Giant constellation resource scheduling method for moving target tracking

Abstract

The invention provides a moving target tracking-oriented giant constellation resource scheduling method, and aims to solve the problems that the existing giant constellation has a large number of nodes, the requirement for storing massive resource information on a satellite by using traditional space-time grid coding is too strict, and the resource scheduling efficiency is too low by using a centralized algorithm. Space-time grid coding and storage rules are introduced, on-satellite autonomous inverse solution is carried out, a coverage calculation model is deduced, finally, distributed double-layer auction task allocation is realized by simulating an auction process based on a constellation clustering management and control architecture, and then an inter-cluster / inter-satellite task execution sequence is obtained. According to the method, the resource scheduling efficiency can be remarkably improved, and the method plays an important role in resource management and scheduling of giant constellations. In the future, the method can be widely applied to the field of efficient management and resource optimization of a large-scale satellite network, and further development of a giant constellation technology is promoted.

Description

Technical Field

[0001] The present invention relates to the technical field of satellite communication and navigation, and in particular to a method for scheduling resources of a giant constellation for mobile target tracking. Background Art

[0002] Currently, the number of satellites in a giant constellation is huge, and these satellites perform resource scheduling through traditional centralized algorithms, facing many challenges. Traditional space-time grid coding requires storing a large amount of resource information on satellites, which poses extremely high requirements on the storage capacity of satellites. In practical applications, each node of the giant constellation needs to frequently store and update a large amount of resource data, resulting in huge storage pressure and a complex and lengthy data update process. Secondly, due to the large scale of the giant constellation, the method of centralized management and scheduling of resources often leads to delays in calculation and scheduling when facing a large number of satellite nodes, thus affecting the response speed and resource utilization efficiency of the entire system. Traditional centralized resource scheduling methods are difficult to effectively cope with the complex and dynamic changes in resource requirements in a giant constellation and cannot meet the requirements for efficient and real-time resource scheduling in practical applications. In addition, in the face of sudden tasks or changes in resource requirements, existing centralized resource scheduling methods lack flexibility and autonomy, resulting in difficulties in achieving the efficiency and effect of resource scheduling in engineering applications.

[0003] In order to overcome the limitations of these traditional methods and improve the resource scheduling efficiency of giant constellations, new methods and technologies are urgently needed. The resource scheduling method based on distribution, combined with advanced space-time grid coding rules and constellation clustering management architecture, is expected to significantly improve the efficiency and flexibility of resource scheduling and provide a new solution for the efficient management and optimization of giant constellations.

[0004] Based on the above background analysis, a method for scheduling resources of a giant constellation for mobile target tracking is proposed to provide technical support for the in-orbit autonomous mission allocation of constellations in China. Summary of the Invention

[0005] The object of the present invention is to solve the problems in the prior art, and a method for scheduling resources of a giant constellation for mobile target tracking is proposed.

[0006] The present invention is realized through the following technical solutions. The present invention proposes a method for scheduling resources of a giant constellation for mobile target tracking, and the method includes the following steps:

[0007] Step 1: Divide the space at each level of the earth based on the theory of regional grid dissection to facilitate the establishment of a direct mapping relationship between binary cataloging and longitude and latitude;

[0008] Step 2: Constellation resource preprocessing: To address the constellation resource coverage issue, resource information is encoded based on the GeoSOT grid and stored in the onboard database for faster access.

[0009] Step 3: Implement a distributed network model of the constellation based on the cluster control architecture to achieve autonomous management and provide model support for the next step of double-layer auction resource scheduling;

[0010] Step 4: Establish the constellation auction rules corresponding to the auction value of the auction item, and conduct a double-layer auction for the constellation based on the real-time latitude and longitude of the mobile target.

[0011] Furthermore, in step 1, the space of each level of the earth is divided based on the regional gridding theory, so as to establish a direct mapping relationship between binary cataloging and longitude and latitude. The derivation process is as follows:

[0012] The earth is unfolded into a plane. In order to cover the entire surface and be able to express it in binary form, the range of the entire earth is defined as level 0. The earth is expanded into a 512°×512° plane, which is defined as level 1, 128° as level 2, and so on. 1° is a 9-level grid. 1° is expanded to 64′ again, and then expanded to a 64′×64′ grid. 1′×1′ is expanded to a 64″×64″ grid. This divided space grid is empowered and represented as the unique code of the grid at a specific level.

