Space target lengthened astronomical image astronomical positioning method of large-view-field space-based monitoring platform

Abstract

The invention discloses an astronomical positioning method for a space target elongated astronomical image of a large-field-of-view space-based monitoring platform, relates to the technical field of astronomical observation, and solves the problem that the elongated astronomical image is abandoned due to incapability of target association and precise orbit determination caused by inaccurate centering of the elongated astronomical image and low precision of a positioning method of an existing monitoring platform. According to the method, an observation image is divided into 16 sub-view fields, and each sub-view field is an independent view field and is calculated by an independent processor; removing fixed stars in the observation image by adopting an adjacent frame image difference method and extracting a space target star image; secondly, describing the length and angle of the lengthened astronomical image by adopting a minimum enclosing rectangle, and constructing a degradation model; performing motion blurred image restoration on the elongated star image; error points with large errors are eliminated by adopting a mutual comparison method, and track association of the space target is completed; and finally completing precise astronomical positioning of the elongated astronomical image and the like. According to the method, the processing efficiency is greatly improved, and a large number of lengthened astronomical images which are abandoned before are fully utilized again.

Description

Technical Field

[0001] The invention relates to the technical field of astronomical observation, and in particular to an astronomical positioning method for elongated star images of space targets on a large-field-of-view space-based monitoring platform. Background Art

[0002] At present, my country has more than 900 artificial satellites working in orbit at the same time, undertaking many important tasks such as navigation positioning and space science research. These application satellites are closely related to the national economy and national defense construction. Once damaged, they will have a huge social and economic impact and even endanger national security. Therefore, it is necessary to take effective measures to achieve accurate detection and high-precision positioning of space targets, so that artificial satellites in orbit can effectively avoid collisions with space debris or other spacecraft. Compared with traditional ground observation platforms, space-based monitoring platforms can provide a wider field of view and all-weather observation capabilities, and can meet the needs of all-weather continuous monitoring and precise feature measurement of artificial satellites and space debris. However, when the space-based monitoring platform is in orbit, its monitoring of space targets is in a dynamic capture scene, especially when the space-based monitoring platform and the space target meet at the closest distance according to their respective orbits, the apparent motion speed of the observed space target suddenly increases, causing the star image of the space target to be elongated after the camera is exposed, which is very unfavorable for the high-precision positioning of the space target.

[0003] Traditional observation platforms generally use the centroid restoration method to deal with the problem of elongated star images, that is, to draw a boundary at the elongated star image and find the geometric centroid of the boundary to restore the centroid of the elongated star image of the space target. However, this type of method is not very accurate, especially in the process of processing sequential images, the elongated star image restoration results of the previous and next frames are not related, and the random error is large. It is more suitable for the application scenario of ground observation platforms observing first and then processing.

[0004] In summary, the space-based space target monitoring platform moves rapidly with the carrying satellite, which causes the space target star image in the image to be elongated and blurred, especially when the distance between the carrying satellite and the space target is close, the elongation and blurring phenomenon is even worse. This makes the centroid extraction error of the target star image extremely large, seriously affecting the accuracy of astronomical positioning and precise orbit determination.

[0005] For space-based surveillance platforms, the problem of elongated star images of space targets in sequence images can be solved by establishing a fuzzy kernel function, and then training the function through repeated iterations, accurately predicting the degree of elongation of star images, slope direction, etc. based on the point spread function of star images, thereby more accurately restoring the center of mass of the elongated star images of space targets, and providing more accurate and more secure data support for the coordinates of the center of mass of star images for subsequent astronomical positioning and precise orbit determination of space targets. Therefore, in order to improve the space situation awareness capability of space-based surveillance platforms, the present invention provides an astronomical positioning method for elongated star images of space targets for large-field-of-view space-based surveillance platforms, which can eliminate or reduce the interference factors of this elongation phenomenon, which is crucial for high-precision orbit determination, tracking and cataloging of space targets. Summary of the invention

[0006] The present invention aims to solve the problems that the existing monitoring platform has inaccurate centering of elongated stars, the positioning method has low precision, resulting in the inability to perform target association and precise orbit determination, and thus the elongated stars are abandoned. A method for astronomical positioning of space targets with elongated stars for a space-based monitoring platform with a large field of view is provided.

