Multi-satellite cooperative three-dimensional observation method and device

Abstract

The application discloses a kind of multi-satellite coordination three-dimensional observation method and device, the method includes: obtaining observation task set, target satellite set and load information;The observation task set, the target satellite set and the load information are processed, and the task satellite detailed information set is obtained;Based on the load information, using three-dimensional digital globe, the task satellite detailed information set is processed to three-dimensional visualization simulation, and multi-satellite coordination three-dimensional visualization observation result is obtained.The application provides a kind of multi-satellite coordination three-dimensional observation method and device, overcomes the limitation and error existing in single satellite observation, makes difficult space information visualized and intuitive, improves the efficiency of data analysis and processing.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of satellite observation, in particular to a multi-satellite cooperative three-dimensional observation method and device. BACKGROUND

[0002] In the existing satellite task planning research, a single satellite flies in orbit, and a two-dimensional scanning band with a certain width centered on the sub-satellite point can be observed by using attitude maneuver. The spatial information mainly exists in the form of graphics. However, it is very abstract to display spatial information with a two-dimensional graphical interface, and only professionals can understand it.

[0003] In the task planning process, a task point may have multiple time windows with a satellite, or may not be visible to multiple satellite nodes. Single satellite observation has limitations and errors. Due to the limitations of satellite on-orbit motion, field of view angle of satellite-borne remote sensing equipment, and side swing range of satellite-borne remote sensing equipment, the satellite can only observe the ground task point in a limited time window, and sometimes the ground task point is even invisible within the planning time. Compared with two-dimensional visualization, three-dimensional visualization provides a more abundant and realistic platform for the display of spatial information, visualizes and intuitively abstract spatial information, and users can understand it combined with their own relevant experience, so as to make accurate and rapid judgments. SUMMARY

[0004] The technical problem to be solved by the present application is to provide a multi-satellite cooperative three-dimensional observation method and device, which overcomes the limitations and errors of single satellite observation, visualizes and intuitively abstracts difficult spatial information, and improves the efficiency of data analysis and processing.

[0005] To solve the above technical problems, the first aspect of the embodiment of the present application discloses a multi-satellite cooperative three-dimensional observation method, characterized in that the method comprises:

[0006] S1, obtaining an observation task set, a target satellite set, and load information;

[0007] S2, processing the observation task set, the target satellite set, and the load information to obtain a task satellite detailed information set;

[0008] S3, based on the load information, using a three-dimensional digital globe to perform three-dimensional visualization simulation processing on the task satellite detailed information set to obtain a multi-satellite cooperative three-dimensional visualization observation result.

[0009] As an optional implementation manner, in the first aspect of the embodiment of the present application, the processing of the observation task set, the target satellite set, and the load information to obtain a task satellite detailed information set comprises:

[0010] S21, processing the observation task set and the target satellite set to obtain a multi-satellite cooperative observation task set;

[0011] S22, processing the multi-satellite cooperative observation task set to obtain all cooperative observation tasks;

[0012] S23, processing any cooperative observation task based on the load information to obtain task satellite detailed information;

[0013] S24, arranging all the task satellite detailed information in a sequence to obtain a task satellite detailed information set.

[0014] As an optional implementation, in the first aspect of the embodiment of the present application, the processing of the observation task set and the target satellite set to obtain a multi-satellite cooperative observation task set comprises:

[0015] S211, traversing the observation task set to obtain all observation tasks; traversing the target satellite set to obtain all task satellite information;

[0016] S212, processing any observation task to obtain point task information and area task information;

[0017] S213, processing any task satellite information to obtain first orbit data information and second orbit data information;

[0018] S214, fusing the point task information, the area task information, the first orbit data information and the second orbit data information to obtain a satellite cooperative observation task;

[0019] S215, arranging all the satellite cooperative observation tasks in a time sequence to obtain a multi-satellite cooperative observation task set.