[0013] Further, the position coordinates (B, L) are converted into the code C code =c 1 c 2 c 3 c 4 ...c i The process is:

[0014] Step 1: Set n = 0, which represents the entire earth, and n = 1, C = c 1 When, according to

[0015]

[0016] Encode. This first line of code divides the earth into four regions, which is more convenient for expressing locations. When n>1, go to the next step;

[0017] Step 2: Convert the latitude and longitude coordinates (B, L) to degrees, minutes, and seconds (D B °M B 'S B .U B ″,D L °M L 'S L .U L″) in an expression form for facilitating the next binary conversion;

[0018] Step 3: Convert the longitude and latitude (D B °M B ′S B .U B ″, D L °M L ′S L .U L ″) of any point on the earth's surface into a binary code c 1 d 1 d 2 ...d 7 d 8 m 1 m 2 ...m 6 s 1 s 2 ...s 6 u 1 u 2 ...u 11 Characterize, and the corresponding conversion relationship is

[0019]

[0020] According to this formula, process D B into an 8-bit binary number Process M B into a 6-bit binary number Process S B into a 6-bit binary number Process U B into an 11-bit binary number For D L °M L ′S L .U L ″, perform the same processing;

[0021] Step 4: Concatenate the processed binary numbers to obtain a 31-bit binary number and Then perform mixed coding to generate a quaternary unique code C code = c 1 c 2 c 3 ...c i ...c level , where when i = 1, c i is represented by Equation 1, and when i ≥ 2, it is represented by the following formula;

[0022]

[0023] Step 5: Assume that the time of the task scenario is from T start to T end , with a time step of Δt. Divide the time period according to the time step, and each time period t i is a discrete time encoding This encoding is represented as a 64-bit binary encoding. Combine this time encoding with the spatial encoding of this time period to form a spatio-temporal encoding in the form of a binary tuple.

[0024] Furthermore, in Step 2, for the tasks of constellation remote sensing imaging for earth surveillance and near-earth moving target tracking, the method for calculating the satellite observation field of view's earth coverage range is to use the longitude and latitude encoding of the coverage area strip obtained by satellite earth pushbroom scanning, and adopt the ray method to determine whether the target is within the longitude and latitude of the coverage area obtained by inverse decoding; this ray method is used to determine whether a point is inside or on the boundary of a polygon. Its logic is to emit a ray from the target point along the positive x-axis or any ray, and count the number of intersections of this ray with the sides of the polygon. If the number of intersections is odd, the point is inside the polygon; if it is even, the point is outside the polygon. If the point exactly falls on the boundary of the polygon, it is also considered inside.

[0025] Furthermore, in Step 2, in the determination of constellation satellite tracking in the air, a method is adopted to judge whether the included angle between the direction of the line connecting satellite targets and the projection of the satellite flight direction on the plane where the line is located is within the satellite's reachable field of view. Here, the satellite's reachable field of view is the sum of the satellite's half field of view angle and the pitch angle of the satellite tracking turntable.

[0026] Furthermore, in Step 3, the constellation clustering control architecture divides the constellation into several clusters according to rules, and each cluster contains a cluster task management unit, a cluster resource management unit, and a task unit responsible for specific task execution.

[0027] Furthermore, in Step 4, the description of task auction is that the value of the task to the task management node conducting the auction is V bid , and an auction activity with independent value is carried out for multiple clusters of the giant constellation, represented as a set

[0028] A auction ={N,(V i ,F i ) i∈N ,p,C} (4)

[0029] where N = {1, 2,..., n} is the set of clusters participating in the auction, V i represents the set of possible private values of the i-th cluster for the task, and its probability distribution function is F i (V i ), the inter-domain private values are independent of each other, and each cluster participating in the auction determines its bid according to its private value Vi Submit a bid b i for the cluster i that wins the task win According to the executable sequence p it provides, the transaction price is C;

[0030] In the process of resource scheduling, this auction mechanism is applied as follows: The task management node acts as the auctioneer, and the task acts as the auction item. The initial bid of the task is determined by its value label , that is, whether it can achieve the observation of the target; The first round of bidding is carried out among the clusters within the constellation to compete for the execution right of the task; The set of clusters participating in the bidding is denoted as where cluster A k has a private value for the task of , that is, it can continuously observe the target within a certain period of time; The set of bids corresponding to the imaging strategy provided by the cluster is expressed as

