Abstract:
A wavefront measuring system and method for detecting phase aberrations in wavefronts that are reflected from, transmitted through or internally reflected within objects sought to be measured, e.g., optics systems, the human eye, etc. includes placing a reticle in the path of a return beam from the object, and placing a detector at a diffraction pattern self-imaging plane relative to the reticle. The diffraction pattern is analyzed and results in a model of the wavefront phase characteristics. A set of known polynomials is fitted to the wavefront phase gradient to obtain polynomial coefficients that describe aberrations in the object or within the wavefront source being measured.

Description:
FIELD OF THE INVENTION 
     The present invention relates generally to systems and methods for measuring phase characteristics of electromagnetic wavefronts. 
     BACKGROUND 
     Measuring how a wavefront deviates from perfectly diffraction-limited has many applications. As non-limiting examples, measuring deviations, also referred to as “aberrations”, in a wavefront produced by an optical system, such as a telescope, can reveal manufacturing flaws in the system, since many optical systems, to function as best as is possible, must produce perfectly diffraction-limited wavefronts. By adding a component to the system that produces a wavefront that is the conjugate of the measured deviations, the system can be made to produce a more diffraction-limited wavefront and, thus, diffraction-limited performance (i.e., best possible performance). 
     Another example of an application where knowing the aberrations in a wavefront is useful is in correcting human vision. For instance, as noted in U.S. Pat. No. 5,963,300, by measuring deviations from the perfectly spherical in reflections of laser light from the eye of a patient, aberrations of the eye can be measured and, hence, compensated for. In the &#39;300 patent, light that is reflected from a patient&#39;s eye is passed through two reticles, and the resulting moiré shadow pattern is presented on a screen. An imaging system images the shadow on the screen onto a camera, with subsequent analysis being undertaken of the imaged shadow. The technique of the &#39;300 patent is based on geometrical or ray-tracing analysis, which as recognized herein requires theoretical assumptions to perform the geometrical analysis that limit the amplitude of the aberrations that can be measured as well as limit the accuracy with which the aberrations can be measured. 
     With these drawbacks in mind, the present invention provides the solutions below to one or more of them. 
     SUMMARY OF THE INVENTION 
     A system for determining aberrations in a coherent electromagnetic wavefront includes a reticle that is positioned in the path of the wavefront, and a detector is also positioned in the path. In accordance with this aspect, the light detector is located at a diffraction pattern self-imaging plane relative to the reticle. 
     A processor receives the output signal from the light detector and determines aberrations in the beam based thereon. The aberrations in the beam represent aberrations in the wavefront due to the medium through which it passes, or an object from which it reflects, or the source of the wavefront itself. 
     In a preferred, non-limiting embodiment, the processor executes logic that includes determining a phase gradient of the wavefront phase-front, and determining coefficients of polynomials based on the phase-front gradient which quantify the aberrations. The coefficients represent aberrations. Preferably, the gradient is obtained from a frequency domain transformation of the beam, such that the gradient is the derivatives of phases of the wavefront in directions established by the reticle orientation. In a particularly preferred, non-limiting embodiment, the derivatives are determined in at least two directions, and the coefficients are determined by fitting derivatives of a set of known polynomials to the measured gradient. 
     In another aspect, a method for determining aberrations in an object includes passing a light beam from the object through a reticle, and then determining derivatives that are associated with the light beam subsequent to the light beam passing through the reticle. Using the derivatives, a measure of aberrations in the object can be output. 
     In yet another aspect, a computer program product includes a computer readable medium having a program of instructions stored thereon for causing a digital processing apparatus to execute method steps for determining aberrations in an object. The product includes means for receiving a representation of a wavefront propagating into the apparatus, and means for determining wavefront aberrations of the representation. Means are provided for fitting the derivatives to known polynomials or derivatives thereof to obtain coefficients of polynomials. The product includes means for outputting a wavefront characterization based at least in part on the coefficients, with the signal representing aberrations in the object. 