[0020] As an optional implementation, in the first aspect of the embodiment of the present application, the processing of any cooperative observation task based on the load information to obtain task satellite detailed information comprises:

[0021] S231, processing the cooperative observation task based on the load information by using an orbit calculation model to obtain satellite orbit coordinate data information;

[0022] S232, processing the satellite orbit coordinate data information based on the load information by using a satellite subsatellite point longitude and latitude calculation model to obtain satellite subsatellite point strip information;

[0023] S233, Based on the payload information, the collaborative observation task is processed using the satellite side-swing latitude and longitude calculation model to obtain satellite side-swing strip information;

[0024] S234, Based on the satellite coverage calculation model, the satellite nadir point strip information, the satellite side-swing strip information and the observation task set are processed to obtain the satellite strip task intersection coordinate set;

[0025] S235, the satellite orbital coordinate data information and the satellite strip mission intersection coordinate set are fused to obtain detailed mission satellite information.

[0026] As an optional implementation, in the first aspect of the present invention, the orbit calculation model expression is:

[0027]

[0028] Where a represents the semi-major axis of the orbit; t0 represents the given time; r0 represents the satellite's position at time t0; v0 represents the satellite's velocity at time t0; t represents the current time; r represents the satellite's position at time t; v represents the satellite's velocity at time t; ΔE represents the difference in aperimeter angle between the current time and the given time; and μ represents the gravitational constant.

[0029] As an optional implementation, in the first aspect of the present invention, the step of processing the satellite orbit coordinate data information based on the payload information using a satellite nadir latitude and longitude calculation model to obtain satellite nadir strip information includes:

[0030] S2321, Using the satellite nadir latitude and longitude calculation model, coordinate transformation processing is performed on the satellite orbit coordinate data to obtain the station center horizontal rectangular coordinate information;

[0031] S2322, using the satellite sub-satellite point latitude and longitude calculation model, the station center horizontal rectangular coordinate information is processed by coordinate transformation to obtain the station center polar coordinate information;

[0032] S2323, The payload information is calculated and processed to obtain the satellite overpass scan strip;

[0033] S2324, using the station center polar coordinate information, the satellite transit scan strip is processed to obtain the satellite nadir point strip information.

[0034] As an optional implementation, in the first aspect of the present invention, the expression for the satellite sub-satellite point latitude and longitude calculation model is as follows:

[0035]

[0036] Where (L0, B0) represent geodetic coordinates (latitude and longitude); (X0, Y0, Z0) represent sphere-centered rectangular coordinates; (X, Y, Z) represent sphere-centered rectangular coordinates; (x, y, z) represent station-centered horizontal rectangular coordinates; R represents the slope distance between the station and the target point; A represents the slope distance azimuth angle between the station and the target point; and y represents the slope distance elevation angle between the station and the target point.

[0037] As an optional implementation, in the first aspect of the present invention, the step of processing the satellite nadir strip information, the satellite side-swing strip information, and the observation task set based on the satellite coverage calculation model to obtain the satellite strip task intersection coordinate set includes:

[0038] Using the satellite coverage calculation model, the satellite nadir point strip information output by the satellite nadir point calculation model, the satellite side-slip strip information output by the satellite side-slip calculation model, and the observation task set are subjected to intersection calculation processing to obtain the satellite strip task intersection coordinate set;

[0039] The expression for the satellite coverage calculation model is as follows:

[0040] C = A∩B∩R;

[0041] Where C represents coverage; A represents satellite nadir strip information; and B represents satellite side-swing strip information.

[0042] A second aspect of this invention discloses a multi-satellite collaborative three-dimensional observation device, the device comprising:

[0043] The acquisition module is used to acquire the observation task set and the target satellite set;

[0044] The first processing module is used to process the observation task set and the target satellite set to obtain a detailed information set of the mission satellites;

[0045] The second processing module is used to perform three-dimensional visualization simulation processing on the detailed information set of the mission satellites based on a three-dimensional globe, so as to obtain multi-satellite collaborative three-dimensional visualization observation results.

