Abstract:
A method for identifying and determining the frequency of scattered radiation fringe patterns for applications such as particle or droplet sizing and laser Doppler velocimetery. The method utilizes a series of windowed Fourier transforms performed on an intensity profile of the scattered radiation to locate a segment where a fringe pattern is located on the intensity profile. A standard Fourier transform is then performed on the segment to determine a dominant frequency of the fringe pattern, from which a physical quantity such as diameter or velocity of the particle or droplet may be derived. The method may be utilized with a line or an array sensor to measure the fringe patterns in a spatial domain, or with a point detector to measure the fringe patterns in the time domain.

Description:
RELATED APPLICATION 
   This application claims benefit of U.S. Provisional Application Ser. No. 60/713,790, filed Sep. 1, 2005, which is hereby fully incorporated herein by reference. 

   FIELD OF THE INVENTION 
   The present invention relates to systems and processes for analyzing fringe patterns or oscillation patterns derived from scattered coherent energy, and more particularly to an apparatus and method for analyzing the fringe patterns presented by moderate to high density target population fields. The apparatus and method hereof are particularly well suited for measuring the physical characteristics of airborne particles and droplets based on the frequency or spacing of interference fringes. 
   BACKGROUND OF THE INVENTION 
   A variety of particle and droplet characterizing techniques involve the analysis of fringe patterns or oscillation patterns scattered by an irradiated particle or droplet. For example, interferometric particle sizing is based on the interference of laser energy reflected and refracted from transparent spherical particles. The angular spacing of the interference fringes is inversely proportional to the droplet diameter. 
   Some interferometric particle sizing systems utilize a sheet-shaped laser beam that is applied to a measurement space, and out-of-focus images of droplets irradiated with the laser beam are captured. A known method for fringe pattern analysis in the out-of-focus images involves the so-called “edge detection” technique. The out-of-focus image corresponding to each droplet is distinguished and extracted from the original image by detecting the edge of the fringe pattern. Since the relationship between the angular spacing of the fringe pattern and the diameter of the droplet is known, the diameter of the droplet is determined by counting the number of interference fringes in the extracted fringe pattern. 
   U.S. Pat. No. 6,587,208 to Maeda, et al. (Maeda) discloses an improvement on the edge detection technique. The Maeda method calls for the use of a cylindrical lens to compress an otherwise disk-shaped fringe pattern into a line oscillation pattern without significantly altering the spacing of the fringes. The line oscillation pattern enables the use of a low-pass filter to convert the oscillation pattern to a one-dimensional Gaussian pattern, from which individual fringe patterns can be distinguished and extracted. Maeda also discloses the use of a fast Fourier transform to establish the number of fringes in an extracted fringe pattern. 
   Another technique that may involve fringe pattern analysis is laser Doppler velocimetry (LDV). Particles pass through a viewing volume determined by the intersection of two laser beams. Light scattered by the particles passing through the viewing volume is detected, and the particle velocity, which is inversely proportional to the frequency of the scattered fringe pattern, is determined. 
   A problem arises with the aforementioned sizing and velocity techniques when the population density of a particle or droplet field is high enough to cause frequent overlapping of corresponding fringe patterns. Existing techniques cannot discern between overlapping fringe patterns, and instead presumes the overlapping fringe patterns to be a single fringe pattern. An error results in the fringe count (and therefore the size determination) as well as in the frequency and position determination of the corresponding particles. 
   SUMMARY OF THE INVENTION 
   To address these and other concerns, the present invention provides a system and process for analyzing fringe pattern data, i.e. the oscillations in the intensity of interfering scattered monochromatic energy, such as the light or other electromagnetic radiation reflected and refracted by droplets. Hereinafter, “intensity” is defined as a radiative energy passing through an area per unit solid angle, per unit of the area projected normal to the direction of passage, and per unit time, or any parameter proportional thereto, such as radiative flux. The fringe pattern data preferably are presented as variations in intensity, over space (as in the case of interferometric particle sizing), or over time (as in the case of laser Doppler velocimetry). 
   Initially, a windowed Fourier transform is applied to the fringe pattern data. If time or distance is presented as the horizontal axis or the abscissa parameter of a plot or profile in which the vertical axis or ordinate represents intensity, a “window” of the fringe pattern data can be pictured as a vertically extending subset or “slice” having a horizontal width along the abscissa (e.g. in pixels or samples representing micrometers or milliseconds) less than the pixel size or width of the fringe pattern data as a whole, and more particularly similar in width to the anticipated fringe pattern width. Each window is characterized by a midpoint along the abscissa, and successive windows are based on progressive shifts of the center point along the abscissa of the data field. Adjacent windows preferably overlap one another. An exemplary window width is in the range of 64 to 128 pixels or samples, and the shift from one window position to the next is 1 to 4 pixels or samples. 
   With respect to each window, a Fourier transform is performed after multiplying the fringe pattern data by a window function. The window function is non-zero within the window width, and zero outside the window. 
   The result is a set of power-frequency spectra, one associated with each window position (hereinafter referred to as a window power-frequency spectrum). For convenience, “frequency” is hereby defined as a spatial frequency having units of inverse length, a periodic frequency having units of inverse time, or a dimensionless angular spacing. The power-frequency spectra are aggregated to give a composite distribution of the power in the frequency-space (or frequency-time) domain. In connection with performing a Fourier transform on each window, criteria can be used to reject points unlikely to be part of a fringe, e.g. due to intensity less than a threshold, or the absence of any substantial intensity oscillation. 
   Next, each window power-frequency spectrum is used to locate a dominant or “peak” frequency (i.e. the frequency where the electromagnetic radiation is at highest power) associated with each window. 
   Based on the sensed peak frequencies, fringe patterns are located by generating a plot or profile of the peak frequencies in a frequency-space or frequency-time domain. Rejected points are assigned a frequency of zero. Because the frequency of fringe patterns is substantially uniform, each fringe pattern appears on the plot or profile as a horizontal (zero slope) line, corresponding in length to the location or duration of the associated fringe pattern. This accurately positions the fringes along the space (or time) axis, and facilitates distinguishing segments of the original fringe pattern data, one segment associated with each fringe pattern, to be extracted from the original data. 
   Each fringe pattern data segment is individually analyzed to determine the fringe pattern frequency. Preferably this is done in a frequency domain by performing a standard Fourier transform on the fringe pattern data segment. Thus, the frequency of each fringe pattern is determined by using the power spectrum produced from the associated fringe pattern data segment, providing an accurate determination of fringe pattern frequency or angular spacing, for conversion to particle size or particle velocity or other physical information of interest, depending on the application. 
   As an alternative to the standard Fourier transform, each fringe pattern data segment can be analyzed in a space or time domain by autocorrelation. 

