Automatic planning method for space target observation mission based on sky cloud segment value

Abstract

The present invention relates to the field of optical observation technology for space targets, and in particular to an automatic planning method for space target observation tasks based on the value of sky cloud arc segments, including: S1: obtaining geographical location information of observation equipment and orbital parameters of space targets; S2: eliminating space targets that do not meet monitoring conditions; S3: using a cloud amount evaluation function to calculate the cloud amount evaluation value of the trajectory of the space target that currently meets the monitoring conditions; S4: sorting the observation priority of the space target that currently meets the monitoring conditions according to the cloud amount evaluation value, and the observation equipment observes the space target according to the observation priority of the space target to obtain observation data; S5: repeating steps S1 to S4 to obtain the observation data at the latest time until the observation task is completed. The present invention integrates sky background information and satellite trajectory information, timely grasps the observability of different satellites under current sky conditions, and improves the observation efficiency of space target observation tasks.

Description

Technical Field

[0001] The present invention relates to the technical field of optical observation of space targets, and in particular to an automatic planning method for space target observation tasks based on sky cloud segment values. Background Art

[0002] With the development and application of aerospace technology, scientific satellites, communication satellites, military satellites and meteorological satellites are emerging in an endless stream, and countries are competing to seize limited space orbits. While the number of satellites has increased dramatically, a large amount of space debris has also been generated, and space has become increasingly crowded. Therefore, the demand for space situational awareness has increased significantly. Using ground-based photoelectric telescopes to monitor and determine orbits of space targets is one of the important means of space situational awareness. It has the advantages of a wide observation range and high resolution, and can continuously monitor and determine orbits of space targets for a long time. However, ground-based photoelectric telescopes also face many challenges in practical applications, the most prominent of which is that their observation efficiency is greatly affected by meteorological conditions. Specifically, severe weather conditions such as cloud cover, haze, rain and snow will seriously affect the observation effect of ground-based photoelectric telescopes, and even lead to observation interruptions. This will not only reduce the real-time and accuracy of space situational awareness, but may also affect the ability to promptly warn and respond to space activities. Summary of the invention

[0003] In view of this, the present invention aims to provide an automatic planning method for space target observation tasks based on the sky cloud arc value, so as to solve the problem that the observation efficiency of ground-based optoelectronic telescopes is greatly affected by meteorological conditions. The present invention integrates sky background information and satellite trajectory information, timely grasps the observability of different satellites under current sky conditions, and improves the observation efficiency of space target observation tasks.

[0004] To achieve the above object, the technical solution created by the present invention is implemented as follows:

[0005] A method for automatically planning space target observation tasks based on sky cloud segment value specifically comprises the following steps:

[0006] S1: Obtain the geographical location information of the observation equipment and the orbital parameters of no less than two space targets;

[0007] S2: Calculate the trajectory information of all space targets passing through at the current moment, and eliminate space targets that do not meet the monitoring conditions;

[0008] S3: construct a cloud amount evaluation function, and use the cloud amount evaluation function to calculate the cloud amount evaluation values ​​of the trajectories of the space targets that currently meet the monitoring conditions in sequence;

[0009] S4: The space targets that currently meet the monitoring conditions are sorted according to the cloud amount evaluation value, and the observation equipment observes the space targets according to the observation priority of the space targets to obtain observation data;

[0010] S5: Replace the current time with the latest time, repeat steps S1 to S4, and obtain the observation data of the latest time until the observation task is completed.

[0011] Furthermore, in step S1, the geographic location information includes the longitude, latitude, altitude and current time of the observation device; the orbital parameters include the orbital semi-major axis, orbital eccentricity, orbital inclination, right ascension of the ascending node, argument of perigee and time of passing perigee.

[0012] Furthermore, in step S2, the trajectory information of the space target is represented as List(t, a, e), wherein t represents time, a represents the azimuth angle of the space target relative to the observation device at time t, and e represents the pitch angle of the space target relative to the observation device at time t.

[0013] Furthermore, in step S2, a space target with a pitch angle greater than ten degrees and a transit time greater than one minute is regarded as a space target that meets the monitoring conditions.

