{\{state\}\}">b</figure-callout>}}_4+{\mathrm{\&beta;}}_2^{2}m+{\mathrm{\&beta;}}_3^2({\mathrm{<figure-callout\; id="1"\; label="p"\; filenames="HSA00000110791900041.png"\; state="\{\{state\}\}">p</figure-callout>}}_1,p_1)-2{\mathrm{\&beta;}}_2{b}_2-2{\mathrm{\&beta;}}_3{b}_5+2{\mathrm{\&beta;}}_1{\mathrm{\&beta;}}_3{\mathrm{<figure-callout\; id="2"\; label="b"\; filenames="HSA00000110791900041.png"\; state="\{\{state\}\}">b</figure-callout>}}_2$

$a_0=\frac{b_6}{(p_0,p_0)}$

$a_1=\frac{b_7-{\mathrm{\&beta;}}_1{b}_6}{({\mathrm{<figure-callout\; id="1"\; label="p"\; filenames="HSA00000110791900041.png"\; state="\{\{state\}\}">p</figure-callout>}}_1,p_1)}$

$a_2=\frac{b_8-{\mathrm{\&beta;}}_2{b}_6-{\mathrm{\&beta;}}_3({\mathrm{<figure-callout\; id="1"\; label="p"\; filenames="HSA00000110791900041.png"\; state="\{\{state\}\}">p</figure-callout>}}_1,I)}{({\mathrm{<figure-callout\; id="2"\; label="p"\; filenames="HSA00000110791900041.png"\; state="\{\{state\}\}">p</figure-callout>}}_2,p_2)}$

Wherein, (p ₀, p ₀), (p ₁, p ₁), (p ₂, p ₂) be the temporary variable in the computation process, β 1, and β 2, and β 3 is parameter to be asked.

Phase calculation module 44 is used to calculate the phase place of orthogonalization model;

Particularly, phase calculation module 44 comprises that also a parameter merges sorting module, is used for the orthogonalization model parameter is merged arrangement;

Particularly, will be changed to model as the orthogonalization model of step 1

F (x)=DC+Acos (Kx)+Bsin (Kx), wherein:

DC＝a ₀+β ₁β ₃a ₂-β ₁a ₁-β ₂a ₂

A＝a ₁-β ₃a ₂

B＝a ₂

Wherein, DC is a dark current, and A is a cosine coefficient, and B is a cosine coefficient, and β 1, and β 2, and β 3 is parameter to be asked.

The phase calculation module is used to calculate the phase place of orthogonalization model;

Promptly

Wherein A is a cosine coefficient, and B is a cosine coefficient.

Particularly,

$f\left(x\right)=\mathrm{DC}+A\cos \left(\mathrm{Kx}\right)+B\sin \left(\mathrm{Kx}\right)$

Aligned position is

Through emulation relatively, only find the solution 40% of symmetric matrix the working time of the technical scheme of the embodiment of the invention for present general square-root method.

The embodiment of the invention also further provide a kind of based on the orthogonalization model from the axis signal disposal system, comprise the foregoing description described based on the orthogonalization model from the axis signal treating apparatus, specify and see the foregoing description for details, repeat no more herein.

One of ordinary skill in the art will appreciate that and realize that all or part of step that the foregoing description method is carried is to instruct relevant hardware to finish by program, described program can be stored in a kind of computer-readable recording medium, this program comprises one of step or its combination of method embodiment when carrying out.

In addition, each functional unit in each embodiment of the present invention can be integrated in the processing module, also can be that the independent physics in each unit exists, and also can be integrated in the module two or more unit.Above-mentioned integrated module both can adopt the form of hardware to realize, also can adopt the form of software function module to realize.If described integrated module realizes with the form of software function module and during as independently production marketing or use, also can be stored in the computer read/write memory medium.

In sum, this paper provides a kind of off-axis signal treatment method based on the orthogonalization model, Apparatus and system, by determining an orthogonalization model and obtaining the position sampling signal and the luminosity sampling signal, and the sampled signal abbreviation that adds up handled, so that the accurate fast phase place of determining registration signal, thereby finally determine its aligned position.

More than a kind of off-axis signal treatment method based on the orthogonalization model provided by the present invention, Apparatus and system are described in detail, used specific case herein principle of the present invention and embodiment are set forth, the explanation of above embodiment just is used for helping to understand the solution of the present invention; Simultaneously, for one of ordinary skill in the art, according to thought of the present invention, the part that all can change in specific embodiments and applications, in sum, this description should not be construed as limitation of the present invention.