     In still another aspect, an apparatus for detecting aberrations in an object as manifested in a wavefront includes a reticle positioned in a path of the wavefront and a light detector positioned relative to the reticle to receive the diffracted self-image that is associated with the wavefront. The self-imaging distances are at discrete distances from the reticle that are integral multiples of, where p is the period of the reticle and the λ is the spectral wavelength of the wavefront. A processor receives signals from the light detector that represent the self-image. The processor derives the wavefront phase gradient associated with the wavefront and uses the coefficients of derivatives of polynomials that define the wavefront to determine the wavefront aberrations. 
     The details of the present invention, both as to its structure and operation, can best be understood in reference to the accompanying drawings, in which like reference numerals refer to like parts, and in which: 
    
    
     BRIEF DESCRIPTION OF THE DRAWINGS 
     FIG. 1 is a block diagram of the present system architecture; 
     FIG. 1 a  is a block diagram of a more detailed implementation of the system shown in FIG. 1; 
     FIG. 2 is a flow chart of the overall logic of the invention; 
     FIG. 3 is a flow chart of the logic for data extraction in the spatial frequency domain; and 
     FIG. 4 is a flow chart of further logic for extraction of the desired data from spatial frequency data. 
    
    
     DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT 
     Referring initially to FIG. 1, a wavefront sensor is shown, generally designated  10 . As shown in FIG. 1, a reference wavefront  11  can pass through (or, be reflected from) a transfer (optical or otherwise) system or element  12 . The system or element  12  can be an optics system, such as a telescope system, or it can be a human eye, or other object having aberrations sought to be measured. 
     As shown in FIG. 1, a transferred wavefront  18 , i.e., the wavefront  11  after having passed through or having been reflected from the system or element  12 , passes through a reticle  20 . The reticle  20  diffracts the wavefront  18 , and the diffracted wavefront self-images onto a sensor plane a self-imaging distance “d” away from the reticle  20 , at which location is disposed a light sensor  22  such as but not limited to a CCD. The self-imaging distance “d” is dependent on the spectral wavelength of the coherent wavefront and the spatial frequency of the reticle. 
     In a non-limiting, exemplary embodiment, the wavefront incident on the imaging detector can be represented by the following diffraction equation:                I        (       r   ϖ     ,   z     )       =       I   o          cos        (       πλ                 z       p   2       )            cos   [         2      π     p          (         r   ρ     ·     p   ^       -       r   ^     ·     (       z   ρ                   X                     ∇   ρ        w       )         ]                   (   1   )                                
     wherein λ is the wavelength of the coherent wavefront, z is the propagation distance, p is the period of the reticle (distance from the beginning of one grid line to the next grid line), r is the spatial dimension in the plane of the detector with its associated vector, {circumflex over (r)} is the unit vector, {circumflex over (p)} the unit vector representing the reticle orientation, and ∇ is the directional—derivative (or, gradient) of the wavefront phase “w” that is being measured. The self-imaging distance is dependent on the spectral wavelength of the coherent wavefront and the spatial frequency of the reticle is given by:              d   =     (       np   2     λ     )             (   2   )                                
     where n is the integer multiple at which distances the self-images occurs. 
     Accordingly, the self-imaged reticle on the light sensor or detector  22  that is located at the self-image plane contains the desired information pertaining to the phase characteristics of the coherent wavefront. This information is extracted from the spatial signal collected at the sensor  22  and sent to a data processor (i.e., computer)  24  for processing in accordance with the disclosure below. To undertake the present logic, the processor  24  accesses a preferably software-implemented module  26 , and outputs a signal representative of the wavefront (or a conjugate thereof) to an output device  28 , such as but not limited to a printer, monitor, computer, network, or other appropriate output device. 