[0007] A method for astronomical positioning of space targets with elongated stars for a large-field-of-view space-based surveillance platform, the method being implemented by the following steps:

[0008] Step 1: Obtain observation images;

[0009] Step 2: performing image preprocessing on the observation image described in step 1;

[0010] Step 3: extract the star catalog, perform star map matching, establish the mapping relationship between the celestial coordinates of the calibration star and the image coordinates, and solve the plate constant model;

[0011] Step 4: Adopting the adjacent frame image difference method to eliminate the stars in the observed image preprocessed in step 2 and extract the space target star image;

[0012] Step 5: restore the elongated space target star image in the extracted space target star image to obtain the centroid coordinates of the space target restored image; the specific process is:

[0013] Step 51: Use the minimum circumscribed rectangle to describe the length L and the elongated angle θ of the elongated space target star image, and construct a degradation model of astronomical image degradation caused by motion blur;

[0014] Step 52: According to the degradation model, the motion blurred image of the elongated space target star image is restored to obtain the image coordinates of the restored space target;

[0015] Step 6: Use the mutual comparison method to eliminate the error points and realize the track association of the space target star image in the restored image;

[0016] Step 7: Complete accurate astronomical positioning of the space target star image that has completed track association.

[0017] Beneficial effects of the present invention:

[0018] 1. In the method of the present invention, based on the degradation model of astronomical image degradation caused by motion blur and the iterative calculation method of fuzzy kernel function, the elongated star image of the space target is restored. It is particularly suitable for application scenarios in which space-based monitoring platforms process sequence images. By repeatedly iteratively training the fuzzy kernel function, the direction and length of the point spread function of the elongated star image are estimated by maximum likelihood, the elongated and blurred star image is restored, and accurate center of mass coordinate data is extracted, thereby achieving high-precision astronomical positioning and precise orbit determination of space targets.

[0019] 2. The space-based monitoring platform in the method of the present invention has the advantages of being unaffected by weather, 24-hour continuous observation, and strong mobility of the observation position. However, the observation platform operates in a low-Earth orbit and has a fast operating speed. Its relative speed with the observed space target is large, resulting in a large number of space targets with elongated stars appearing on the space-based monitoring platform. The present invention aims to solve the problem of the inability to perform target association and precise orbit determination due to the low astronomical positioning accuracy of the space-based monitoring platform for the elongated space targets, so that a large number of elongated stars that were previously discarded can be fully utilized again.

[0020] 3. The method of the present invention adopts a multi-core parallel computing solution with a divided field of view to monitor space targets, which greatly improves the processing efficiency and is particularly suitable for space-based observation platforms that monitor space targets with a large field of view.

[0021] 4. The root mean square error (RMS value) of the astronomical positioning of the stretched space target after the star image is restored by the method of the present invention is much smaller than the traditional astronomical positioning method of restoring the centroid of the space target using the centroid when dealing with the stretched star image problem. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 The present invention provides a schematic diagram of 16 partitions of an observation image in a method for astronomical positioning of space targets by elongated star images on a space-based surveillance platform with a large field of view.

[0023] Figure 2 Schematic diagram of the difference method of adjacent frame images; among them, the constellations numbered 1 to 9 are stars distributed in the sky in sequence, and the constellations numbered A and B are space targets.

[0024] Figure 3 The minimum enclosing rectangle is used to describe the elongated star image of the space target;

[0025] Figure 4 It is a schematic diagram of the length L and the elongation angle θ of the space target star image;

[0026] Figure 5Degradation model for astronomical images caused by motion blur

[0027] Figure 6 The adjacent frame image difference method is used to remove stars from the image and extract the schematic diagram of the space target; where (a) is the schematic diagram of the previous frame image, and (b) is the schematic diagram of the next frame image;

[0028] Figure 7 Schematic diagram of space target track association principle;

[0029] Figure 8 The star image restoration effect diagram of the stretched sequence of space target images; among them, (a) is the stretched sequence of space target star image (1 to 5 frames), and (b) is the restored sequence of space target star image (1 to 5 frames). DETAILED DESCRIPTION