[0031]

[0032] where is the bid value corresponding to cluster A k , which is defined as the system value of the strategy in the process of resource scheduling; The bidding rule is formulated so that the bidder who can achieve the longest observation time wins, and the transaction price is full payment. The currently winning cluster will provide the next strategy and enter the next round of bidding, and the inter-satellite bidding will be carried out within the cluster to enable the longest time observation by a single satellite to obtain the specific execution sequence of the satellites within the cluster. If the cluster obtained through a single round of bidding cannot achieve the full-process execution of the task , it will be extended to the multi-round bidding process. The bid provided by the task management node organizing the bidding will be based on the transaction price of the previous round, that is, except for the first round of bidding, the bid value of the task value in the subsequent rounds of bidding will be based on whether the longest observation can be achieved within the remaining time of the task as the initial bid; Under the constraint of the finite auction round k bid , the final auction transaction is achieved.

[0033] Furthermore, in step four, at the beginning of the auction, the tasks are sorted by priority. The tasks auctioned first have higher priority. When the auction of a task is completed, the satellites of the cluster corresponding to the moment of executing the task will not participate in the subsequent task bidding and will only bid during the idle period.

[0034] The beneficial effects of the present invention are:

[0035] The present invention proposes a giant constellation resource scheduling method for mobile target tracking. Aiming at the problems that the number of existing giant constellations is large, the requirements for storing massive resource information on the satellite using traditional space-time grid coding are too strict, and the efficiency of resource scheduling using centralized algorithms is too low, the method introduces space-time grid coding and storage rules, autonomously reverses and derives the coverage calculation model on the satellite, and finally realizes distributed two-layer auction task allocation through a simulated auction process based on the constellation clustering management and control architecture, thereby obtaining the inter-cluster / inter-satellite task execution sequence.

[0036] The present invention effectively improves the efficiency of giant constellation resource scheduling. By optimizing the space-time grid coding and storage rules, the on-board storage requirements are greatly reduced, and the flexibility and autonomy of constellation resource scheduling are enhanced. The distributed two-layer auction mechanism makes full use of the inter-cluster and inter-satellite collaboration capabilities to optimize the timeliness and accuracy of task execution. Compared with traditional centralized algorithms, the present invention can significantly improve resource scheduling efficiency and play an important role in resource management and scheduling of giant constellations. In the future, the present invention will be widely used in the field of efficient management and resource optimization of large-scale satellite networks, promoting the further development of giant constellation technology. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 It is a flow chart of the giant constellation double-tier auction algorithm of the present invention.

[0038] Figure 2 It is a schematic diagram of the satellite flight direction and earth observation area range described in the present invention.

[0039] Figure 3 It is a schematic diagram of the four vertices of the satellite earth observation area described in the present invention.

[0040] Figure 4 It is a schematic diagram of the satellite air coverage calculation method described in the present invention. DETAILED DESCRIPTION

[0041] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0042] Aiming at the needs of space-based remote sensing constellations to track mobile targets, a task planning method based on space-time grid coding is designed. The advantage of this method is that when planning tasks for large-scale constellations autonomously, the real-time status of the constellation can be obtained more quickly by calling the database code, and distributed computing is performed through the clustering management and control framework, which is superior to the traditional centralized algorithm in task planning efficiency. It is applicable to task allocation for various systems with multiple satellite networks. The details of the technical solution are as follows:

[0043] See also Figures 1-4 The present invention proposes a giant constellation resource scheduling method for mobile target tracking, the method comprising the following steps:

[0044] Step 1: Divide the earth's space at all levels based on the regional gridding theory to establish a direct mapping relationship between binary cataloging and longitude and latitude;

[0045] Step 2: Constellation resource preprocessing: To address the constellation resource coverage issue, resource information is encoded based on the GeoSOT grid and stored in the onboard database for faster access.

[0046] Step 3: Implement a distributed network model of the constellation based on the cluster control architecture to achieve autonomous management and provide model support for the next step of double-layer auction resource scheduling;

[0047] Step 4: Establish the constellation auction rules corresponding to the auction value of the auction item, and conduct a double-layer auction for the constellation based on the real-time latitude and longitude of the mobile target.