[0014] Furthermore, in step S3, the specific steps of constructing the cloud amount evaluation function are:

[0015] S301: Use the cloud device to capture the cloud image at the current moment, and mark the position coordinates of the hth pixel in the cloud image as Pixel h (x h ,y h ), where x h Represents the horizontal axis position of the h-th pixel in the cloud map, y h Represents the vertical axis position of the h-th pixel in the cloud image;

[0016] S302: Set the trajectory information of the space target that currently meets the monitoring conditions to List1 ( , , )、List2( , , ),……、List N ( , , );

[0017] S303: Get the trajectory information List of the current space target i ( , , )’s kth trajectory point Pos k Track information Pos k (t k , a k , e k ), and calculate the i-th pixel point of the current space target on the cloud map The distance from the center pixel of the cloud image :

[0018] ;

[0019] in, is the i-th pixel point of the space target on the cloud image The location coordinates of

[0020] S304: Take the center point O of the cloud map as the center of the circle, and Create a circle for the radius , and based on the circle Establish the spatial altitude angle between the observation device and the current space target and distance Functional relationship:

[0021] =fun( ) ;

[0022] Among them, fun() is the spatial altitude angle and distance The conversion function of is the maximum radius of the cloud image;

[0023] S305: Altitude angle to space and distance Derivative of the functional relationship to obtain the minimum value of the spatial altitude angle , and correspondingly record the minimum value of the angle change of the current space target in the azimuth direction :

[0024] ;

[0025] in, For Circle The maximum distance between each pixel point in the cloud and the central pixel point of the cloud map;

[0026] S306: replacing the current space target that meets the monitoring conditions with the next space target that meets the monitoring conditions, and repeating steps S303 to S305 until the calculation of all space targets that currently meet the monitoring conditions is completed;

[0027] S307: Based on all the space targets that currently meet the monitoring conditions obtained in step S306, calculate the differences in the azimuth and elevation angles of the space targets relative to the observation device in turn, and set the differences to be greater than the corresponding minimum values ​​at the same time. and the corresponding minimum value The spatial targets are eliminated to obtain the sequence of spatial targets to be calculated;

[0028] S308: Select a space target to be calculated from the sequence of space targets to be calculated, and add all the trajectory points Pos k (t k , a k , e k ) is mapped to the corresponding pixel position Pixel on the cloud map h (x h ,y h ), remove the overlapping mapping points, and obtain the mapping point set {Pixel k};

[0029] S309: Calculate the mapping point set {Pixel k} contains the sum of the values ​​of the mapping points contained in Val, and based on the starting trajectory point Pos of the current spatial target to be calculated s and the end track point Pos e , calculate the spatial angular distance of the current space target to be calculated ;

[0030] ;

[0031] S310: Construct a cloud amount evaluation function, and use the cloud amount evaluation function to calculate the cloud amount evaluation value E of the trajectory of the current space target to be calculated:

[0032] E=Val / Angle;

[0033] S311: Replace the current space target to be calculated with the next space target to be calculated, and repeat steps S308-S310 until the calculation of cloud amount evaluation values ​​of all space targets to be calculated is completed.

[0034] Furthermore, in step S301, Pixel h (x h ,y h ) takes a value of 0 or 1, where 0 represents that there is no cloud at the current pixel and 1 represents that there is cloud at the current pixel.

[0035] Further, in step S304:

[0036] fun( ) ;

[0037] ;

[0038] in, For The corresponding polynomial coefficient, m is the polynomial coefficient The number of In the cloud map The distance between the pixel point and the center pixel point of the cloud map, and Both Corresponding to the polynomial coefficients The coefficient of .

[0039] Furthermore, in step S4, the smaller the cloud cover evaluation value is, the higher the observation priority of the space target is.

[0040] Furthermore, the observation device includes a control module, and the control module is used to obtain orbital parameters of the space target.

[0041] Furthermore, in step S4, the priority sorting result is sent to the control module, and the control module guides the observation device to perform observation until the acquisition of the observation data is completed.

[0042] Compared with the prior art, the invention can achieve the following beneficial effects:

[0043] (1) The present invention creates an automatic planning method for space target observation tasks based on the sky cloud cover arc value, which combines the observation plan of the observation equipment with the sky cloud cover information to prevent the observation equipment from being blocked by clouds and affecting the observation effect.