     In accordance with present principles, the beam that emerges from the reticle  20  establishes a diffraction pattern. This pattern, however, substantially cannot be discerned except at the self-image planes that are spaced integer multiples of a distance “d” from the reticle  20 , as discussed above. Thus, the self image of the diffusion pattern can be detected by the light sensor or detector  22  that in one preferred embodiment is placed at the first (n=1) self-image plane as shown in FIG. 1, although it is to be understood that the sensor or detector  22  can be positioned at any of the self-image planes that are spaced from the reticle  20  by integer multiples of the distance “d”. 
     It is to be understood that the present logic is executed on the architecture shown in FIG. 1 in accordance with some or all of the blocks in the flow chart of FIG. 2, which illustrates the structure of the logic of the present invention as embodied in computer program software. Those skilled in the art will appreciate that the flow charts illustrate the structures of logic elements, such as computer program code elements or electronic logic circuits, that function according to this invention. Manifestly, the invention is practiced in its essential embodiment by a machine component that renders the logic elements in a form that instructs a digital processing apparatus (that is, a computer, controller, processor, etc.) to perform a sequence of function steps corresponding to those shown. 
     In other words, the logic may be embodied by a computer program that is executed by the processor  24  as a series of computer- or control element-executable instructions. These instructions may reside, for example, in RAM or on a hard drive or optical drive, or the instructions may be stored on magnetic tape, electronic read-only memory, or other appropriate data storage device that can be dynamically changed or updated. 
     FIG. 1 a  shows a particular non-limiting implementation of the system  10  in which the electromagnetic energy is reflected from an object or is internally reflected from within an object. Examples of applications include microwave topography of large surfaces, wherein the electromagnetic energy is microwave and the object is the surface sought to be measured; optical topography of reflective surfaces, wherein the electromagnetic energy is laser light; retinal reflection within an eye in order to measure the aberrations of the eye, and gamma ray reflection within very small objects in order to characterize mechanical or optical properties. 
     Accordingly, for illustration purposes FIG. 1 a  shows that the reference wavefront  11  passes through (or, is reflected from) a transfer (optical or otherwise) system or element  15 , such as but not limited to a beamsplitter, along a propagation path  13 . The wavefront  11  is incident on an object  12  such as a human eye wherein it is either reflected externally or transmits into the object  12  where it is internally reflected. The return wavefront follows along a return path  17 , and can be reflected from or transmitted through the system or element  15 . The wavefront may then pass through an optical relay system  19 . The transferred wavefront  18  passes through the reticle  20  and is processed as described above in reference to FIG.  1 . 
     The logic of the processor  24  can be appreciated in reference to FIG.  2 . Commencing at block  30  in FIG. 2, the wavefront  18  of the beam passes through the reticle  20 . Diffraction effects cause a self-image of the reticle to appear at the self-image planes described above, including at the first plane located at a distance “d” from the reticle  20  where the detector  22  is positioned. The particular plane chosen for the position of the detector  22  should have sufficient resolution cells to resolve the diffraction pattern. 
     The self-image of the diffraction pattern caused by the beam  18  passing through the reticle  20  is acquired at block  33  by the sensor or detector  22  and is represented by the signal output by the light detector  22 , as received by the processor  24 . Proceeding to block  34 , the signal in the spatial image domain is transformed to the spatial frequency domain. In one non-limiting embodiment, executing a Fast Fourier Transform (FFT) on the signal performs this, although it is to be understood that other mathematical transformations can be used. While FIG. 2 indicates that the FFT is implemented in software, it is to be understood by those skilled in the art that alternatively, prior to being sent to the processor  24  an optical FFT of the return beam can be made using optics known in the art. 
     Proceeding to block  36 , regions of interest in the frequency domain are selected based on reticle period and other factors discussed further below. This selection can be a priori, and need not be undertaken during measurement. Essentially, at block  36  the regions of interest for which gradient (directional derivative) of the wavefront is to be determined are located in the spatial frequency domain and isolated. 