[0046] A third aspect of this invention discloses another multi-satellite collaborative three-dimensional observation device, characterized in that the device comprises:

[0047] Memory containing executable program code;

[0048] A processor coupled to the memory;

[0049] The processor calls the executable program code stored in the memory to execute some or all of the steps in the multi-satellite collaborative three-dimensional observation method disclosed in the first aspect of the present invention.

[0050] The fourth aspect of the present invention discloses a computer-readable storage medium storing computer instructions, which, when invoked, are used to execute some or all of the steps in the multi-satellite collaborative three-dimensional observation method disclosed in the first aspect of the present invention.

[0051] Compared with the prior art, the embodiments of the present invention have the following beneficial effects:

[0052] In this embodiment of the invention, during mission planning, reasonable coverage results are provided for each on-orbit satellite within a specified time. Multi-satellite collaborative observation can fully utilize the advantages and complementarities of each satellite to achieve efficient and comprehensive observation of the mission or region. Simultaneously, using a three-dimensional sphere as a background, multi-satellite information, satellite transit scan effect information, multi-object information, and timeline effect information are displayed (the satellite position at a specific moment can be viewed by manually dragging the timeline). This intuitively presents the observation results, overcoming the limitations and errors of single-satellite observation, visualizing and intuitively representing complex spatial information, and improving the efficiency of data analysis and processing. Attached Figure Description

[0053] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0054] Figure 1 This is a flowchart illustrating a multi-satellite collaborative three-dimensional observation method disclosed in an embodiment of the present invention;

[0055] Figure 2 This is a schematic diagram of the structure of a multi-satellite collaborative three-dimensional observation device disclosed in an embodiment of the present invention;

[0056] Figure 3 This is a schematic diagram of another multi-satellite collaborative three-dimensional observation device disclosed in an embodiment of the present invention;

[0057] Figure 4 This is a simulation effect diagram of a multi-satellite collaborative three-dimensional observation method disclosed in an embodiment of the present invention. Detailed Implementation

[0058] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0059] The terms "first," "second," etc., used in the specification, claims, and accompanying drawings of this invention are used to distinguish different objects, not to describe a specific order. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, apparatus, product, or device that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or devices.

[0060] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of the invention. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0061] In this application, the term "exemplary" is used to mean "used as an example, illustration, or description." Any embodiment described as "exemplary" in this application is not necessarily to be construed as being more preferred or advantageous than other embodiments. The following description is provided to enable any person skilled in the art to make and use this application. Details are set forth in the following description for purposes of explanation. It should be understood that those skilled in the art will recognize that this application can be made without using these specific details. In other instances, well-known structures and processes are not described in detail to avoid obscuring the description of this application with unnecessary detail. Therefore, this application is not intended to be limited to the embodiments shown, but is consistent with the broadest scope of the principles and features disclosed in this application.

[0062] It should be noted that since the method in this application embodiment is executed in a computer device, the processing objects of each computer device exist in the form of data or information, such as time, which is essentially time information. It is understood that if size, quantity, position, etc. are mentioned in subsequent embodiments, they are all corresponding data that exist so that the computer device can process them. Specific details will not be elaborated here.

[0063] It should be noted that the artificial intelligence-related technologies that may be involved in this application will be briefly described. Artificial intelligence (AI) is the theory, method, technology, and application system that uses digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, perceive the environment, acquire knowledge, and use that knowledge to obtain optimal results. In other words, artificial intelligence is a comprehensive technology in computer science that attempts to understand the essence of intelligence and produce a new kind of intelligent machine that can react in a way similar to human intelligence. Artificial intelligence is the study of the design principles and implementation methods of various intelligent machines, enabling machines to have the functions of perception, reasoning, and decision-making.

[0064] Artificial intelligence (AI) is a comprehensive discipline encompassing a wide range of fields, including both hardware and software technologies. Fundamental AI technologies generally include sensors, dedicated AI chips, cloud computing, distributed storage, big data processing, operating / interactive systems, and mechatronics. AI software technologies primarily include computer vision, speech processing, natural language processing, and machine learning / deep learning.