[0030] Specific implementation method 1. Combination Figures 1 to 8 The present embodiment is described as a method for astronomical positioning of space targets with elongated stars on a large-field-of-view space-based surveillance platform. The method first divides the captured image of the large field of view into 16 sub-fields of view, such as Figure 1 As shown. With the increase of the aperture and field of view of the observation telescope, the number of stars in the field of view also increases dramatically, so the observation image is divided into 16 sub-fields of view. The space-based monitoring platform carries an embedded multi-core parallel processor. Each sub-field of view is an independent field of view and is calculated by an independent processor, which improves processing efficiency and meets the real-time processing requirements of astronomical positioning. Secondly, the adjacent frame image difference method is used to remove the stars in the observation image and extract the space target star image. Then the minimum circumscribed rectangle is used to describe the length and angle of the elongated star image, the fuzzy kernel function is defined, and the Lucy-Richardon algorithm is used to restore the motion blurred image of the elongated star image; then the mutual comparison method is used to eliminate the error points with large errors and complete the track association of the space target; finally, the precise astronomical positioning of the elongated star image is achieved. The specific process of this implementation method is:

[0031] Step 1. Obtain the observed image; the specific process is:

[0032] Step 1-1. Turn on the telescope of the space-based monitoring platform and record the orbital instantaneous root, attitude parameters and guidance data (A, H) fed back by the telescope motor encoder, where A is the azimuth of the space-based monitoring platform and H is the altitude of the space-based monitoring platform; calculate the direction of the telescope in celestial coordinates, i.e. the center direction of the telescope (C_Ra, C_Dec) according to the above data. Set the camera exposure time T and shooting time t to obtain a set of sequential images as observation images;

[0033] Step 1-2. Divide the observed image into 16 sub-fields of view on average, and calculate and record the center direction of each sub-field of view according to the center direction of the telescope (C sub _Ra,C sub _Dec), where sub is the sub-field number and also the number of the corresponding core of the multi-core parallel processor, sub=0~15.

[0034] Step 2. Image preprocessing;

[0035] The observed image is preprocessed, including image threshold segmentation, dilation operation, and contour extraction. The centroid of the extracted stars is calculated to obtain the image coordinates (x i ,y i According to the field of view division rule, the image coordinates of the stars in each sub-field of view are (x subi ,y subi ),sub=0~15.

[0036] Step 3. Extract the star catalog; perform star map matching to establish the film constant model;

[0037] According to the central pointing direction of the telescope (C_Ra, C_Dec), the celestial coordinates of the photographed area are solved by the calculation method of spherical astronomy, and combined with the field of view of the telescope, the calibration star group (α l ,δ l )(l=1~N st , N st is the total number of stars extracted from the standard star catalog), then the sub-field of view corresponds to the calibration star group in the standard star catalog (α subl ,δ subl ).

[0038] In this implementation, the specific process of establishing the film constant model through star map matching is as follows:

[0039] Step 3-1. Image coordinates (x i ,y i ) and calibration star group (α l ,δ l ) uses the triangle matching sub-graph isomorphism algorithm to perform star map matching, and the center position coordinates (α0, δ0) of the first frame image are obtained by star map matching.

[0040] Step 3-2. Solve the extracted calibration star group (α l ,δ l ) is calculated as follows:

[0041]

[0042] Step 3-3. Image coordinates of the star (x i ,y i ) and the ideal coordinates (ζ i ,η i ) also has a mapping relationship, and the six-constant film model is used to describe this mapping relationship:

[0043]

[0044] Among them, A, B, C, D, E, F are film constants, and Ω is the ratio of the camera pixel size to the focal length of the telescope. By combining equations (1) and (2), we can solve the film constants by the least squares method, thereby establishing the mapping relationship between the celestial coordinates of the calibrated stars and the image coordinates.

[0045] Step 3-4. Set the image center coordinates (x C ,y C ) sub Substituting (1) and (2) into equations, we can find the center position coordinates (α) of each sub-field in the current frame. sub0 ,δ sub0 ), so far, each sub-field of view can use an independent processor (core) to perform star map matching and film constant calculation in its own sub-field of view.