[0048] In step 1, the space of each level of the earth is divided based on the regional gridding theory, so as to establish a direct mapping relationship between binary cataloging and longitude and latitude. The derivation process is as follows:

[0049] The earth is unfolded into a plane. In order to cover the entire surface and be able to express it in binary form, the range of the entire earth is defined as level 0. The earth is expanded into a 512°×512° plane, which is defined as level 1, 128° as level 2, and so on. 1° is a 9-level grid. 1° is expanded to 64′ again, and then expanded to a 64′×64′ grid. 1′×1′ is expanded to a 64″×64″ grid. This divided space grid is empowered and represented as the unique code of the grid at a specific level.

[0050] Convert a position coordinate (B, L) to code C code =c 1 c 2 c 3 c 4 ...c i The process is:

[0051] Step 1: Set that when n = 0, it represents the whole Earth, and when n = 1, C = c 1 At this time, encode according to

[0052]

[0053] This first-line encoding divides the Earth into four regions, making it more convenient to express positions. When n > 1, proceed to the next step;

[0054] Step 2: Convert the longitude and latitude coordinates (B, L) into the form of (D B °M B ′S B .U B ″, D L °M L ′S L .U L ″) for the convenience of the next binary conversion;

[0055] Step 3: Convert the longitude and latitude (D B °M B ′S B .U B ″, D L °M L ′S L .U L ″) of any point on the Earth's surface into the binary code c 1 d 1 d 2 ...d 7 d 8 m 1 m 2 ...m 6 s 1 s 2 ...s 6 u 1 u 2 ...u 11 for representation. The corresponding conversion relationship is

[0056]

[0057] According to this formula, process D B into an 8-bit binary number Process M B into a 6-bit binary number Process S B into a 6-bit binary number Process U B into an 11-bit binary number For D L °M L ′S L.U L ″Process in the same way;

[0058] Step 4: Concatenate the processed binary numbers to obtain a 31-bit binary number and Then perform mixed coding to generate a quaternary unique code C code = c 1 c 2 c 3 ...c i ...c level , where when i = 1, c i is represented by Equation 1, and when i ≥ 2, it is represented by the following formula;

[0059]

[0060] Step 5: Assume that the time of the task scenario is from T start to T end , the time step is Δt, divide the time period according to the time step, and each time t i is a discrete time code This code is represented as a 64-bit binary code, and this time code and the spatial code of this time period are combined to form a spatio-temporal code in the form of a binary tuple.

[0061] In Step 2, for the tasks of constellation remote sensing imaging for ground surveillance and near-Earth moving target tracking, the calculation method of the satellite observation field-of-view ground coverage range is based on the longitude and latitude codes of the coverage area strips obtained by satellite pushbroom imaging of the ground. The ray method is used to determine whether the target is within the longitude and latitude of the coverage area obtained by inverse decoding; this ray method is used to determine whether a point is inside or on the boundary of a polygon. Its logic is to emit a ray from the target point along the positive x-axis or any ray, and count the number of intersections of this ray with the sides of the polygon. If the number of intersections is odd, the point is inside the polygon; if it is even, the point is outside the polygon. If the point exactly falls on the boundary of the polygon, it is also considered inside.

[0062] In Step 2, in the determination of constellation satellite tracking in the air, since the field of view of the observed target at the satellite altitude includes the Earth and space, and it is difficult to map the target at the satellite altitude on the spherical surface for ray method judgment, the method of judging whether the included angle between the direction of the connection line between satellite targets and the projection of the satellite flight direction in the plane where the connection line is located is within the satellite reachable field of view is selected. Here, the satellite reachable field of view is the sum of the satellite half field of view angle and the pitch angle of the satellite tracking turntable.

[0063] In Step 3, the constellation clustering control architecture divides the constellation into several clusters according to rules, and each cluster contains a cluster task management unit, a cluster resource management unit, and a task unit responsible for specific task execution.