[0065] Computer vision (CV) is a science that studies how to enable machines to "see." More specifically, it refers to machine vision, which uses cameras and computers to replace human eyes in recognizing and measuring targets, and then performs image processing to create images more suitable for human observation or transmission to instruments. As a scientific discipline, computer vision studies related theories and technologies, attempting to build artificial intelligence systems capable of extracting information from images or multidimensional data. Computer vision technologies typically include image processing, image recognition, image semantic understanding, image retrieval, OCR, video processing, video semantic understanding, video content / behavior recognition, 3D object reconstruction, 3D technology, virtual reality, augmented reality, simultaneous localization and mapping (SLAM), and common biometric recognition technologies such as facial recognition and fingerprint recognition.

[0066] Monomodal information refers to data of only one type, such as text, images, audio, video, or electromagnetic signals. Multimodal information refers to data that includes at least two types of monomodal information. Furthermore, multimodal information is suitable for complex tasks that require the integration of multiple information sources, such as sentiment analysis, robot interaction, and autonomous driving. By integrating information from multiple modalities, higher performance and accuracy can usually be achieved in these tasks.

[0067] Large models refer to artificial neural network models with a very large number of parameters. In the field of artificial intelligence, large models typically refer to models with hundreds of millions to trillions of parameters. These models usually need to be trained on large-scale datasets and require a significant amount of computing resources for optimization and tuning. Large models are commonly used to solve complex tasks such as natural language processing, computer vision, and speech recognition. Generative AI is a type of AI that can create new content and ideas, including dialogues, stories, images, videos, and music. In this embodiment, the large model can be a language model of the scale of ChatGPT, BERT, XLNet, Zhipu model, Claude, Moonshot AI model, ChatGLM model, Qianyitongwen model, MiniMax model, Xinghuo model, Llama model, 360GPT model, Qwen model, Baichuan model, Yunque model, vivoLM model, and Wenxin Yiyan, etc., and this embodiment does not limit the scope of the large model.

[0068] This invention discloses a multi-satellite collaborative three-dimensional observation method and device, which overcomes the limitations and errors of single-satellite observation, visualizes and intuitively presents difficult-to-understand spatial information, and improves the efficiency of data analysis and processing.

[0069] Example 1

[0070] Please see Figure 1 , Figure 1 This is a flowchart illustrating a multi-satellite collaborative three-dimensional observation method disclosed in an embodiment of the present invention. Figure 1 The described multi-satellite collaborative three-dimensional observation method is applied to satellite observation systems, such as local servers or cloud servers used for satellite observation system management; however, this embodiment of the invention is not limited to such applications. Figure 1 As shown, this multi-satellite collaborative three-dimensional observation method may include the following operations:

[0071] S1, acquires the observation task set, target satellite set, and payload information;

[0072] It should be noted that the observation task set includes a point task set and a regional task set;

[0073] It should be noted that the point task set includes several point tasks; the point tasks are represented in the form of a one-dimensional array.

[0074] It should be noted that the set of regional tasks includes several regional tasks; the regional tasks are represented in the form of a two-dimensional array with the first and last elements connected.

[0075] It should be noted that the target satellite set includes several target satellites; the target satellites are satellites designated for the observation target area.

[0076] It should be noted that the payload information includes electronic payload information, optical payload information, and SAR (Synthetic Aperture Radar) payload information;

[0077] It should be noted that the electronic payload information includes: (1) visibility rule: nadir point; (2) coverage constraint: global range ±60; (3) energy constraint: single-cycle working time not exceeding 40 minutes; (4) motion constraint: interval between two missions not less than 5 minutes;

[0078] It should be noted that the optical payload information includes: (1) Visibility rule: nadir point; (2) Coverage constraint: continuously adjustable ±45; (3) Illumination: illuminated area; (4) Energy constraint: single-loop imaging time 10 minutes; (5) Motion constraint: interval between two consecutive side swings not less than 8 minutes; (6) Imaging resolution: 0.5m-2m; (7) Imaging swath width: 30km-300km;

[0079] It should be noted that the SAR payload information includes: (1) visibility rule: side view; (2) coverage constraint: variable from 30 to 60 degrees left and right; (3) energy constraint: single-loop imaging time of 8 minutes; (4) motion constraint: left and right test conversion time of 5 minutes; (5) imaging resolution: 1m-20m; (6) imaging swath width: 10km-1000km.