   
     BRIEF DESCRIPTION OF THE DRAWINGS 
       FIG. 1  is a flowchart illustrating a process for analyzing the fringe pattern data in accordance with an embodiment of the present invention; 
       FIG. 2  illustrates a one-dimensional intensity profile (intensity vs. time t or intensity vs. position x) recorded by a point detector over time, a line detector or an area image sensor; 
       FIG. 3  illustrates a space-frequency distribution for a subset and an abscissa parameter segment of the intensity profile of  FIG. 2 ; 
       FIG. 4  is a plot of peak frequencies in the abscissa-frequency domain over the full range of the intensity profile of  FIG. 2 ; 
       FIG. 5  is a schematic view of an interferometric particle sizing system configured according to the present invention; 
       FIG. 6  illustrates out-of-focus interferometric fringe pattern images produced by an interferometric particle sizing instrument with a conventional circular aperture; 
       FIG. 7  depicts out-of-focus interferometric fringe pattern images produced by the system of  FIG. 5 ; 
       FIG. 8  is an enlarged schematic view depicting the optical system subcomponent of  FIG. 5 ; 
       FIG. 9  is a chart illustrating droplet imaging locations with respect to a nozzle of a pressure atomizer; 
       FIGS. 10-12  are histograms corresponding to different zones of the image of  FIG. 9 ; 
       FIG. 13  depicts a laser Doppler velocimeter according to the present invention; 
       FIG. 13   a  depicts the measuring region of the laser Doppler velocimeter of  FIG. 13 ; 
       FIG. 14  illustrates the oscillation pattern generated by the scattered light from particles passing through the measurement volume in the laser Doppler velocimetry system of  FIG. 13 . 
   