[0046] Step 3-5. As the sequence of images is captured, the center position coordinates (α sub0 ,δ sub0 ) can be obtained from the celestial coordinates of the center position of the previous frame (α sub0 ,δ sub0 )′ is continuously updated and corrected in combination with the shooting time t and the guidance data (A, H) of the telescope, and the film constant is also updated and corrected accordingly.

[0047] Step 4. Use the adjacent frame image difference method to separate the stars and space target constellations from the preprocessed observation image.

[0048] In this embodiment, the adjacent frame image difference method is used to remove stars in the observed image and extract the space target star image; the observation mode of the space-based monitoring platform is set to the star rate mode, so the star movement in the telescope is the diurnal apparent motion, that is, the star in the next frame of the star image will move to the right by a certain distance relative to the previous frame, and the distance can be calculated by the exposure time and the moving speed. Figure 6As shown in the figure, (a) is a schematic diagram of the previous frame image, and (b) is a schematic diagram of the next frame image; all the stars in the previous frame are translated to the right to obtain new coordinates; the coordinates of the stars in the previous and next frames are compared. If the difference in coordinate distance is less than the matching threshold σ, it is judged as a star and the image coordinates of these stars are recorded, otherwise it is judged as a suspected space target; the specific process is as follows:

[0049] Step 4-1. Settings is the centroid coordinate of the star image of the k-th frame observation image, set is the centroid coordinate of the star image in the k-1th frame observation image, then the distance between the star images in the k-1th frame observation image is:

[0050]

[0051] Step 4-2. According to the uniform motion characteristics of stars on the camera target surface, the motion distance of the stars in the two frames of the sequence image is is equidistant, while the moving distance of space target stars is Distance from star motion There is an obvious difference in comparison. The matching coefficient D can be calculated and the following judgment can be made:

[0052]

[0053] Where σ is the matching threshold, which is related to the observation accuracy, and is generally set to 1 to 2 pixels. When D = 0, it means and is a star. When D=1, it means and Suspected to be a space target. The movement distance of space target stars is significantly different from that of stars, such as Figure 2 As shown, after translation, the positions of the space targets in the k-1th and kth frames will be staggered. By operating the kth and k+1th frames in the same way, the suspected space targets can be selected.

[0054] Step 5. Restore the elongated space target star image and obtain the image coordinates (x ta ,y ta ), ta=1~N ta , N ta is the total number of space targets; the specific process is:

[0055] Step 5-1. Use the minimum bounding rectangle to describe the elongated image of the space target, and set the coordinates of the four vertices of the bounding rectangle to be A(x a ,y a ),B(x b ,y b ),C(xc ,y c ),D(x d ,y d ),like Figure 3 As shown. The central axis EF of the rectangle intersects AB and CD at E(x e ,y e ),F(x f ,y f ), then the coordinates of the end points of the central axis EF of the rectangle's major axis are:

[0056]

[0057] like Figure 4 As shown in the figure, the length L of the elongated space target star image and the elongation angle θ are calculated as follows:

[0058]

[0059]

[0060] Where n is the number of pixels occupied by the elongated space target star image in the x-axis direction, and m is the number of pixels occupied by the elongated star image in the y-axis direction;

[0061] For astronomical images with elongated stars, blurred images and degraded quality caused by moving targets, image deconvolution can be used to restore the source image. A degradation model for astronomical images degraded by motion blur is constructed, such as Figure 5 As shown in the figure, the ideal clear image h(x,y) is degraded into a motion stretched blurred image b(x,y) under the effect of the blur kernel function k(x,y) and the noise γ(x,y). The mathematical expression of the degradation model is as follows:

[0062] b(x,y)=h(x,y)*k(x,y)+γ(x,y)(8)

[0063] Among them, b(x,y) is the stretched motion blurred image of the space target taken by the camera, h(x,y) is the ideal clear image, k(x,y) is the blur kernel function, γ(x,y) is the additive noise, and (x,y) is the image coordinate. Within the exposure time T, the space target can be considered to be in uniform motion relative to the space-based monitoring platform, and its motion in the x and y directions of the camera is represented by the time functions x0(t) and y0(t) respectively. Then, within the exposure time T, the motion blurred image b(x,y) can be considered to be the grayscale average of the space target along the blur direction, which can be specifically expressed as:

[0064]

[0065] Performing Fourier transform on equation (9) and exchanging the order of integration yields:

[0066]

[0067] The degradation model undergoes Fourier transform, and according to the convolution theorem, the convolution in the spatial domain is converted into the convolution in the frequency domain:

[0068] B(u,v)=H(u,v)*K(u,v)+Γ(u,v)(11)

[0069] Among them, B(u,v) and H(u,v) represent the Fourier transform of the blurred source image and the clear image respectively, Γ is the Fourier transform of the noise, and K(u,v) is the blur kernel function in the frequency domain. By comparing equation (10) and equation (11), it can be seen that the blur kernel function is specifically expressed as:

[0070]

[0071] Converting the K(u,v) fuzzy kernel function to the spatial domain can obtain the linear uniform fuzzy kernel function, which is defined as:

[0072]

[0073] From equation (13), we can see that the blur kernel function is only related to the elongation angle and the elongation length. Therefore, we only need to obtain these two parameters to obtain the blur kernel function and derive a clear restored image.

[0074] Step 5-2. Lucy-Richardon algorithm is one of the most widely used image restoration technologies. It uses an iterative method and an accelerated convergence algorithm to restore the image. The Lucy-Richardon algorithm assumes that the pixels in the image satisfy the Poisson distribution. Based on the Bayesian conditional probability model, it uses maximum likelihood estimation to iteratively calculate the degraded image to solve the original clear image. The iterative equation is:

[0075]

[0076] Among them, f w (x, y) is the w-th iterative restoration result of the process of restoring the initial image to a clear image, f w+1 (x,y) is the restoration result of the w+1th iteration.

[0077] We can make f 0 (x,y)=b(x,y) as the initial condition for iteration. As w increases, f w+1 (x, y) will gradually converge to the ideal clear image h(x, y) according to probability, and extract the centroid coordinates (x ta ,y ta ).

[0078] Step 6. Track association;

[0079] The space target images in the restored image are track-correlated to distinguish different space target images and eliminate redundant and erroneous data. Figure 7 As shown, Figure 7 This is a schematic diagram of the principle of multi-space target track association. The coordinates of each suspicious target in the previous and next two frames are associated, and the x displacement, y displacement, x speed, y speed and other data are calculated to form a list of suspicious targets. The data in the list is filtered, and the erroneous data with too large moving speed is removed by the x displacement and y displacement thresholds. For example, g-3 in the figure may be eliminated. The data retained in the list will be iteratively entered into the processing of the third frame and subsequent frames.

[0080] The data in the suspicious list are associated with the suspicious targets in the third frame and subsequent frames. Since the space target moves in a circular orbit in a short period of time and the apparent motion speed of the target changes very little, the space target can be considered to move in a uniform straight line during the exposure time. By comparing the xy displacement and xy velocity vector, the redundant targets in the suspicious target list are removed again to complete the target track association.

[0081] In this implementation, in the process of associating the track of the restored elongated star image space target, missed detection and false detection are inevitable. Therefore, the mutual comparison method is used to eliminate the error points. The specific process is as follows:

[0082] Step 6-1. Assume that the measurement arc duration of the space target is τ, first determine three authentication points, the distance between them is more than τ / 4, and set the three authentication points to S1, S2, and S3.

[0083] Generally, the polynomial fitting method is used to obtain the visual trajectory of the space target on the image. Since the measurement arc of the space target is short, a quadratic polynomial is used to describe the trajectory of the target:

[0084]

[0085] Step 6-2. Substitute the three authentication points into the above formula, solve a0, a1, a2 and b0, b1, b2, and use these six coefficients to calculate the coordinates (x cal ,y cal ), and compare these values ​​with the centroid coordinates (x ta ,y ta ), the difference must satisfy:

[0086]

[0087] Where ε is the elimination threshold, which is related to the observation accuracy and is generally set to 1 to 2 pixels. If most of the restored space targets meet the conditions of formula (16), it means that the three authentication points are correct, and the restored space target centroids that do not meet the conditions of formula (16) are eliminated. If most of the target centroid coordinates do not meet the conditions of formula (16), it means that there are problems with these three points and the authentication points need to be replaced until the conditions are met.

