A moving target calculation tracking imaging method based on high frame frequency image shift superposition

Abstract

The application discloses a moving target calculation tracking imaging method based on high-frame-frequency image shift superposition, which comprises high-frame-frequency continuous image acquisition and pretreatment; estimation of the visual position of a moving target on an image plane to obtain a measurement coordinate prediction value of the moving target in multiple images; registration of the translation of the image sequence of the moving target on a sub-pixel scale based on the measurement coordinate prediction value to obtain an image after superposition enhancement; star image detection processing on the image after superposition enhancement; track correlation processing based on the star image detection result, and screening of a moving target sequence based on a preset speed range; and output of the information of the moving target. The method can effectively solve the problem that a moving target in a field of view cannot be tracked and imaged in a non-tracking imaging mode of an optical telescope, effectively accumulates a moving target signal and improves a signal-to-noise ratio in software algorithm, and finally realizes effective detection of a dark and weak moving target and high-precision positioning and light measurement of the moving target.

Description

Technical Field

[0001] This invention relates to the fields of astronomical image processing and space moving target observation technology, specifically a moving target calculation and tracking imaging method based on high frame rate image shifting and superposition. Background Technology

[0002] Ground-based photogrammetry remains irreplaceable in the observation of moving targets such as near-Earth small objects and artificial satellites due to its low cost and ease of deployment. In recent years, low-cost, ultra-large field-of-view ground-based photoelectric telescopes have been widely used in this field due to their extremely high observational efficiency. However, in large field-of-view images, there are stars and multiple moving targets with inconsistent apparent motion velocities. Telescopes cannot simultaneously obtain good stellar images of both a reference star and numerous moving targets. When tracking a star, the reference star image is good, but the moving target image is elongated, preventing effective energy accumulation and resulting in a low signal-to-noise ratio. Conversely, when tracking a moving target, the moving target image is good, but the reference star image is elongated, making it impossible to obtain high-precision astrometry information. When moving targets with inconsistent motion velocities appear in the field of view, or when the motion velocity of the moving targets is unknown, the telescope's tracking problem becomes completely unsolvable. Therefore, a moving target computational tracking imaging method based on high-frame-rate image shifting and superposition is urgently needed to solve these problems. Summary of the Invention

[0003] The purpose of this invention is to provide a moving target calculation and tracking imaging method based on high frame rate image shifting and superposition, which can effectively solve the problems existing in the prior art.

[0004] To solve the above-mentioned technical problems, the present invention adopts the following technical solution: a moving target calculation and tracking imaging method based on high frame rate image shifting and superposition, comprising the following steps:

[0005] S1. Perform high frame rate continuous image acquisition at a frequency of not less than 10Hz, and preprocess the acquired images;

[0006] S2. Based on the near-Earth small celestial body ephemeris and the cataloging root of moving targets in space, the apparent position of the moving target on the image plane is estimated, and the predicted values ​​of the metric coordinates of the moving target in multiple frames of images are obtained.

[0007] S3. Based on the predicted metric coordinates of the moving target in multiple frames of images, the moving target is registered and translated at the sub-pixel scale to obtain the superimposed and enhanced image.

[0008] S4. Perform star detection processing on the superimposed and enhanced image;

[0009] S5. Based on the star detection results, perform track association processing and filter out the target sequence based on the preset speed range;

[0010] S6: Output information about the moving target.

[0011] Preferably, high frame rate continuous image acquisition is performed at a frequency of 10Hz.

[0012] Preferably, the acquired images are preprocessed to remove the effects of skylight background, instrument background, and fixed-mode noise, specifically including:

[0013] Set a median filter window of odd length L, where L = 2K + 1, K is a positive integer, and K is greater than the diameter of all constellations;

[0014] Let I(x, y) be the pixel in the image to be processed, where x and y represent the row and column values ​​of the corresponding pixel in the image, respectively;

[0015] Using a long window, the image to be processed is filtered row by row and column by column in the x and y directions at a time. The value of a pixel after filtering is I′(x, y).