   DETAILED DESCRIPTION OF THE INVENTION 
   Turning now to the drawings,  FIG. 1  is a flowchart illustrating a preferred process for analyzing fringe pattern data to obtain the desired physical information, for example particle sizes in the interferometric particle sizing application. The original fringe pattern data are largely associated directly with particle size or velocity or other physical information depending on the application, and therefore are useful. However, the fringe pattern data also include extraneous data associated with noise, non-spherical particles, and multi-particle effects. Most extraneous data are of limited or no utility and complicates the analysis of fringe pattern data. According to an embodiment of the present invention, windowed Fourier transforms and peak frequencies are employed to distinguish the useful data from the extraneous data and extract the useful data. Subsequent processing steps are performed only on the extracted data, resulting in more reliable particle and droplet characterizing information. 
   The first step, as indicated at  52 , is the detection of scattered light. In one embodiment, this entails forming a two-dimensional image at the sensing plane of an area detector such as a by a CCD (charge coupled device) detector. In alternative systems, the fringe pattern data may be generated, for example, by a point detector such as a photomultiplier tube (PMT) or an avalanche photo detector (APD), a linear CCD detector, or an area detector other than a CCD detector such as a CMOS (complementary metal oxide semiconductor) imaging device. 
   At  54  the recorded fringe pattern information is used to generate a one-dimensional intensity profile  56  as seen in  FIG. 2 , where an intensity is plotted on the ordinate against an abscissa parameter. The abscissa parameter may be a spatial parameter such as distance or pixel if a line or area detector is used, or the abscissa parameter may be time if a point detector is used. Furthermore, when the fringe information is recorded with a two-dimensional area detector, the intensity profile is obtained by vertically scanning (combining or integrating) a small number of neighboring horizontal rows in the two-dimensional image to produce one-dimensional intensity data. Such vertical scanning may be used to analyze the whole image. 
   Next at  58 , a windowed Fourier transform is performed on the fringe pattern data as represented by the intensity profile. Performing a windowed Fourier transform can be thought of as executing multiple standard Fourier transforms, each upon a window or continuous subset  60  of the intensity profile  56  at a different one of multiple window positions. The window positions are incremented along the abscissa to cover the complete length of the profile. Each window position is characterized by an abscissa parameter midpoint. 
   Each Fourier transform is performed only upon data within the associated window, and involves multiplying that data by a window function. The present system employs the 64-sample or 64-pixel Hann window, which is non-zero within the window width and zero outside the window. Other window sizes, e.g. 32 samples or 128 samples, and other window functions, e.g. Hamming window or Blackman window, may be used. In any case, the window width is a continuous fraction or subset of the intensity profile length as measured in pixels corresponding either to time or distance. 
   After the windowed Fourier transforms are performed at all window locations, a window power-frequency spectrum  62 , denoted by the dashed line in the graph in  FIG. 3 , is generated at  64  in for each window and correlated with the midpoint of the window location at the abscissa parameter. A dominant or “peak” frequency corresponding to a frequency at which the power of the power-frequency spectrum  62  is at a maximum is found in each of the spectra, as indicated at  66  in  FIG. 3 . 
   Then, as indicated at  68 , the peak frequencies are plotted or recorded in an abscissa-frequency domain (i.e. space-frequency or time-frequency domain) to produce a ridge map or abscissa-frequency profile  70  of the peak frequencies as depicted in  FIG. 4 . If a “peak frequency” is associated with a window location unlikely to be part of a fringe pattern, for example locations of low amplitude (i.e. below a predetermined threshold) or lacking a perceptible intensity oscillation, the frequency is assigned a value of zero in the ridge map or abscissa-frequency profile  70 , to more clearly separate useful data from extraneous data. 
   The peak (dominant) frequency plot in  FIG. 4  has identified abscissa parameter segments at  72 ,  74 ,  76  and  78 . Abscissa parameter segments  76  and  78  correspond to fringe patterns that overlap, but are distinguishable based on their different peak frequencies. With each fringe pattern having a primary frequency that is substantially constant, segments indicating fringe patterns are likely to have constant frequency or zero slope as indicated for abscissa parameter segments  72 ,  74  and  76 . The “two-tiered” top of abscissa parameter segment  78  illustrates a change in the peak frequency within a predetermined tolerance, so that a fringe pattern is recognized. A segment  80  is rejected, i.e. determined not to represent a fringe pattern, due to the variance in peak frequency. 
   At  82  ( FIG. 1 ), the space or time locations of segments  72 - 78  are applied to the intensity profile ( FIG. 2 ) to distinguish and extract those segments of the original fringe data determined to represent fringe patterns. Each segment is padded with zeros (i.e. assigning a value of zero to elements outside the fringe pattern) on both sides to fix its length, e.g. at 512 samples. Then, as indicated at  84 , the original fringe data within each of segments  72 - 78  are analyzed in a frequency domain by performing a standard Fourier transform on the data within that segment. At  85 , power-frequency spectra associated with segments  72 - 78  are generated and the peak frequency of each fringe pattern data segment is obtained. The result with respect to one of the data segments is a power-frequency spectrum  86  that indicates the peak frequency at  88 , denoted by the solid-line plot in  FIG. 3 . This frequency information can be used to calculate particle size or velocity or other physical quantity or information based on a known relationship depending on the underlying physics of the application. 
   As an alternative to performing standard Fourier transform, each extracted segment of the original fringe data can be analyzed in a space domain by autocorrelation. 
   Because of the improved resolution due to the greater number of sample points in segments  72 - 78  as compared to the window power-frequency spectrums  62 , peak frequency  88  is a more accurate determination of the dominant frequency than is peak frequency  66 . 
   For fringe patterns that are captured in the spatial domain, conversion of the imaged fringe spacing to the angular fringe spacing involves implementing a geometric correction, a step indicated at  90  in  FIG. 1 . In a processing step  92 , the corrected information is used to determine droplet sizes or other information. The methodology for the geometric correction  90  and processing step  92  is described below in connection with  FIG. 8  and equations (1) through (6). 