[0080] It should be noted that the interval time is used to describe the time it takes for a satellite to pass through a specified area;

[0081] S2, process the observation task set, the target satellite set, and the payload information to obtain a detailed task satellite information set;

[0082] It should be noted that the aforementioned mission satellite detailed information set includes several pieces of mission satellite detailed information;

[0083] It should be noted that the detailed information about the mission satellite includes two lines of orbital data for the mission satellite;

[0084] It should be noted that the two rows of track data include the first row of track data and the second row of track data; the first row of track data is as shown in Table 1; the second row of track data is as shown in Table 2;

[0085] Table 1, first row, describes the format of the track data.

[0086]

[0087]

[0088] Table 2, row 2, description of the track data format.

[0089] Serial number Field serial number Description 1 01 Orbit line number 2 03-07 Satellite number (international code) 3 09-16 Satellite orbit inclination (in degrees) 4 18-25 Longitude of ascending node (in degrees) 5 27-33 Eccentricity (in decimal fraction) 6 35-42 Argument of perigee (in degrees) 7 44-51 Longitude of perigee (in degrees) 8 53-63 Mean motion (revolutions per day) 9 64-68 Epoch orbit number (counting from the first revolution) 10 69 Check code

[0090] S3, based on the payload information, use a three-dimensional digital globe to perform three-dimensional visualization simulation processing on the mission satellite detailed information set to obtain multi-satellite collaborative three-dimensional visualization observation results;

[0091] As can be seen, the multi-satellite collaborative three-dimensional observation method described in the embodiments of the present invention overcomes the limitations and errors of single-satellite observation, visualizes and intuitiveizes difficult-to-understand spatial information, and improves the efficiency of data analysis and processing.

[0092] In an optional embodiment, step S2 above, which involves processing the observation task set, the target satellite set, and the payload information to obtain a detailed task satellite information set, includes:

[0093] S21, Process the observation task set and the target satellite set to obtain a multi-satellite collaborative observation task set;

[0094] S22, Process the multi-satellite collaborative observation task set to obtain all collaborative observation tasks;

[0095] It should be noted that the processing of the multi-satellite collaborative observation task set to obtain all collaborative observation tasks includes:

[0096] S221, Traverse the set of multi-satellite collaborative observation tasks to obtain all satellite collaborative observation tasks;

[0097] S222, The satellite collaborative observation task is analyzed and processed to obtain the satellite observation task;

[0098] The parsing process refers to obtaining the satellite observation task using the field identifier bit;

[0099] S223, all satellite observation tasks are arranged in sequence to obtain all collaborative observation tasks;

[0100] S23, Based on the payload information, process any of the cooperative observation tasks to obtain detailed information about the mission satellites;

[0101] S24. Arrange all the mission satellite details in chronological order to obtain the mission satellite details set.

[0102] As can be seen, the multi-satellite collaborative three-dimensional observation method described in the embodiments of the present invention overcomes the limitations and errors of single-satellite observation, visualizes and intuitiveizes difficult-to-understand spatial information, and improves the efficiency of data analysis and processing.