[0016] ;

[0017] Preprocessing is completed by dividing pixel I(x, y) in the original image by the filtered pixel I′(x, y). The size of the image to be processed is m×n.

[0018] Preferably, based on the dark field image, subtracting fixed-pattern noise caused by dark current inhomogeneity includes the following steps:

[0019] S1. Cover the lens cap of the device and acquire a dark field image sequence in the absence of light signal;

[0020] S2. Merge the dark field images to suppress the effect of readout noise;

[0021] S3. Subtract the dark field image from the measured image sequence to eliminate the influence of dark current non-uniformity.

[0022] Preferably, in step S2, the orbital elements of the moving target in space and the position of the near-Earth small celestial body are obtained; wherein:

[0023] For near-Earth small celestial bodies, the ephemeris is obtained directly from the website, and then the celestial coordinates are obtained by interpolation based on the shooting time;

[0024] For moving targets in space, ephemeris predictions are obtained based on SPG4 and SDP4 models, and then celestial coordinates are obtained by interpolation based on the shooting time.

[0025] By using the centripetal projection model, the celestial coordinates of moving targets and near-Earth small celestial bodies are transformed to the measurement coordinates of the image plane, and the predicted measurement coordinates of the moving targets in multiple frames of images are obtained.

[0026] Preferably, the transformation from celestial coordinates to measurable coordinates of the moving target is specifically as follows:

[0027] Establish a rectangular coordinate system with the image center C as the origin, the vertical axis as the projection of the declination circle, taking the direction of increasing declination as positive, and the horizontal axis perpendicular to the x-axis, taking the direction of increasing right ascension as positive. Construct an ideal coordinate system C- for the image plane. ;

[0028] The formula for converting the celestial coordinates of a moving target to ideal coordinates is as follows:

[0029] ;

[0030] in, The coordinates of the celestial sphere corresponding to the center of the image;

[0031] The parameters of the film model are calculated using the least squares method based on a polynomial model. The formula is:

[0032] ;

[0033] Where (x, y) are the measurement coordinates of the moving target in the image, and m represents the order of the polynomial; when The number of (x,y) parameters exceeds the number of parameters to be estimated. In cases of quantity, the parameters of the film model are obtained using the least squares method. The best estimate.

[0034] Preferably, in step S3, the registration of the image sequence at the sub-pixel scale is performed to obtain the new image S(i,j) after shifting, specifically as follows:

[0035] Using the first frame or an intermediate frame as a reference, calculate the displacement (dx, dy) of the time sequence image relative to the reference image, where dx and dy are in pixels;

[0036] Let P(i,j) be the pixel value of the image, where i and j represent the row and column numbers of the pixel, respectively;

[0037] The integer pixel shift is performed based on the integer parts int(dx) and int(dy) of the displacement (dx, dy), i.e.:

[0038] Q(i,j)=P(i+int(dx),j+int(dy));

[0039] Subpixel shifting is performed based on the fractional parts of the displacement (dx, dy), dx' = dx - int(dx) and dy' = dy - int(dy), including:

[0040] Perform subpixel shift in the row direction: R(i,j)=(1- dx') ×Q(i,j)+ dx' ×Q(i,j+1);

[0041] Perform subpixel shift in the column direction: S(i,j)=(1- dy') ×R(i,j)+ dy'×R(i+1,j).

[0042] Preferably, for all n moving targets predicted to appear in the field of view, n sets of subpixel shifted image sequences are obtained in parallel based on the same reference image; the n sets of image sequences are superimposed in parallel to obtain n frames of superimposed enhanced images, corresponding to the simultaneous tracking and imaging of n moving targets in the field of view.

[0043] Preferably, in step S5, when performing track association processing: an initial track is established for all target pairs in the neighboring frame images according to the apparent motion speed range of the moving target, and the track is extrapolated based on the rule of uniform linear motion to select the sequence that establishes a stable track and whose speed is within the set range as the moving target sequence.