   Referring to  FIG. 5 , an embodiment of an interferometric droplet measuring system  116  for measuring droplet sizes is depicted including an irradiation source such as a laser  118 , e.g. a 532 nm double-pulsed Nd:YAG laser. Laser  118  incorporates beam shaping optics for generating a laser beam  120 . The laser beam appears as a line in the figure, and occupies a plane perpendicular to the drawing to provide a planar light sheet  122  within a viewing volume traversed by liquid (e.g. water) droplets  117  or other particles. The light sheet has a thickness in the micron-millimeter range, e.g. 250 or 500 micrometers. Droplets  117  can be produced by a nozzle or other source (not depicted) that causes droplets  117  to travel at least generally parallel to the plane of light sheet  122 . Alternatively, droplets  117  can be carried in a turbulent flow along and through the light sheet. In either event, droplets  117  within the light sheet scatter the laser energy by refraction and reflection. 
   System  116  may include a digital camera  124  such as a CCD (charge-coupled device) camera (e.g. 12 bit, 2,000×2,000 pixels) and have an optical system  125  that collects and detects scattered energy. A lens axis or optical axis  126  of the camera lies in the plane of  FIG. 5  and is inclined from the plane of light sheet  122  by a scattering angle θ of 60 degrees. In accordance with generalized scattering imaging (GSI), 60 degrees is the scattering angle at which the oscillation spacing or frequency of fringe patterns exhibits minimum sensitivity to changes in the refractive index of droplets under study. 
   An aperture plate  128  is disposed upstream of digital camera  124  and incorporates an elongate, slot-like aperture oriented lengthwise along the plane of  FIG. 5 . Thus, scattered light reaching camera  124  is restricted to that passing through the elongate aperture. 
   The purpose of aperture plate  128  is to crop the disk-shaped fringe pattern images  129  that correspond to droplets  117 , to improve the capacity to distinguish between separate fringe pattern images. To illustrate this result,  FIGS. 6 and 7  represent fringe pattern images  129  that are out of focus and subtended by a plane  131  having a first or horizontal axis  133  perpendicular to a second or vertical axis  135 . The fringe pattern images  129  of  FIGS. 6 and 7  were produced using a conventional round aperture and slotted aperture plate  128 , respectively. Considering first  FIG. 6 , light scattered by each droplet produces an out-of-focus fringe pattern image in the shape of a disk. The size of the out-of-focus fringe pattern images  129  subtended by the plane  131  depends on camera optics, and accordingly the fringe pattern images are the same size regardless of variations in the diameters of droplets  117 . In contrast, different fringe pattern images have different fringe patterns or oscillation patterns, as represented by the alternating light and dark vertical stripes of the fringe pattern images  129 . Each pattern exhibits a substantially uniform spacing (more precisely, angular spacing) between fringes or oscillations. The spacing is inversely proportional to the diameter of the droplet  117  producing fringe pattern image  129 . The fringe pattern image at the bottom of  FIG. 6  corresponds to a droplet smaller than the fringe pattern images immediately above it with more fringes, i.e. closer fringe pattern spacing. 
   The fringe pattern images  129  in  FIG. 7  are equivalent to that in  FIG. 6 , except that due to aperture plate  128 , the formerly circular fringe pattern images are reduced to horizontal bars comprising horizontal center regions of equivalent circular fringe pattern images  129 . The fringe pattern spacing appears as clearly as it does in  FIG. 6 , with the added advantage that the circular patterns overlapping one another in  FIG. 6  are reduced to spaced apart horizontal bars in  FIG. 7 , and thus are more readily distinguished from one another. As an alternative to plate  128 , a cylindrical lens can be used to compress each fringe pattern image  129 , thereby reducing the incidence of overlapping fringe pattern images. 
   Returning to  FIG. 5 , the output of digital camera  124 , a digital signal representing the fringe pattern images such as those in  FIG. 7 , is provided to a processor  130  for at least temporary storage in a memory  132  and processed based on operating programs  134  also stored in the processor. Droplet information generated as a result of the operations on the incoming signal is provided to a video terminal or other display device  136  that provides the information in human readable form. A controller  137  synchronizes laser  118  and digital camera  124 . 
     FIG. 8  schematically illustrates certain adjustments made to digital camera  124  in the course of using system  116 . Because of the 60-degree (rather than 90-degree) scattering angle θ, the light sheet plane  122  and a lens plane  138  of camera  124  are not parallel, but intersect along a line  140  which appears as a point in  FIG. 8 . Based on the Scheimpflug principle, a focused image plane  142 , i.e. the plane where images from light sheet  122  are in focus, also intersects line  140  and is inclined from lens plane  138  by a Scheimpflug angle β. Light scattered by the droplets  117  is imaged on a light sensing plane  144  perpendicular to lens plane  138  and spaced apart from focused image plane  142 , thus to produce the desired out-of-focus images. 
   Along lens axis  126 , focused image plane  142  and sensing plane  144  are separated by a nominal defocusing distance dzo. Because of the incline of lens plane  138  relative to light sheet  122 , and the resulting incline of sensing plane  144  relative to focused image plane  142 , the actual defocusing distance dzx varies with lateral position, increasing in the rightward lateral direction as viewed in  FIG. 8 . A magnification ratio M x  likewise varies, having a nominal value M 0  at the lens axis. 
   In  FIG. 8 , a droplet  146  spaced apart from lens axis  126  produces an out-of-focus image  148  on sensing plane  144  that also is spaced apart from the lens axis. More particularly, image  144  can be thought of as angularly spaced apart from lens axis  126  by an angle α. The offset from the lens axis distorts image  144 , and the distortion may be corrected or taken into account for the image for a more accurate representation of the fringe pattern spacing. An in-situ calibration to provide direct conversion from a fringe pattern spacing across a fringe pattern image to the corresponding angular fringe pattern spacing Δλ is desirable, but difficult to implement. One aspect of the present invention is a geometric optics-based correction process that compensates for the image distortion. 
   As a first step in the geometric correction process, the system is calibrated using a calibration target to determine a pre-defocusing magnification ratio M corresponding to lens plane  138  positioned at an initial calibration plane  50 , spaced apart axially from light sheet  22  by a distance d o  determined by the equation
 