[0088] Step 7. Astronomical positioning;

[0089] In this embodiment, the astronomical positioning of the space target is a positioning method that calculates the celestial coordinates of the space target based on the relative mapping relationship between the space target position in the image and the calibration stars. It is achieved by solving the plate constant model by establishing a relative mapping relationship between the celestial coordinates of the calibration stars and the image coordinates of the space target.

[0090] Step 7-1. By establishing the calibration star group (α subl ,δ subl ) and the image coordinates (x subi ,y subi ) and the negative constant model:

[0091]

[0092] Among them (α sub0 ,δ sub0 ) is the celestial coordinate of the center of each sub-field of view, sub=0~15, sub is the sub-field of view number, and also the core number of the multi-core parallel processor.

[0093]

[0094] Combining equations (17) and (18), the film constant (A) of each sub-field of view is solved by the least square method. sub ~F sub ).

[0095]

[0096] Step 7-2. Restore the centroid coordinates (x ta ,y ta ) into formula (19) to obtain the ideal coordinates of the space target star image (ζ ta ,η ta ), and substitute it into the following formula:

[0097]

[0098] After formula (20) is sorted out, the celestial coordinates of the space target star image (α ta ,δta ):

[0099]

[0100] At this point, the astronomical positioning of the elongated stars of space targets by the large-field-of-view space-based surveillance platform has been completed.

[0101] Specific implementation method 2: Combination Figure 8 The present embodiment is described. The present embodiment is a verification example of the method for astronomical positioning of elongated star images of space targets on a space-based surveillance platform with a large field of view as described in the first embodiment: In order to verify the restoration effect and astronomical positioning accuracy of the method for astronomical positioning of elongated star images of space targets on a space-based surveillance platform with a large field of view as described in the first embodiment, the method described in the present embodiment is used to restore a sequence of images of an elongated laser ranging star (space target) and conduct an astronomical positioning accuracy verification experiment. The two-row elements (TLE) of the laser ranging star are solved to obtain its celestial position. Since the orbit determination data of the laser ranging star has high accuracy, it can be used as the true value of the experiment, which is recorded as the C value. The target is astronomically positioned by using the traditional centroid algorithm and the method described in the present embodiment to restore the target center of mass using the fuzzy kernel function to restore the target, and the observed value is recorded as the O value. The positioning error OC value of each frame of the sequence image is recorded (i.e., the observed value minus the true value, where (OC) α is the right ascension direction, (OC) δ is the declination direction), and calculate the root mean square error of the target's astronomical positioning:

[0102]

[0103] Where N f is the number of frames of the sequence image. The star image restoration effect of the stretched space target sequence image is as follows: Figure 8 The calculation results of the astronomical positioning root mean square error are shown in Table 1. Table 1 shows the astronomical positioning error of the method of the present invention for the elongated target star image.

[0104] Table 1

[0105]

[0106] Table 2 shows the astronomical positioning error of the elongated target star image using the centroid method.

[0107] Table 2

[0108]

[0109] By comparing Table 1 and Table 2 above, it can be seen that the root mean square error (RMS value) of the astronomical positioning after the elongated space target star image restoration method described in this embodiment is much smaller than the astronomical positioning method of restoring the center of mass of the space target from the centroid when using the traditional method to deal with the elongated star image problem.

[0110] The technical features of the above-described embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above-described embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0111] The above-mentioned embodiments only express several implementation methods of the present invention, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for ordinary technicians in this field, several variations and improvements can be made without departing from the concept of the present invention, and these all belong to the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention shall be subject to the attached claims.