[0044] Preferably, in step S6, the moving target information includes the observation time corresponding to the moving target information, the measurement coordinates of the moving target, the signal-to-noise ratio, the gray value, as well as the celestial coordinates of the moving target and the instrument star.

[0045] Beneficial effects: This invention is based on a moving target computational tracking imaging method using high frame rate image shifting and superposition. It can acquire wide-area short-exposure images at high frequency using a small-aperture ultra-large field-of-view optical telescope and an sCMOS camera. The shorter exposure time can suppress the influence of the sky background, while simultaneously "freezing" (not stretching) all moving targets and reference stars in the observed image. Based on the motion characteristics of the reference star and multiple types of moving targets, the invention achieves simultaneous tracking imaging of all types of moving targets within the field of view through sub-pixel-scale image shifting and parallel superposition enhancement methods in software algorithms. This effectively solves the problem that multiple types of moving targets cannot be simultaneously tracked and imaged in the observed image. Attached Figure Description

[0046] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used together with the embodiments of the invention to explain the invention and do not constitute a limitation thereof.

[0047] In the attached diagram:

[0048] Figure 1 A flowchart illustrating a method for calculating and tracking imaging of moving targets based on high frame rate image shifting and overlay;

[0049] Figure 2 A schematic diagram of subpixel image shifting for the invention;

[0050] Figure 3This is an example of the effect of star tracking imaging in a measured star map sequence using the method of the present invention;

[0051] Figure 4 This is an example of the tracking and imaging results of a medium orbit moving target (MEO) in a measured star map sequence using the method of the present invention;

[0052] Figure 5 This is an example of the tracking and imaging results of a geostationary orbit moving target (GEO) in a measured star map sequence using the method of the present invention. Detailed Implementation

[0053] To make the objectives and advantages of this invention clearer, the invention will be specifically described below with reference to embodiments. It should be understood that the following text is merely used to describe a moving target calculation and tracking imaging method based on high frame rate image shifting and superposition, or several specific implementation methods of this invention, and does not strictly limit the scope of protection specifically claimed by this invention.

[0054] Example: Figure 1 As shown, a moving target computational tracking imaging method based on high frame rate image shifting and superposition includes high frame rate star image acquisition and preprocessing; moving target apparent motion velocity estimation; sub-pixel scale image shifting; parallel superposition of temporal images; star detection; moving target association; and output of the metric coordinates and grayscale values ​​of the moving target, ultimately achieving tracking imaging of the moving target star image in the field of view. It can effectively solve the problem that photoelectric telescopes cannot track and image moving targets in the field of view in non-tracking imaging mode. In terms of software algorithm, it realizes effective accumulation of moving target signals and improvement of signal-to-noise ratio, ultimately achieving effective detection of faint moving targets and high-precision positioning and photometry of moving targets.

[0055] In one specific embodiment, the telescope used has an aperture of 150mm and a focal length of 160mm; the detector is a Dhyana4040 camera with a target size of 4096×4096×9um;

[0056] (1) Select the sky area where faint space moving targets or near-Earth small celestial objects may appear as the object. Based on the small aperture ultra-large field of view optical telescope and sCMOS camera, high frequency acquisition of wide-area short exposure images is used. The shorter exposure time can suppress the influence of the sky background. The high frame rate (10Hz) imaging mode is adopted to continuously acquire 100 frames of star map.

[0057] (2) Preprocessing of the acquired time-series images to remove the effects of skylight background, instrument background, and fixed-mode noise; specifically including:

[0058] (21) Let the image to be processed be of size mpixel×npixel. Use two variables x and y to represent the row and column values ​​of a certain pixel in the whole image, respectively. I(x, y) represents the intensity value matrix of each pixel when reading the image (actual size is m×n).

[0059] (22) Set a median filter window with an odd length L, L=2K+1, where K is a positive integer. K must be greater than the radius of all stars to ensure that there are no unfiltered stars in the filtered image.

[0060] (23) The filtering calculation is performed row by row and column by column in both the x and y directions. The value of each pixel after filtering is represented by I′(x, y):

[0061] ;

[0062] I′(x, y) is the low-frequency signal in the observed image. Dividing the original image I(x, y) by I′(x, y) will remove its uneven background and complete the preprocessing.