 d   o =(1+1 /M ) f,    (1)
 
where f is the lens focal length. Then, based on the magnification ratio M and a defocusing shift Δz (i.e. the axial distance between calibration plane  150  and lens plane  138 ), the nominal defocusing plane dz 0  and post-defocusing nominal magnification Mo are determined. Then, the defocusing distance and magnification at any given angle α offset from the lens axis are calculated according to the following equations:
 
 dz   x   =dz   o +(1 +M   o )· f ·sin α[sin α−cos α·tan(α+β)]; and (2)
 
 M   x   =M   o −(1 +M   o )·sin α·[sin α−cos α·tan(α+β)]  (3)
 
   Thus, for any point along sensing plane  144  spaced laterally from lens axis  126 , i.e. offset from the lens axis by a given angle α, the defocusing distance and magnification are corrected from dz 0  to dz x  and from M 0  to M x  to compensate for the relative incline of the sensing plane to the focused image plane. 
   At this stage, the angular spacing of the fringes of the fringe pattern is calculated, based on the corrected values for defocusing distance and magnification, using the equation:
 
Δυ= M   x   ·n·δ/dz   x    (4)
 
where Δυ is the angular fringe pattern spacing in radians; M x  is the magnification at the given point; n is the detected fringe pattern spacing of the image expressed as a number of pixels; and δ is the pixel size in terms of distance (e.g. millimeters) between adjacent pixels.
 