[0044] (2) The method for automatically planning space target observation tasks based on the sky cloud segment value created by the present invention only requires inputting the orbital parameter library, station geographic coordinates and time information of the observation target, so as to formulate the observation plan of the space target in real time and conduct automatic observation of the space target, thereby saving the manpower cost of formulating the observation plan and processing the invalid observation data generated by cloud cover.

[0045] (3) The method for automatically planning space target observation tasks based on the sky cloud arc value created by the present invention improves the observation efficiency of the observation equipment and gives full play to the observation capability of the observation equipment.

[0046] (4) The method for automatically planning space target observation tasks based on the sky cloud segment value created by the present invention can provide users with real-time sky monitoring images combining full sky imaging and satellite trajectories, such as Figure 1 As shown, Figure 1 The gray areas in the image represent clouds, the black crescent shape represents the moon, and the lines of different colors represent different satellite tracks. Figure 1 It can be intuitively understood that under the current weather conditions, the satellites corresponding to the red satellite tracks are more suitable for observation, and the satellites corresponding to the blue satellite tracks may be affected by cloud cover, moonlight, etc., resulting in poor observation results or observation failure. Therefore, the present invention can very intuitively provide users with more reference information, greatly reducing the difficulty of satellite observation.

[0047] (5) The method for automatically planning space target observation tasks based on the sky cloud cover arc value created by the present invention can combine cloud cover information to calculate the cloud cover evaluation values ​​on the transit trajectories of different space targets.

[0048] (6) The method for automatically planning space target observation tasks based on the sky cloud segment value created by the present invention calculates the current status of the transiting satellite in real time, gives priority to observing the space targets that are least affected by cloud cover, and realizes the automation of space target observation tasks. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] The drawings constituting part of the present invention are used to provide a further understanding of the present invention. The exemplary embodiments and descriptions of the present invention are used to explain the present invention and do not constitute an improper limitation on the present invention. In the drawings:

[0050] Figure 1 The satellite trajectory effect diagram with full sky imaging as the background according to the present invention;

[0051] Figure 2 A flow chart of a method for automatically planning space target observation tasks based on sky cloud segment values ​​described in an embodiment of the present invention. DETAILED DESCRIPTION

[0052] In order to make the purpose, technical solution and advantages of the invention more clear, the invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described here are only used to explain the invention and do not constitute a limitation of the invention.

[0053] It should be noted that, in the absence of conflict, the embodiments of the present invention and the features in the embodiments may be combined with each other.

[0054] In the description of the present invention, it should be understood that the terms "center", "longitudinal", "lateral", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside" and the like indicate positions or positional relationships based on the positions or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the present invention. In addition, the terms "first", "second", etc. are only used for descriptive purposes, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, features defined as "first", "second", etc. may explicitly or implicitly include one or more of the features. In the description of the present invention, unless otherwise specified, "multiple" means two or more.

[0055] In the description of the invention, it should be noted that, unless otherwise clearly specified and limited, the terms "installation", "connection" and "connection" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the invention can be understood according to specific circumstances.

[0056] The present invention will be described in detail below with reference to the accompanying drawings and in combination with embodiments.

[0057] like Figure 2 As shown, the automatic planning method for space target observation tasks based on the sky cloud cover arc value of the present invention is characterized by the addition of prior information. The present invention realizes the automatic generation of observation plans by combining the sky cloud cover information and the space target trajectory information currently passing through the space, while significantly improving the observation efficiency of the observation equipment, saving human resources, and giving full play to the observation capabilities of the equipment.

[0058] The following is a brief introduction to the automatic planning method for space target observation tasks of the present invention, specifically: 1. Input the orbital parameters of L space targets, and calculate the orbital information of all M currently transiting space targets based on the orbital parameters of the space targets and the geographical location information of the observation equipment. 2. Screen the orbital information of the transiting space targets, and eliminate space targets that do not meet the space target monitoring conditions such as too low elevation angles and too short transit times. 3. For the remaining N transit targets, calculate the target transit trajectory of each space target in the coordinate system of the observation equipment during the transit period. 4. Combined with the current sky background image data and the transit trajectory information of the space target, evaluate the cloud cover on the transit trajectory of each space target, and sort them according to the principle that the less cloud cover on the transit trajectory, the higher the priority of the space target. 5. The observation equipment automatically gives priority to observing the space target with a high priority in step 4, and repeats the above steps after the observation of the space target is completed.