[0063] (24) Based on the dark field image, subtract the fixed-mode noise caused by dark current inhomogeneity; including the following steps:

[0064] S1. Cover the lens cap of the device and acquire a dark field image sequence in the absence of light signal;

[0065] S2. Merge the dark field images to suppress the effect of readout noise;

[0066] S3. Subtracting the dark field image from the measured image sequence can eliminate the influence of dark current non-uniformity.

[0067] (3) Based on the near-Earth small celestial bodies ephemeris and the number of spatial moving targets cataloging elements, the apparent position of the moving target on the image plane is estimated, and its apparent motion speed and direction are obtained by solving according to the frame rate.

[0068] (31) Obtain the orbital elements (two-line elements, TLE) of moving targets in space and the positions of near-Earth objects through the SpaceTrack website and the IAU MPC website.

[0069] (32) For near-Earth small celestial bodies, their ephemeris can be obtained directly from the website, and their celestial coordinates can be obtained by interpolation based on the shooting time;

[0070] (33) For moving targets in space, the ephemeris is predicted based on the SPG4 and SDP4 models, and its celestial coordinates are obtained by interpolation based on the shooting time;

[0071] (34) The celestial coordinates of moving targets in space and near-Earth small celestial bodies are transformed to the measurement coordinates of the image plane through the centripetal projection model.

[0072] (35) Establish a rectangular coordinate system in the star map with the image center C as the origin, and the vertical axis as the coordinate system. This is the projection of the declination circle, taking the direction of increased declination as positive, with the horizontal axis... Perpendicular to The axis is defined by taking the direction of increasing right ascension as the positive direction, thus constructing an ideal coordinate system C- for the image plane. The celestial (equatorial) coordinates of the moving target. The formula for converting to ideal coordinates is:

[0073] ;

[0074] in, The coordinates of the celestial sphere corresponding to the center of the image;

[0075] (36) Solve the film model parameters using the least squares method based on the polynomial model. The formula is:

[0076] ;

[0077] Where (x, y) are the metric coordinates of the moving target in the image, thus completing the transformation from celestial coordinates to metric coordinates of the moving target; m represents the order of the polynomial; in The number of (x,y) parameters exceeds the number of parameters to be estimated. In cases involving quantity, the parameters of the film model can be obtained using the least squares method. The best estimate;

[0078] (4) Based on the predicted metric coordinates of the moving target in multiple frames of images, the translation registration of the image sequence is completed at the sub-pixel scale.

[0079] (41) Using the first frame image or the intermediate frame image as a reference, calculate the displacement of the time sequence image relative to the reference image.

[0080] (42) Let P(i,j) be the pixel value of the image, where i and j represent the row and column numbers of the pixel, respectively; let the displacement to be made in the time series image be (dx,dy), where dx and dy are in pixels; the subpixel shifting steps of the image are divided into two steps: “integer pixel shifting” and “subpixel shifting”.

[0081] (43) The displacement of "integer pixel shift" is the integer part of dx and dy, int(dx) and int(dy), respectively, that is:

[0082] Q(i,j)=P(i+int(dx),j+int(dy));

[0083] (44) The displacement of the subpixel shift is the fractional part of dx and dy: dx' = dx - int(dx) and dy' = dy - int(dy).

[0084] First, perform a "subpixel shift" in the row direction, that is:

[0085] R(i,j)=(1- dx') ×Q(i,j)+ dx' ×Q(i,j+1);

[0086] Perform a "subpixel shift" in the column direction, that is:

[0087] S(i,j)=(1- dy') ×R(i,j)+ dy'×R(i+1,j);

[0088] After the above operations, the new image S(i,j) after shifting is obtained.

[0089] (45) For all moving targets that are predicted to appear in the field of view (assuming there are n moving targets), based on the same reference image, n sets of subpixel shifted image sequences are processed in parallel; the n sets of image sequences are superimposed in parallel to obtain n frames of superimposed enhanced images, corresponding to the simultaneous tracking and imaging of n moving targets in the field of view.