     In the preferred embodiment, the portions of the spatial frequency domain that contain the slope information and that consequently are isolated depend on the configuration of the reticle  22  and can be, e.g., represented by orthogonal axes of the FFT. This spatial frequency domain manipulation is further illustrated in FIG. 3, discussed below. 
     Proceeding to block  38 , an inverse transform is applied only to the isolated regions of the signal to render a spatial representation of the gradient of the wavefront in the direction normal to the linear or segmented linear dimension of the reticle. Thus, if the reticle contains a singular set of linear grating lines, there will be two regions of the spatial frequency domain containing the desired information. If there are two sets of linear gratings superimposed in the reticle, the spatial frequency domain will contain four regions of interest. Each additional set of linear gratings provides more information pertaining to the wavefront gradient. In the limit, a circular grating reticle represents an infinite number of segmented linear gratings superimposed on each other. Preferably, the reticle contains two orthogonal superimposed linear grating patterns. In a non-limiting preferred embodiment, the wavefront gradient is determined in isolated regions in two directions. In a non-limiting example, when the object  12  is a human eye, the two directions are orthogonal to each other and lie in a plane defined by the front of and tangential to the patient&#39;s eye, with one of the directions extending from the center of the eye at a 45° angle relative to the horizontal and tangent to the eye when the patient is standing and facing directly forward. 
     If desired, in a non-limiting embodiment filtering of random background noise can be further effected by using a “computationally-implemented” matte screen by which the spatial characteristics of the self-image are enhanced and the background reduced to very low (i.e., zero) frequency components in the spatial frequency domain. This principle will be further discussed in relation to FIG.  4 . 
     Moving to block  40 , a set of known functions such as polynomials (and their derivatives) is defined or otherwise accessed for the two directions mentioned above. These polynomials can be used to model the wavefront. In one preferred, non-limiting embodiment, a set of 36 Zernike polynomials are used. Then, at block  42  the derivatives of the known polynomials are fit to the derivatives (i.e., gradient) determined at block  38  using, e.g., a least squares fit or other fitting algorithm. 
     The outcome of the fitting step at block  42  is that each polynomial has an accompanying coefficient, also referred to as the “amplitude” of the polynomial. Each coefficient represents an aberration from the perfectly spherical in the return beam  18  and, hence, an aberration in the object  12 . Consequently, at block  44  a reconstructed wavefront equation can be output (to, e.g., the output device  28 ) that is the set of the known polynomials with the coefficients obtained in the fitting step at block  42 . At block  46 , the output, and in particular the coefficients in the reconstructed wavefront equation, can be used to indicate aberrations in the original wavefront and, hence, in the object  12 . Furthermore, the output can be used as a basis for implementing corrective optics for the system  12  that essentially represent the conjugate of the polynomials and/or coefficients to null out the aberrations of the object  12 . 
     Now referring to FIG. 3, which shows further details of blocks  34 ,  36  and  38  in FIG. 2, at block  50  the self-image of the reticle is converted in software or optically from spatial data to spatial frequency data. As discussed above, this is preferably performed with a Fourier Transform algorithm and preferably the Fast Fourier Transform computer software algorithm (FFT). Moving to block  52 , from an a priori knowledge of the system  10  configuration, regions of interest in the spatial frequency domain are selected. The a priori information is provided at block  54  as follows. The reticle  20  has (a) periodic pattern(s) in known directions. The period of the reticle, the number of superimposed reticles, and the spatial orientations of the reticle relative to the wavefront path of propagation are needed to locate these regions. Gradiant data in the individual regions of interest is accessed at block  56  and isolated at block  58 . This data has symmetry in the spatial frequency domain. Accordingly, in block  60  if desired only one of the symmetric data sets need be selected. Then in block  62  each set is converted back to the spatial domain. This data is then passed to block  38  in FIG.  2 . 