[0064] In step 4, the description of the auction activity is that the value of the item to the auctioneer organizing the auction is V bid , and a sealed auction activity with independent private values is carried out for multiple bidders, characterized as a set

[0065] A auction ={N,(V i ,F i ) i∈N ,p,C} (4)

[0066] where N = {1, 2,..., n} is the set of clusters participating in the auction, V i represents the set of possible private values of the i-th cluster for the task, and its probability distribution function is F i (V i ), the private values between clusters are independent of each other, and each cluster participating in the auction submits a bid b i according to its private value V i , and the winning cluster i win makes a decision according to the executable sequence p it provides, and the transaction price is C;

[0067] In the process of resource scheduling, this auction mechanism is applied as follows: the task management node acts as the auctioneer, and the task is used as the auction item, and the initial bid of the task is determined by its value tag , that is, whether it can achieve the observation of the target; the first round of bidding is carried out among the clusters within the constellation to compete for the execution right of the task; the set of clusters participating in the bidding is denoted as where the private value of cluster A k for the task is , that is, it can continuously observe the target within a certain time; the set of bids corresponding to the imaging strategies provided by the cluster is expressed as

[0068]

[0069] where is the bid value corresponding to cluster A k , which is defined as the system value of the strategy in the process of resource scheduling; the bidding rule is formulated so that the bidder who can achieve the longest observation time wins, and the transaction price is full payment. The currently winning cluster will provide the next strategy and enter the next round of bidding, and the inter-satellite bidding is carried out within the cluster to enable the longest observation time with a single satellite to obtain the specific execution sequence of the satellites within the cluster. If the cluster obtained from a single round of bidding cannot achieve the task If the whole process is executed, it will be expanded to a multi-round auction process. The bids provided by the task management node organizing the auction will be based on the transaction price of the previous round. That is, except for the first round of auction, the bids for the auction task value of the remaining rounds will be based on whether the longest observation can be achieved within the remaining time of the task as the initial bid; in the limited auction round k bid Under the constraints, the final auction transaction was achieved.

[0070] In step 4, in order to achieve a reasonable allocation of constellation resources and resolve task conflicts, at the beginning of the auction, the tasks Priority sorting is performed, and the task auctioned first has a higher priority. When the task is auctioned, the satellites in the corresponding time cluster that executes the task will not participate in the subsequent task auction and will only bid during the idle period.

[0071] Example

[0072] The present invention proposes a cluster constellation resource scheduling method for mobile target tracking, the method comprising the following steps:

[0073] Step 1: Divide the earth's space at various levels based on the regional gridding theory to facilitate the establishment of a direct mapping relationship between binary cataloging and longitude and latitude.

[0074] Step 2: Implement constellation resource preprocessing. To address the constellation resource coverage problem, encode the latitude and longitude of a single satellite and the four vertices of the ground coverage area based on the space-time grid and store them in the on-board database for faster access. The satellite observation field coverage calculation method is:

[0075] For ground surveillance and near-ground moving target tracking, the execution unit satellite has strong maneuverability and carries a visible light camera payload. Its visible area is represented by

[0076]

[0077] Among them, α and β represent the range of satellite swing along the flight direction and vertical direction of the satellite node respectively. The range of satellite flight direction and earth observation area is as follows: Figure 2 As shown. P represents the satellite point, Q represents the projection point of the satellite on the earth, and O represents the center of the earth. The maximum side angle of the satellite perpendicular to the flight direction is and It can be obtained by the following formula

[0078]

[0079] The same calculation method as above is used to obtain and Respectively in the flight direction and the opposite direction. Thus, the latitudes and longitudes of points A, B, C, and D are obtained. These four points are the midpoints of the four sides of the coverage area, and from this, the vertices P 1 , P 2 , P 3 , P 4 coordinate latitude and longitude information. The area covered by satellite observations at each moment is stored in the on-board database in the form of codes by converting the latitude and longitude information of the four vertices of the rectangular area, as Figure 3 shown.

[0080] In the air tracking mission, the mission execution unit of the constellation is equipped with an air precision tracking camera, and the field of view range is the sum of the satellite half-field angle and the pitch angle of the tracking turntable The air coverage calculation method is as Figure 4 shown.

[0081] Establish a coordinate system with the current satellite position. At this time, the latitude and longitude of the satellite position O are known. Convert them to the current coordinate system. Let the origin position vector The target position vector is The satellite flight direction vector Is represented by the direction of the line connecting the next moment's latitude and longitude and the current latitude and longitude. The vector of the line connecting the satellite and the target Is represented as

[0082]

[0083] Calculate the line vector The projection on the XY plane where the satellite flight direction is located

[0084]

[0085] Calculate the line vector And The included angle between them. First, calculate the modulus of the line vector Modulus

[0086]

[0087] Calculate the modulus of the line vector projection Modulus

[0088]

[0089] Use the modulus to calculate the cosine value of the included angle

[0090]

[0091] Find out the included angle α

[0092]

[0093] By comparing α with the sum of the satellite's half field of view angle and the elevation angle of the tracking turntable If Then within the coverage area, the satellite can achieve observation and tracking; otherwise, it cannot. Thus, the calculation process of the sky coverage is completed.