[0090] Based on the above tracking and imaging results, the following is a summary:

[0091] like Figure 3 As shown, the calculated tracking imaging results of the stellar target are dx and dy, which are approximately 0.460 pixels / s and -3.160 pixels / s, respectively.

[0092] like Figure 4 As shown, this is the calculated tracking and imaging result of a moving target in a MEO orbit, with dx and dy being approximately 3.074 pixels / s and 0.667 pixels / s, respectively.

[0093] like Figure 5 The figure shows the calculated tracking and imaging results of a moving target in a GEO orbit, with dx and dy being approximately -0.010 pixels / s and 0.003 pixels / s, respectively.

[0094] (5) Perform star detection processing on the superimposed and enhanced image; by calculating the background mean and standard deviation of the image, perform binarization segmentation on the image, and count the pixel blocks of the connected regions as stars;

[0095] (6) Based on the star detection results after sub-pixel scale superposition enhancement of multiple sets of measurement images, track association processing is performed. According to the apparent motion speed range of the moving target, an initial track is established for all target pairs in the neighboring frame images. The track is extrapolated based on the rule of uniform linear motion. Only the sequence with a stable track and a speed within the set range is the moving target sequence, thus avoiding false alarms caused by displacement superposition and star interference in the field of view.

[0096] (7) Output moving target information, including the observation time corresponding to the moving target information, the measurement coordinates of the moving target, the signal-to-noise ratio, the gray value, as well as the celestial coordinates of the moving target and the instrument magnitude.

[0097] The embodiments of the present invention have been described in detail above with reference to the accompanying drawings. However, the present invention is not limited to the above embodiments. For those skilled in the art, after learning the contents described in the present invention, several equivalent changes and substitutions can be made without departing from the principle of the present invention. These equivalent changes and substitutions should also be considered to fall within the protection scope of the present invention.

Claims

1. A moving target calculation and tracking imaging method based on high frame rate image shifting and superposition, characterized in that: Includes the following steps: S1. Perform high frame rate continuous image acquisition at a frequency of not less than 10Hz, and preprocess the acquired images; S2. Based on the near-Earth small celestial body ephemeris and the cataloging root of moving targets in space, the apparent position of the moving target on the image plane is estimated, and the predicted values ​​of the metric coordinates of the moving target in multiple frames of images are obtained. S3. Based on the predicted metric coordinates of the moving target in multiple frames of images, the moving target is registered and translated at the sub-pixel scale to obtain the superimposed and enhanced image. S4. Perform star detection processing on the superimposed and enhanced image; For all n moving targets that are predicted to appear in the field of view, n sets of sub-pixel shifted image sequences are obtained through parallel processing based on the same reference image. n sets of image sequences are superimposed in parallel to obtain n frames of superimposed enhanced images, which correspond to simultaneous tracking and imaging of n moving targets in the field of view; S5. Based on the star detection results, perform track association processing and filter out the target sequence based on the preset speed range; Based on the star detection results enhanced by subpixel scale superposition of multiple sets of measurement images, when performing track association processing: an initial track is established for all target pairs in the neighboring frame images according to the apparent motion speed range of the moving target, and the track is extrapolated based on the rule of uniform linear motion. The sequence that establishes a stable track and whose speed is within the set range is selected as the moving target sequence. S6: Output information about the moving target.

2. The moving target calculation and tracking imaging method based on high frame rate image shifting and superposition according to claim 1, characterized in that: High frame rate continuous image acquisition is performed at a frequency of 10Hz.