Claims

1. A method for astronomical positioning of space targets with elongated stars for a large-field-of-view space-based surveillance platform, characterized by: The method is implemented by the following steps: Step 1: Obtain observation images; Step 2: performing image preprocessing on the observation image described in step 1; Step 3: extract the star catalog, perform star map matching, establish the mapping relationship between the celestial coordinates of the calibration star and the image coordinates, and solve the plate constant model; Step 4: Adopting the adjacent frame image difference method to eliminate the stars in the observed image preprocessed in step 2 and extract the space target star image; Step 5: restore the elongated space target star image in the extracted space target star image to obtain the centroid coordinates of the space target restored image; the specific process is: Step 51: Use the minimum circumscribed rectangle to describe the length L and the elongated angle θ of the elongated space target star image, and construct a degradation model of astronomical image degradation caused by motion blur; Step 52: According to the degradation model, the motion blurred image of the elongated space target star image is restored to obtain the image coordinates of the restored space target; Step 6: Use the mutual comparison method to eliminate the error points and realize the track association of the space target star image in the restored image; Step 7: Complete accurate astronomical positioning of the space target star image that has completed track association.

2. The method for astronomical positioning of space targets with elongated stars for a space-based surveillance platform with a large field of view according to claim 1, characterized in that: The specific process of step one is: Step 11: Record the orbital instantaneous root and attitude parameters of the space-based monitoring platform and the guidance data fed back by the telescope motor encoder through the space-based monitoring platform telescope, and calculate the pointing direction of the telescope in celestial coordinates, that is, the center pointing direction of the telescope (C_Ra, C_Dec); Step 12: setting the exposure time T and the shooting time t of the camera to obtain a set of sequence images as observation images; Step 13: Divide the observed image into 16 sub-fields of view on average, and calculate the center direction (C) of each sub-field of view according to the center direction of the telescope. sub _Ra,C sub _Dec), where sub is the sub-field number; The sub-field of view number sub also serves as the number of the corresponding core of the embedded multi-core parallel processor carried by the space-based monitoring platform, sub=0~15.

3. The method for astronomical positioning of space targets with elongated stars for a space-based surveillance platform with a large field of view according to claim 1, characterized in that: In step 3, extract the star catalog: according to the central direction of the telescope (C_Ra, C_Dec), the celestial coordinates of the photographed area are solved by the calculation method of spherical astronomy, and the calibration star group (α l ,δ l ), l=1~N st , N st is the total number of stars extracted from the standard star catalog, then the sub-field of view corresponds to the calibration star group in the standard star catalog (α subl ,δ subl ).

4. The method for astronomical positioning of space targets with elongated stars for a large-field-of-view space-based surveillance platform according to claim 3 is characterized by: In step 3, the specific process of performing star map matching based on the extracted star catalog and establishing the film constant model is as follows: Step 3. Image coordinates of the first frame of the star image and calibration of the star group (α l ,δ l ) The triangle matching sub-graph isomorphism algorithm is used to perform star map matching, and the center position coordinates (α0, δ0) of the first frame image are obtained by star map matching; Step 32: According to the center position coordinates (α0, δ0) of the first frame image, solve the calibration star group (α l ,δ l )’s ideal coordinates (ζ i ,η i ), and uses the six-constant plate model to describe the image coordinates of the stars (x i ,y i ) and the ideal coordinates (ζ i ,η i ) to establish a mapping relationship between the celestial coordinates of the calibrated stars and the image coordinates; Step 33: According to the mapping relationship obtained in step 32, the center position coordinates (α sub0 ,δ sub0 ); the center position of each sub-field of view in the current frame (α sub0 ,δ sub0 ) is the center position of the previous frame (α sub0 ,δ sub0 )′ is updated and corrected according to the shooting time t and the guidance data of the telescope, thereby realizing the update and correction of the film constant.

5. The method for astronomical positioning of space targets with elongated stars for a space-based surveillance platform with a large field of view according to claim 4, characterized in that: In step 32, solve the calibration star group (α l ,δ l )’s ideal coordinates (ζ i ,η i )The formula is as follows: The six-constant plate model is used to describe the image coordinates (x i ,y i ) and the ideal coordinates (ζ i ,η i ) is as follows: Among them, A, B, C, D, E, and F are all film constants, Ω is the ratio of the camera pixel size to the focal length of the telescope, and the ideal coordinates (ζ i ,η i ) formula and mapping relationship, the plate constant is solved by least square fitting method, and the mapping relationship between the celestial coordinates of the calibrated stars and the image coordinates is established.