[0059] Example 1

[0060] The following describes in detail the automatic planning method for space target observation tasks based on the value of sky cloud arc segments, taking the satellite as the space target:

[0061] S1: Obtain the geographical location information of the observation device and input the orbital parameters of L satellites into the control module;

[0062] The geographical location information includes the longitude, latitude, altitude and current time of the observation equipment; the orbital parameters include the orbital semi-major axis, orbital eccentricity, orbital inclination, right ascension of the ascending node, argument of perigee and time of passing perigee.

[0063] The observation device includes a control module, which sends the sorting result to the control module of the observation device, and the control module guides the observation device to perform observation until the acquisition of observation data is completed.

[0064] S2: Calculate the trajectory information of all satellites passing by at the current moment, and remove satellites that do not meet the monitoring conditions;

[0065] The satellite's trajectory information is represented as List(t, a, e), where t represents time, a represents the azimuth of the satellite relative to the observation device at time t, and e represents the elevation angle of the satellite relative to the observation device at time t.

[0066] In step S2, satellites with a pitch angle greater than ten degrees and a transit time greater than one minute are regarded as satellites meeting the monitoring conditions.

[0067] S3: Construct a cloud amount evaluation function, and use the cloud amount evaluation function to sequentially calculate the cloud amount evaluation values ​​of the trajectories of the satellites that currently meet the monitoring conditions.

[0068] In step S3, the specific steps of constructing the cloud amount evaluation function are:

[0069] S301: Use the cloud device to capture the cloud image Img at the current moment (the imaging design of the cloud image Img satisfies the characteristic of geometric central symmetry), and mark the position coordinate of the hth pixel point in the cloud image as Pixel h (x h ,y h ), where x h Represents the horizontal axis position of the h-th pixel in the cloud map, y h Represents the vertical axis position of the h-th pixel in the cloud image;

[0070] In step S301, Pixel h (x h ,y h ) takes a value of 0 or 1, where 0 represents that there is no cloud at the current pixel and 1 represents that there is cloud at the current pixel.

[0071] S302: Set the trajectory information of the satellites that currently meet the monitoring conditions to List1 ( , , )、List2( , , ),……、List N ( , , ).

[0072] S303: Get the current satellite trajectory information List i ( , , )’s kth trajectory point Pos k Track information Pos k (t k , a k , e k ), after a trajectory point on the satellite is imaged on the cloud map, the i-th pixel point of the current satellite on the cloud map is calculated by the following formula The distance from the center pixel of the cloud image :

[0073] ;

[0074] in, is the i-th pixel of the satellite on the cloud image The location coordinates of .

[0075] S304: Take the center point O of the cloud map as the center of the circle, and Create a circle for the radius , and based on the circle Establish the spatial altitude angle between the observation device and the current satellite and distance The functional relationship of is obtained through experimental calibration, and the data set { :

[0076] =fun( ) ;

[0077] Among them, fun() is the spatial altitude angle and distance The conversion function of is the maximum radius of the cloud image.

[0078] The least square method is used, with orthogonal polynomials as the basis, and the fitting function is obtained through experimental data calibration according to the actual state of the observed equipment. , so that the fitting function Approach :

[0079] fun( ) ;

[0080] ;

[0081] Polynomial coefficients It is expressed as follows:

[0082] ;

[0083] in, For The corresponding polynomial coefficient, m is the polynomial coefficient The number of In the cloud map The distance between the pixel point and the center pixel point of the cloud map, and Both Corresponding to the polynomial coefficients The coefficient of .

[0084] S305: Altitude angle to space and distance The functional relationship of is derived as follows: = ( ),calculate ( ) in [0, R max ] range, and obtain the minimum value of the spatial altitude angle , and correspondingly record the minimum value of the current satellite's azimuth angle change :

[0085] ;

[0086] in, For Circle The maximum distance between each pixel in the cloud and the central pixel of the cloud.

[0087] S306: Replace the satellite that currently meets the monitoring conditions with the next satellite that meets the monitoring conditions, and repeat steps S303 to S305 until the calculation of all satellites that currently meet the monitoring conditions is completed.