[0094] Step 3: Implement a distributed network model of the constellation based on the cluster control architecture to achieve autonomous management. This cluster architecture is known and designed according to the constellation configuration;

[0095] Step 4: When the constellation is launched into orbit and starts working, the unified mission management node distributes target information to each cluster mission management node. The mission management node determines whether to perform ground monitoring and tracking or sky tracking according to the nature of the mission, and then transfers it to the resource management node. Through the database coding information stored on the satellite, the four vertices of the ground coverage area of each satellite or the satellite longitude and latitude information at each moment are decoded according to the coding rules. By auctioning the real-time longitude and latitude of the target, the inter-cluster / inter-satellite mission execution sequence is obtained to achieve resource scheduling.

[0096] The present invention is proposed in view of the large number of nodes in the existing giant constellation, the overly strict requirements for storing a large amount of resource information on the satellite using traditional spatio-temporal grid coding, and the too low efficiency of resource scheduling using centralized algorithms. The spatio-temporal grid coding rule is introduced. Only special information coding needs to be stored and decoded autonomously on the satellite. The coverage calculation model is deduced, and based on the constellation cluster architecture, through distributed double auctions, the inter-cluster / inter-satellite mission execution sequence is obtained. Effectively improves the resource scheduling efficiency of the giant constellation.

[0097] Although the present invention has been disclosed above with preferred embodiments, it is not intended to limit the present invention. Anyone familiar with this technology can make various modifications and decorations without departing from the spirit and scope of the present invention. Therefore, the protection scope of the present invention should be defined by the claims.

Claims

1. A method for scheduling resources of a giant constellation for tracking mobile targets, characterized in that: The method comprises the following steps: Step 1: Divide the earth's space at all levels based on the regional gridding theory to establish a direct mapping relationship between binary cataloging and longitude and latitude; Step 2: Constellation resource preprocessing: To address the constellation resource coverage issue, resource information is encoded based on the GeoSOT grid and stored in the onboard database for faster access. Step 3: Implement a distributed network model of the constellation based on the cluster control architecture to achieve autonomous management and provide model support for the next step of double-layer auction resource scheduling; Step 4: Establish the constellation auction rules corresponding to the auction value of the auction item, and conduct a double-layer auction for the constellation based on the real-time latitude and longitude of the mobile target.

2. The method according to claim 1, characterized in that: In step 1, the space of each level of the earth is divided based on the regional gridding theory, so as to establish a direct mapping relationship between binary cataloging and longitude and latitude. The derivation process is as follows: The earth is unfolded into a plane. In order to cover the entire surface and be able to express it in binary form, the range of the entire earth is defined as level 0. The earth is expanded into a 512°×512° plane, which is defined as level 1, 128° as level 2, and so on. 1° is a 9-level grid. 1° is expanded to 64′ again, and then expanded to a 64′×64′ grid. 1′×1′ is expanded to a 64″×64″ grid. This divided space grid is empowered and represented as the unique code of the grid at a specific level.

3. The method according to claim 2, characterized in that: Convert a position coordinate (B, L) to code C code =c1c2c3c4...c i The process is: Step 1: Set n = 0, representing the entire earth, and n = 1, C = c1, according to Encode. This first line of code divides the earth into four regions, which is more convenient for expressing locations. When n>1, go to the next step; Step 2: Convert the latitude and longitude coordinates (B, L) to degrees, minutes, and seconds (D B °M B 'S B .U B ″,D L °M L 'S L .U L ″) to facilitate binary conversion in the next step; Step 3: Convert the longitude and latitude (D B °M B 'S B .U B ″,D L °M L 'S L .U L ″) is converted into binary code c1d1d2...d7d8m1m2...m6s1s2...s6u1u2...u 11 Characterization, the corresponding conversion relationship is According to this formula, D B Processed as 8-bit binary number M B Processed as 6-bit binary number S B Processed as 6-bit binary number Will U B Processed as 11-bit binary number For D L °M L 'S L .U L "The same treatment is carried out; Step 4: Concatenate the processed binary numbers to get a 31-bit binary number as well as Then perform mixed coding to generate a quaternary unique code C code =c1c2c3...c i ...c level , where when i=1, c i It is expressed by formula 1. When i≥2, it is expressed by the following formula: Step 5: Assume that the time of the task scenario is from T start to T end , the time step is Δt, the time period is divided according to the time step, each time t i Discrete time encoding The code is expressed as a 64-bit binary code, which is composed of the time code and the space code of this period. Spatiotemporal encoding in binary form.