6. The method for astronomical positioning of space targets with elongated stars for a space-based surveillance platform with a large field of view according to claim 1, characterized in that: In step 4, the adjacent frame image difference method is used to remove stars from the observed image and extract the space target star image, and the configuration coefficient D is set, which is expressed as follows: In the formula, σ is the matching threshold, is the star image movement distance of the two frames of the sequence image, The moving distance of the space target star; When D=0, it means that the star image in the kth frame observation image and the star image in the k-1th frame observation image are both stellar star images; when D=1, it means that the star image in the kth frame observation image and the star image in the k-1th frame observation image are suspected to be space targets.

7. The method for astronomical positioning of space targets with elongated stars for a space-based surveillance platform with a large field of view according to claim 1, characterized in that: The specific process in step 51 is: Set the coordinates of the four vertices of the circumscribed rectangle to be A(x a ,y a ),B(x b ,y b ),C(x c ,y c ),D(x d ,y d ), the central axis of the rectangle's major axis intersects AB and CD at E(x e ,y e ),F(x f ,y f ), then the coordinates of the end points of the central axis EF are: The formula for the length L of the elongated space target star image and the elongation angle θ is as follows: Where n is the number of pixels occupied by the elongated space target star image in the x-axis direction, and m is the number of pixels occupied by the elongated space target star image in the y-axis direction; The degradation model of astronomical image quality caused by motion blur is constructed and expressed as follows: b(x,y)=h(x,y)*k(x,y)+γ(x,y) Where b(x,y) is the motion-stretched blurred image of the space target taken by the camera, h(x,y) is the ideal clear image, k(x,y) is the blur kernel function, and γ(x,y) is the additive noise.

8. The method for astronomical positioning of space targets with elongated stars for a space-based surveillance platform with a large field of view according to claim 7, characterized in that: The specific process of step 52 is: The degradation model is transformed into a frequency domain convolution by Fourier transform and convolution theorem: B(u,v)=H(u,v)*K(u,v)+Γ(u,v) Where B(u,v) is the Fourier transform of the blurred source image in the frequency domain, H(u,v) is the Fourier transform of the clear image in the frequency domain, Γ is the Fourier transform of the noise, and K(u,v) is the blur kernel function in the frequency domain; The fuzzy kernel function K(u,v) is converted to the spatial domain, and the linear uniform fuzzy kernel function is obtained as follows: The Lucy-Richardon algorithm is used to restore the motion blurred image and extract the centroid coordinates of the restored image of the space target.

9. The method for astronomical positioning of space targets with elongated stars for a space-based surveillance platform with a large field of view according to claim 1, characterized in that: In step six, the mutual comparison method is used to eliminate the error points. The specific process is as follows: Step 61: Set the measurement arc duration of the space target star image to τ, determine three authentication points, and set the distance between the three authentication points to τ / 4; The quadratic polynomial is used to describe the trajectory of the space target star image, which can be expressed as follows: Step 62: Solve the above trajectory formula of the three authentication points to obtain the coefficients a0, a1, a2 and b0, b1, b2, and calculate the coordinates (x cal ,y cal ), and compare the calculated coordinates on all frames with the centroid coordinates (x ta ,y ta ) comparison, expressed as follows: In the formula, ε is the elimination threshold. If the difference satisfies the above formula: the three authentication points are correct, and the restored center of mass of the space target that does not meet the conditions is eliminated; if the restored center of mass coordinates of the space target does not satisfy the above formula, it means that the three authentication points are incorrect and the authentication points need to be replaced until the conditions are met.

10. The method for astronomical positioning of space targets with elongated stars for a space-based surveillance platform with a large field of view according to claim 1, characterized in that: The specific process of step seven is: Step 7.1: Establish the calibration star group (α subl ,δ subl ) and the image coordinates (x subi ,y subi ) and the negative constant model: Step 7.2: Convert the image coordinates (x ta ,y ta ) The ideal coordinates of the space target star image are obtained through the plate constant model (ζ ta ,η ta ), and finally obtain the celestial coordinates of the space target star image (α ta ,δ ta ), to achieve the astronomical positioning of space targets and elongated stars of the large-field-of-view space-based surveillance platform.

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