Claims (14)

1. the off-axis signal treatment method based on the orthogonalization model is characterized in that, described off-axis signal treatment method comprises:

Step 1, determine the orthogonalization model;

Step 2, carry out off-axis alignment scanning, obtain position sampling signal and luminosity sampling signal;

Step 3, position sampled signal and the luminosity sampling signal abbreviation that adds up is in real time handled;

Step 4, judge whether to be last group sampling;

Step 5, the abbreviation result that adds up is found the solution, obtain the orthogonalization model parameter;

Step 6, the orthogonalization model parameter is merged arrangement;

The phase place of step 7, calculating orthogonalization model.

2. off-axis signal treatment method according to claim 1 is characterized in that, the orthogonalization model of described step 1 is: f (x)=a ₀p ₀(x)+a ₁p ₁(x)+a ₂p ₂(x), (p0 (x), p1 (x), p2 (x)) is the function base of one group of quadrature in the formula, a0, and a1, a2 is parameter to be asked, wherein:

p ₀(x)＝1

p ₁(x)＝cos(Kx)-β ₁

p ₂(x)＝sin(Kx)-β ₂-β ₃p ₁(x)

K is known constant in this model, and β 1, and β 2, and β 3 is parameter to be asked, and x is the independent variable in the function expression.

3. off-axis signal treatment method according to claim 1 is characterized in that, in described step 3, the sampled signal abbreviation that adds up in real time is treated to each group sampled signal (x _i, I _i) (i=0,1, Lm), m represents total sampling number, order

C _n＝cos(Kx _n)

S _n＝sin(Kx _n)

Add up and obtain following parameters:

b ₁＝∑C _n

b ₂＝∑S _n

$b_3=\mathrm{\&Sigma;}{C}_n^2$

$b_4=\mathrm{\&Sigma;}{S}_n^2$

b ₅＝∑S _nC _n

b ₆＝∑I _n

b ₇＝∑I _nC _n

b ₈＝∑I _nS _n；

X wherein _iBe position sampling signal, I _iBe the luminosity sampling signal, Cn, Sn, b1～b8 are the temporary variable in the computation process.

4. off-axis signal treatment method according to claim 1 is characterized in that, in the described step 4, described judgment mode is last and organizes sampled point when equaling default sampling number when the position sampling signal of actual samples and luminosity sampling signal.

5. off-axis signal treatment method according to claim 3 is characterized in that, in described step 5, obtains the parameter a of above-mentioned orthogonalization model ₀, a ₁, a ₂, the specific algorithm formula is:

(p ₀，p ₀)＝m

${\mathrm{\&beta;}}_1=\frac{b_1}{m}$

$(p_1,p_1)=b_3-2{\mathrm{\&beta;}}_1{b}_1+{\mathrm{\&beta;}}_1^{2}m$

${\mathrm{\&beta;}}_2=\frac{b_2}{m}$

${\mathrm{\&beta;}}_3=\frac{b_5-{\mathrm{\&beta;}}_1{b}_2}{(p_1,p_1)}$

$(p_2,p_2)=b_4+{\mathrm{\&beta;}}_2^{2}m+{\mathrm{\&beta;}}_3^2(p_1,p_1)-2{\mathrm{\&beta;}}_2{b}_2-2{\mathrm{\&beta;}}_3{b}_5+2{\mathrm{\&beta;}}_1{\mathrm{\&beta;}}_3{b}_2$

$a_0=\frac{b_6}{(p_0,p_0)}$

$a_1=\frac{b_7-{\mathrm{\&beta;}}_1{b}_6}{(p_1,p_1)}$

$a_2=\frac{b_8-{\mathrm{\&beta;}}_2{b}_6-{\mathrm{\&beta;}}_3(p_1,I)}{(p_2,p_2)}$

Wherein, (p0, p0), (p1, p1), (p2 p2) is temporary variable in the computation process, and β 1, and β 2, and β 3 is parameter to be asked, a0, and a1, a2 is parameter to be asked.

6. off-axis signal treatment method according to claim 1 is characterized in that, in described step 6 the orthogonalization model parameter is merged arrangement, and specific algorithm is as follows:

DC＝a ₀+β ₁β ₃a ₂-β ₁a ₁-β ₂a ₂

A＝a ₁-β ₃a ₂

B＝a ₂

Wherein, DC is a dark current, and A is a cosine coefficient, and B is a cosine coefficient, and β 1, and β 2, and β 3 is parameter to be asked.

7. off-axis signal treatment method according to claim 1 is characterized in that, the phase place of orthogonalization model is as follows in described step 7:

Wherein A is a cosine coefficient, and B is a cosine coefficient.