4. The method according to claim 3, characterized in that: In step two, for the tasks of constellation remote sensing imaging for ground monitoring and near-ground moving target tracking, the method for calculating the ground coverage range of the satellite observation field of view is to use the ray method to determine whether the target is within the longitude and latitude of the coverage area obtained by inverse decoding based on the longitude and latitude codes of the coverage area strips obtained by satellite ground push scanning; the ray method is used to determine whether a point is inside or on the boundary of a polygon. Its logic is to send a ray from the target point along the positive direction of the x-axis or any ray, and count the number of intersections of this ray with each side of the polygon. If the number of intersections is odd, the point is inside the polygon; if it is even, the point is outside the polygon. If the point happens to fall on the boundary of the polygon, it is also considered inside.

5. The method according to claim 4, characterized in that: In step 2, in the constellation satellite air tracking judgment, the method of judging whether the angle between the direction of the line connecting the satellite targets and the projection of the satellite flight direction on the plane where the line is located is within the satellite's reachable field of view is adopted. Here, the satellite's reachable field of view is the sum of the satellite's half field of view angle and the pitch angle of the satellite tracking turntable.

6. The method according to claim 5, characterized in that: In step three, the constellation cluster management and control architecture divides the constellation into several clusters according to the rules. Each cluster contains a cluster task management unit, a cluster resource management unit, and a task unit responsible for the execution of specific tasks.

7. The method according to claim 6, characterized in that: In step 4, the description of task auction is that the value of the task management node for the task auction is V bid , an auction with independent value is launched for multiple clusters of a giant constellation, represented as a set A auction ={N,(V i ,F i ) i∈N ,p,C} (4) Where N = {1, 2, ..., n} is the set of clusters participating in the auction, V i represents the possible private value set of the i-th cluster for the task, and its probability distribution function is F i (V i ), the private values ​​between domains are independent of each other, and each cluster participating in the auction is determined by its private value V i Submit Bid i , cluster i that wins the task win According to the executable sequence p provided by it, the transaction price is C; In the resource scheduling process, this auction mechanism is applied as follows: the task management node acts as the auctioneer, and the task As an auction item, the initial bid for a task is determined by its value tag Determine whether the target can be observed; the first round of bidding is carried out by clusters in the constellation to compete for the execution right of the task; the cluster set participating in the bidding is recorded as Cluster A k The private value for the task is That is, it can continuously observe the target within a certain period of time; the quotation set corresponding to the imaging strategy provided by the cluster is expressed as in, Cluster A k The corresponding bid value is defined as the system value of the strategy in the resource scheduling process; the auction rules are formulated so that the bidder who can achieve the longest observation time wins, and the transaction price is paid in full. The current winning cluster will provide the next strategy and enter the next level of auction. Inter-satellite auctions are conducted within the cluster to obtain the specific execution sequence of satellites within the cluster based on the longest observation time achieved by a single satellite. If the cluster obtained in a single round of auction cannot achieve the task If the whole process is executed, it will be expanded to a multi-round auction process. The bids provided by the task management node organizing the auction will be based on the transaction price of the previous round. That is, except for the first round of auction, the bids for the auction task value of the remaining rounds will be based on whether the longest observation can be achieved within the remaining time of the task as the initial bid; in the limited auction round k bid Under the constraints, the final auction transaction was achieved.

8. The method according to claim 7, characterized in that: In step 4, at the beginning of the auction, the task Priority sorting is performed, and the task auctioned first has a higher priority. When the task is auctioned, the satellites in the corresponding time cluster that executes the task will not participate in the subsequent task auction and will only bid during the idle period.

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