[0088] S307: Based on all satellites currently meeting the monitoring conditions obtained in step S306, use the linear interpolation method to calculate the differences in the azimuth and elevation angles of the satellites relative to the observation device in turn, and make the differences greater than the corresponding minimum values ​​at the same time. and the corresponding minimum value Satellite removal, that is, interpolation trajectory information List i (t k ,a k ,e k ) in any two trajectory points, so that a k and e k The numerical interval is less than the corresponding minimum value and the corresponding minimum value , obtain the satellite sequence to be calculated.

[0089] S308: Select a satellite to be calculated from the sequence of satellites to be calculated, and in the trajectory information ListNew of the satellite to be calculated i Select any trajectory point Pos k (t k , a k , e k ), and map it to the corresponding pixel position in the cloud coordinates Pixel h . Track information List New i All trajectory point mappings can construct a point set, and the point set can be deduplicated to obtain {Pixel k}, Pixel k The value on the cloud map is 0 or 1, so the set of pixels can be calculated. k The cumulative sum of the values ​​of} is calculated as Val. In simple terms, all the trajectory points Posk(t k , a k , e k) is mapped to the corresponding pixel position Pixel on the cloud map h (x h ,y h ), remove the overlapping mapping points, and obtain the mapping point set {Pixel k}.

[0090] S309: Calculate the mapping point set of the current satellite to be calculated {Pixel k} contains the sum of the values ​​of the mapping points contained in Val, and based on the starting trajectory point Pos of the current satellite to be calculated s and the end track point Pos e , calculate the spatial angular distance of the current satellite to be calculated ;

[0091] .

[0092] S310: Construct a cloud amount evaluation function, and use the cloud amount evaluation function to calculate the cloud amount evaluation value E of the trajectory of the current satellite to be calculated:

[0093] E=Val / Angle.

[0094] S311: Replace the current satellite to be calculated with the next satellite to be calculated until the cloud amount evaluation value calculations of all satellites to be calculated are completed.

[0095] S4: Sort the satellites that currently meet the monitoring conditions by observation priority according to the cloud amount evaluation value, send the trajectory information of N satellites to the observation module in the form of files or data streams, and the observation equipment observes the satellites according to the observation priority of the satellites to obtain sufficient observation data.

[0096] The smaller the cloud amount evaluation value, the higher the satellite's observation priority. The priority sorting result is sent to the control module, and the control module guides the observation equipment to observe until the acquisition of observation data is completed.

[0097] S5: Replace the current time with the latest time, repeat steps S1 to S4, and obtain the observation data of the latest time until the observation task is completed.

[0098] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the disclosure of the present invention can be performed in parallel, sequentially or in different orders, as long as the desired results of the technical solution disclosed in the present invention can be achieved, and this document does not limit this.