One kind based on the orthogonalization model from the axis signal treating apparatus, it is characterized in that, described from the axis signal treating apparatus comprise sampling module, the abbreviation processing module that adds up, parameter acquisition module, phase calculation module, the described abbreviation processing module that adds up, being used for sampled signal to the sampling module abbreviation that adds up in real time handles, and result is transferred to parameter acquisition module, the phase calculation module is used for calculating according to the orthogonalization model parameter phase place of orthogonalization model.

9. according to claim 8ly it is characterized in that from the axis signal treating apparatus described sampling module also comprises a model determination module, the orthogonalization model is f (x)=a ₀p ₀(x)+a ₁p ₁(x)+a ₂p ₂(x), (p0 (x), p1 (x), p2 (x)) is the function base of one group of quadrature in the formula, a0, and a1, a2 is parameter to be asked, wherein:

p ₀(x)＝1

p ₁(x)＝cos(Kx)-β ₁

p ₂(x)＝sin(Kx)-β ₂-β ₃p ₁(x)

K is known constant in this model, and β 1, and β 2, and β 3 is parameter to be asked, and x is the independent variable in the function expression.

10. according to claim 8ly it is characterized in that the described abbreviation processing module that adds up is used for sampled signal to the sampling module abbreviation that adds up in real time and handles, to each group sampled signal (x from the axis signal treating apparatus _i, I _i) (i=0,1, Lm), m represents total sampling number, order

C _n＝cos(Kx _n)

S _n＝sin(Kx _n)

Add up and obtain following parameters:

b ₁＝∑C _n

b ₂＝∑S _n

$b_3=\mathrm{\&Sigma;}{C}_n^2$

$b_4=\mathrm{\&Sigma;}{S}_n^2$

b ₅＝∑S _nC _n

b ₆＝∑I _n

b ₇＝∑I _nC _n

b ₈＝∑I _nS _n，

X wherein _i(i=0,1 ... m) be the position sampling signal, I _i(i=0,1 ... m) be the luminosity sampling signal, Cn, Sn, b1～b8 are the temporary variable in the computation process.

11. according to claim 10ly it is characterized in that from the axis signal treating apparatus described parameter acquisition module is used to obtain orthogonalization model parameter a ₀, a ₁, a ₂, concrete formula is:

(p ₀，p ₀)＝m

${\mathrm{\&beta;}}_1=\frac{b_1}{m}$

$(p_1,p_1)=b_3-2{\mathrm{\&beta;}}_1{b}_1+{\mathrm{\&beta;}}_1^{2}m$

${\mathrm{\&beta;}}_2=\frac{b_2}{m}$

${\mathrm{\&beta;}}_3=\frac{b_5-{\mathrm{\&beta;}}_1{b}_2}{(p_1,p_1)}$

$(p_2,p_2)=b_4+{\mathrm{\&beta;}}_2^{2}m+{\mathrm{\&beta;}}_3^2(p_1,p_1)-2{\mathrm{\&beta;}}_2{b}_2-2{\mathrm{\&beta;}}_3{b}_5+2{\mathrm{\&beta;}}_1{\mathrm{\&beta;}}_3{b}_2$

$a_0=\frac{b_6}{(p_0,p_0)}$

$a_1=\frac{b_7-{\mathrm{\&beta;}}_1{b}_6}{(p_1,p_1)}$

$a_2=\frac{b_8-{\mathrm{\&beta;}}_2{b}_6-{\mathrm{\&beta;}}_3(p_1,I)}{(p_2,p_2)}$

Wherein, (p ₀, p ₀), (p ₁, p ₁), (p2 p2) is temporary variable in the computation process, and β 1, and β 2, and β 3 is parameter to be asked.

12. according to claim 8ly it is characterized in that described phase calculation module comprises that also a parameter merges sorting module from the axis signal treating apparatus, be used for the orthogonalization model parameter is merged arrangement, concrete formula is:

DC＝a ₀+β ₁β ₃a ₂-β ₁a ₁-β ₂a ₂

A＝a ₁-β ₃a ₂

B＝a ₂

Wherein, DC is a dark current, and A is a cosine coefficient, and B is a cosine coefficient, and β 1, and β 2, and β 3 is parameter to be asked.

13. according to claim 8ly it is characterized in that from the axis signal treating apparatus described phase calculation module is used to calculate the phase place of orthogonalization model,

Promptly

Wherein A is a cosine coefficient, and B is a cosine coefficient.

14. one kind based on the orthogonalization model from the axis signal disposal system, it is characterized in that, comprise as claim 8 to 13 any one described from the axis signal treating apparatus.

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