     The above operations by which the wave front is extracted from equation (1) can be expressed in analytical form as follows. First, the non-limiting Fourier transform on the wavefront executed at block  50  in FIG. 3 can be expressed as                F        {     I        (     r   ,   z     )       }                fx   ,   y2               fx   ,   y1             ,             fx   ,   y4               fx   ,   y3           ⇒       F        (     σ                 w     )       .               (   3   )                                
     Wherein the two spatial frequency regions f x,y1  to f x,y2  and f x,y3  to f x,y4  are the two dimensional areas in the frequency domain that contain the relevant data, and F (σw) represents the received wavefront. 
     Then, the gradient (σw) of the wavefront is determined at block  56  by performing the inverse Fourier transform (F −1 ) on equation (3) as follows: 
     
       
           F   −1   {F (σ w ).}→σ w.   (4) 
       
     
     Next, the set of partial derivatives, or gradients, of the chosen polynomial set, e.g., Zernike polynomials (σZ, or Z x  and Z y ) are made to best approximate the gradient of the phase front (σw) at block  42  of FIG. 2 via any algorithm such as a least squares algorithm which is well know in the art. That is,                  σ                 w     =       ∑     i   =   1     n            A   i        σ                   Z   i           ,           (   5   )                                
     wherein n is the number of polynomials chosen to best approximate the wavefront phase gradient, and A i  is the coefficient, or amplitude, of the polynomial Z i . The wavefront phase “w” can now be described as follows:              w   =       ∑     i   =   1     n            A   i                       Z   i     .                 (   6   )                                
     The aberrations in the wavefront can be described by the values of the coefficients Ai. 
     The flow chart of FIG. 4 shows the process of the “computationally-implemented” matte screen discussed above in relation to FIG.  2 . Typically, in a monochromatic system a high pass spectral filter is used to eliminate signal noise. This is a piece of hardware called a matte screen. In many applications a matte screen is not practical to integrate into the system. Accordingly, the matte screen can be computationally implemented on the self-images. 
     The contrast of the image and the self-image fundamental spatial frequency are respectively received from blocks  70  and  71  and input to block  72 , where the two inputs are compared to discriminate the self-image signal. If the contrast from block  70  is lower than the fundamental spatial frequency from block  71 , the matte screen is implemented within block  34  of FIG. 2, with the location of the peak value in the region of interest in block  38  providing the fundamental (predominant) frequency within the self-image signal. From the peak, a finite impulse response (FIR) kernel is derived at block  74  that functions as a high-pass filter of spatial frequency data. Only frequencies higher then the designed limit will remain in the signal, and all others are eliminated at block  76  by mathematically convolving the kernal with the self-image signal. 
     While the particular SYSTEM AND METHOD FOR WAVEFRONT MEASUREMENT as herein shown and described in detail is fully capable of attaining the above-described objects of the invention, it is to be understood that it is the presently preferred embodiment of the present invention and is thus representative of the subject matter which is broadly contemplated by the present invention, that the scope of the present invention fully encompasses other embodiments which may become obvious to those skilled in the art, and that the scope of the present invention is accordingly to be limited by nothing other than the appended claims, in which reference to an element in the singular is not intended to mean “one and only one” unless explicitly so stated, but rather “one or more”. All structural and functional equivalents to the elements of the above-described preferred embodiment that are known or later come to be known to those of ordinary skill in the art are expressly incorporated herein by reference and are intended to be encompassed by the present claims. Moreover, it is not necessary for a device or method to address each and every problem sought to be solved by the present invention, for it to be encompassed by the present claims. Furthermore, no element, component, or method step in the present disclosure is intended to be dedicated to the public regardless of whether the element, component, or method step is explicitly recited in the claims. No claim element herein is to be construed under the provisions of 35 U.S.C. §112, sixth paragraph, unless the element is expressly recited using the phrase “means for” or, in the case of a method claim, the element is recited as a “step” instead of an “act”.