[0099] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for automatically planning space target observation tasks based on sky cloud segment value, characterized by: The specific steps include: S1: Obtain the geographical location information of the observation equipment and the orbital parameters of no less than two space targets; S2: Calculate the trajectory information of all space targets passing through at the current moment, and eliminate space targets that do not meet the monitoring conditions; The trajectory information is expressed as List(t, a, e), where t represents time, a represents the azimuth angle of the space target relative to the observation device at time t, and e represents the pitch angle of the space target relative to the observation device at time t; S3: construct a cloud amount evaluation function, and use the cloud amount evaluation function to calculate the cloud amount evaluation values ​​of the trajectories of the space targets that currently meet the monitoring conditions in sequence; In step S3, the specific steps of constructing the cloud amount evaluation function are: S301: Use the cloud device to capture the cloud image at the current moment, and mark the position coordinates of the hth pixel in the cloud image as Pixel h (x h ,y h ), where x h Represents the horizontal axis position of the h-th pixel in the cloud map, y h Represents the vertical axis position of the h-th pixel in the cloud image; S302: Set the trajectory information of the space target that currently meets the monitoring conditions to List1 ( , , )、List2( , , ),……、List N ( , , ); S303: Get the trajectory information List of the current space target i ( , , )’s kth trajectory point Pos k Track information Pos k (t k , a k , e k ), and calculate the i-th pixel point of the current space target on the cloud map The distance from the center pixel of the cloud image : ； in, is the i-th pixel point of the space target on the cloud image The location coordinates of S304: Take the center point O of the cloud map as the center of the circle, and Create a circle for the radius , and based on the circle Establish the spatial altitude angle between the observation device and the current space target and distance Functional relationship: =fun( ) ; fun( ) ; ； Among them, fun() is the spatial altitude angle and distance The conversion function of is the maximum radius of the cloud image, For The corresponding polynomial coefficient, m is the polynomial coefficient The number of In the cloud map The distance between the pixel point and the center pixel point of the cloud map, and Both Corresponding to the polynomial coefficients The coefficient of S305: Altitude angle to space and distance Derivative of the functional relationship to obtain the minimum value of the spatial altitude angle , and correspondingly record the minimum value of the angle change of the current space target in the azimuth direction : ； in, For Circle The maximum distance between each pixel point in the cloud and the central pixel point of the cloud map; S306: replacing the current space target that meets the monitoring conditions with the next space target that meets the monitoring conditions, and repeating steps S303 to S305 until the calculation of all space targets that currently meet the monitoring conditions is completed; S307: Based on all the space targets that currently meet the monitoring conditions obtained in step S306, calculate the differences in the azimuth and elevation angles of the space targets relative to the observation device in turn, and set the differences to be greater than the corresponding minimum values ​​at the same time. and the corresponding minimum value The spatial targets are eliminated to obtain the sequence of spatial targets to be calculated; S308: Select a space target to be calculated from the sequence of space targets to be calculated, and add all the trajectory points Pos k (t k , a k , e k ) is mapped to the corresponding pixel position Pixel on the cloud map h (x h ,y h ), remove the overlapping mapping points, and obtain the mapping point set {Pixel k }; S309: Calculate the mapping point set {Pixel k } contains the sum of the values ​​of the mapping points contained in Val, and based on the starting trajectory point Pos of the current spatial target to be calculated s and the end track point Pos e , calculate the spatial angular distance of the current space target to be calculated ; ； S310: Construct a cloud amount evaluation function, and use the cloud amount evaluation function to calculate the cloud amount evaluation value E of the trajectory of the current space target to be calculated: E=Val / Angle; S311: replacing the current space target to be calculated with the next space target to be calculated, and repeating steps S308-S310 until the cloud amount evaluation value calculations of all space targets to be calculated are completed; S4: sorting the observation priorities of the space targets that currently meet the monitoring conditions according to the cloud amount evaluation values, and the observation equipment observing the space targets according to the observation priorities of the space targets to obtain observation data; S5: Replace the current time with the latest time, repeat steps S1 to S4, and obtain the observation data of the latest time until the observation task is completed.

2. The method for automatically planning space target observation tasks based on sky cloud segment value according to claim 1 is characterized in that: In step S1, the geographical location information includes the longitude, latitude, altitude and current time of the observation equipment; the orbital parameters include the orbital semi-major axis, orbital eccentricity, orbital inclination, right ascension of the ascending node, argument of perigee and time of perigee.

3. The method for automatically planning space target observation tasks based on sky cloud segment value according to claim 1 is characterized in that: In step S2, the space target with a pitch angle greater than ten degrees and a transit time greater than one minute is regarded as a space target that meets the monitoring conditions.

4. The method for automatically planning space target observation tasks based on sky cloud segment value according to claim 1 is characterized in that: In step S301, Pixel h (x h ,y h ) takes a value of 0 or 1, where 0 represents that there is no cloud at the current pixel and 1 represents that there is cloud at the current pixel.

5. The method for automatically planning space target observation tasks based on sky cloud segment value according to claim 1 is characterized in that: In step S4, the smaller the cloud cover evaluation value is, the higher the observation priority of the space target is.

6. The method for automatically planning space target observation tasks based on sky cloud segment value according to claim 1 is characterized in that: The observation device comprises a control module, and the control module is used to obtain the orbit parameters of the space target.

7. The method for automatically planning space target observation tasks based on sky cloud segment value according to claim 6 is characterized in that: In step S4, the priority sorting result is sent to the control module, and the control module guides the observation device to perform observation until the acquisition of the observation data is completed.

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