3. The moving target calculation and tracking imaging method based on high frame rate image shifting and superposition according to claim 1, characterized in that: The acquired images are preprocessed to remove the effects of skylight background, instrument background, and fixed-mode noise. Specifically, this includes: Set a median filter window of odd length L, where L = 2K + 1, K is a positive integer, and K is greater than the diameter of all constellations; Let I(x, y) be the pixel in the image to be processed, where x and y represent the row and column values ​​of the corresponding pixel in the image, respectively; Using a long window, the image to be processed is filtered row by row and column by column in the x and y directions at a time. The value of a pixel after filtering is I′(x, y). ； Preprocessing is completed by dividing pixel I(x, y) in the original image by the filtered pixel I′(x, y). The size of the image to be processed is m×n.

4. A moving target calculation and tracking imaging method based on high frame rate image shifting and superposition as described in claim 1 or 3, characterized in that: Based on the dark field image, the fixed-pattern noise caused by dark current inhomogeneity is subtracted, including the following steps: S1. Cover the lens cap of the device and acquire a dark field image sequence in the absence of light signal; S2. Merge the dark field images to suppress the effect of readout noise; S3. Subtract the dark field image from the measured image sequence to eliminate the influence of dark current non-uniformity.

5. The moving target calculation and tracking imaging method based on high frame rate image shifting and superposition according to claim 1, characterized in that: In step S2, the orbital elements of the moving target in space and the position of the near-Earth small celestial body are obtained; wherein: For near-Earth small celestial bodies, the ephemeris is obtained directly from the website, and then the celestial coordinates are obtained by interpolation based on the shooting time; For moving targets in space, ephemeris predictions are obtained based on SPG4 and SDP4 models, and celestial coordinates are obtained by interpolation based on the shooting time. By using the centripetal projection model, the celestial coordinates of moving targets and near-Earth small celestial bodies are transformed to the measurement coordinates of the image plane, and the predicted measurement coordinates of the moving targets in multiple frames of images are obtained.

6. The moving target calculation and tracking imaging method based on high frame rate image shifting and superposition according to claim 5, characterized in that: The specific transformation from celestial coordinates to measurable coordinates for a moving target is as follows: Establish a rectangular coordinate system with the image center C as the origin, the vertical axis as the projection of the declination circle, taking the direction of increasing declination as positive, and the horizontal axis perpendicular to the x-axis, taking the direction of increasing right ascension as positive. Construct an ideal coordinate system C- for the image plane. ; The formula for converting the celestial coordinates of a moving target to ideal coordinates is as follows: ； in, The coordinates of the celestial sphere corresponding to the center of the image; The parameters of the film model are calculated using the least squares method based on a polynomial model. The formula is: ； Where (x, y) are the measurement coordinates of the moving target in the image, and m represents the order of the polynomial; when The number of (x,y) parameters exceeds the number of parameters to be estimated. In cases of quantity, the parameters of the film model are obtained using the least squares method. The best estimate.

7. The moving target calculation and tracking imaging method based on high frame rate image shifting and superposition according to claim 1, characterized in that: In step S3, the image sequence is translated and registered at the sub-pixel scale to obtain the new image S(i,j) after shifting. Specifically: Using the first frame or an intermediate frame as a reference, calculate the displacement (dx, dy) of the time sequence image relative to the reference image, where dx and dy are in pixels; Let P(i,j) be the pixel value of the image, where i and j represent the row and column numbers of the pixel, respectively; The integer pixel shift is performed based on the integer parts int(dx) and int(dy) of the displacement (dx, dy), i.e.: Q(i,j)=P(i+int(dx),j+int(dy)); Subpixel shifting is performed based on the fractional parts of the displacement (dx, dy), dx' = dx - int(dx) and dy' = dy - int(dy), including: Perform subpixel shift in the row direction: R(i,j)=(1- dx') ×Q(i,j)+ dx' ×Q(i,j+1); Perform subpixel shift in the column direction: S(i,j)=(1- dy') ×R(i,j)+ dy'×R(i+1,j).

8. The moving target calculation and tracking imaging method based on high frame rate image shifting and superposition according to claim 1, characterized in that: In step S6, the moving target information includes the observation time corresponding to the moving target, the measurement coordinates of the moving target, the signal-to-noise ratio, the gray value, as well as the celestial coordinates of the moving target and the instrument satellite.

Images