   Conversion of the fringe pattern frequency (spacing) obtained in  185  ( FIG. 1 ) to the angular fringe spacing involves implementing the above-described geometric correction (Equations 1 to 4). At this stage, droplet diameters can be calculated based on the equation:
 
 D=λ·X/Δυ   (5)
 
where D is the droplet diameter; λ is the wavelength of the laser energy; Δυ is the angular fringe pattern spacing; and X is a dimensionless factor that depends on the refractive index and scattering angle θ. Given the system scattering angle θ of 60 degrees at which sensitivity to the refractive index is minimized, a constant value of 1.129 can be substituted for X, resulting in the equation:
 
 D= 1.129·λ/Δυ  (6)
 
   In general, system  116  can measure droplet diameters over a range of diameters from 10 microns to 600 micrometers. Due to the cropping or otherwise vertical narrowing of fringe pattern images and the separation of spatially proximate fringe patterns having different frequencies, system  116  can be used to characterize sprays having densities much higher than those susceptible to analysis by conventional systems. Field results suggest that system  116  is capable of measuring droplets at concentrations up to about 3,000 droplets per cubic centimeter. 
     FIG. 9  illustrates multiple water droplets imaged at a series of image areas A-I with respect to a nozzle  194  of a pressure atomizer. Each point in one of areas A-I corresponds to a droplet detected and measured by system  116 . 
   Measured diameter histograms corresponding to regions A, C, and F ( FIGS. 10 ,  11  and  12 ) indicate dual peaks corresponding to larger droplets (D=45 microns) in a spray sheet area near the nozzle exit, and smaller droplets (D=15 microns) in a recirculation zone surrounded by the spray sheet. Region C lies downstream, disposed primarily in the recirculation zone, and the peak corresponding to the smaller diameter droplets is higher. Further downstream in region F, a hollow conical region of the spray closes, and the peak associated with the larger droplets becomes dominant. 
   The invention may also be embodied in a laser Doppler velocimetry system, such as depicted in  FIG. 13 . Laser Doppler velocimetry (LDV) is an established technique for particle and fluid flow velocity measurements. To measure one component of velocity, a single beam  196  from a laser  198  is split into two parallel beams  200  and  202  and passed through a transmitting lens  204  having a focal length  206 , causing the parallel beams  200  and  202  to cross at an intersection  208 . The intersection  208  defines the measuring region of the system. A particle or particles  210  passing through the intersection  208  scatters light in all directions. Each particle passing through the measuring region moves through a fringe pattern  212  generated by the interference of the two split beams  200  and  202 . A portion of the scattered light is collected by a receiving lens  214  and directed to irradiate a photo detector  216 . 
   In response to the irradiation by the scattered light, the photo detector  216  outputs an oscillation signal  218 , depicted in  FIG. 14 . The oscillation signal  218  is proportional to the intensity of the collected light scattered from the fringe pattern  212 . The oscillation signal  218 , also known as a Doppler burst signal, serves as the signal source for a velocity measurement. A signal processor  220  can use the algorithm of  FIG. 1  to detect the oscillation signal and then process it to obtain the oscillation frequency. Because the oscillation frequency is the inverse of the time required to cross a pair of fringes, the velocity component v normal to the fringes is given by:
 
 v=d   f   /f   D    (7)
 
where d f  is the known spacing of interference fringes, f D  is the oscillation frequency.
 
   Hence, the method depicted in  FIG. 1 , which entails the identification of oscillation patterns and the determination of oscillation frequencies, is applicable in LDV systems. Moreover, the ability of the present invention to discern overlapping fringe patterns enables the LDV technique to be employed in a dense particle field. 
   While the foregoing embodiment has been described in terms of interferometric measurement of droplet size and laser Doppler measurement of particle velocity, it is to be recognized that the principles of the invention apply to a wide variety of particle and droplet measuring techniques that employ the analysis of signals of oscillation pattern produced by, or derived from, scattered coherent light.