[0103] In another optional embodiment, step S21 above, which involves processing the observation task set and the target satellite set to obtain a multi-satellite collaborative observation task set, includes:

[0104] S211, Traverse the observation task set to obtain all observation tasks; traverse the target satellite set to obtain all task satellite information;

[0105] S212, perform analytical processing on any of the observation tasks to obtain point task information and regional task information;

[0106] It should be noted that the parsing process refers to obtaining the point task information and the region task information based on the field identifier bits;

[0107] S213, parse and process the information of any of the mission satellites to obtain the first row of orbit data information and the second row of orbit data information;

[0108] It should be noted that the parsing process refers to obtaining the first row of track data information and the second row of track data information based on the field identifier bits;

[0109] S214, the point task information, the area task information, the first row orbit data information and the second row orbit data information are fused to obtain the satellite collaborative observation task;

[0110] It should be noted that the fusion process refers to...

[0111] S215, Arrange all the satellite collaborative observation tasks in chronological order to obtain a multi-satellite collaborative observation task set;

[0112] It should be noted that the arrangement process refers to arranging all the satellite collaborative observation tasks in chronological order.

[0113] As can be seen, the multi-satellite collaborative three-dimensional observation method described in the embodiments of the present invention overcomes the limitations and errors of single-satellite observation, visualizes and intuitiveizes difficult-to-understand spatial information, and improves the efficiency of data analysis and processing.

[0114] In another optional embodiment, in step S23 above, processing any of the cooperative observation tasks based on the payload information to obtain detailed mission satellite information includes:

[0115] S231, Based on the payload information, the collaborative observation task is processed using the orbit calculation model to obtain satellite orbit coordinate data information;

[0116] S232, Based on the payload information, the satellite orbit coordinate data information is processed using a satellite nadir point latitude and longitude calculation model to obtain satellite nadir point strip information;

[0117] S233, Based on the payload information, the collaborative observation task is processed using the satellite side-swing latitude and longitude calculation model to obtain satellite side-swing strip information;

[0118] S234, Based on the satellite coverage calculation model, the satellite nadir point strip information, the satellite side-swing strip information and the observation task set are processed to obtain the satellite strip task intersection coordinate set;

[0119] S235, the satellite orbital coordinate data information and the satellite strip mission intersection coordinate set are fused to obtain detailed mission satellite information.

[0120] As can be seen, the multi-satellite collaborative three-dimensional observation method described in the embodiments of the present invention overcomes the limitations and errors of single-satellite observation, visualizes and intuitiveizes difficult-to-understand spatial information, and improves the efficiency of data analysis and processing.

[0121] In another optional embodiment, in step S231 above, the orbit calculation model expression is:

[0122]

[0123] Where a represents the semi-major axis of the orbit; t0 represents the given time; r0 represents the satellite's position at time t0; v0 represents the satellite's velocity at time t0; t represents the current time; r represents the satellite's position at time t; v represents the satellite's velocity at time t; ΔE represents the angle difference between the current time and the given time asymptotic point; and μ represents the gravitational constant.

[0124] It should be noted that the gravitational constant μ is determined by the masses of the satellite and the Earth according to the formula... The mass of the satellite is obtained, where A1 represents the mass of the Earth and A2 represents the mass of the satellite.

[0125] As can be seen, the multi-satellite collaborative three-dimensional observation method described in the embodiments of the present invention overcomes the limitations and errors of single-satellite observation, visualizes and intuitiveizes difficult-to-understand spatial information, and improves the efficiency of data analysis and processing.

[0126] In another optional embodiment, in step S232 above, the step of processing the satellite orbit coordinate data information based on the payload information using a satellite nadir latitude and longitude calculation model to obtain satellite nadir strip information includes:

[0127] S2321, Using the satellite nadir latitude and longitude calculation model, coordinate transformation processing is performed on the satellite orbit coordinate data to obtain the station center horizontal rectangular coordinate information;

[0128] S2322, using the satellite sub-satellite point latitude and longitude calculation model, the station center horizontal rectangular coordinate information is processed by coordinate transformation to obtain the station center polar coordinate information;

[0129] S2323, The payload information is calculated and processed to obtain the satellite overpass scan strip;

[0130] It should be noted that the aforementioned calculation and processing refers to using image information acquired by the satellite payload and processing that image information to obtain satellite overpass scan stripes. This embodiment of the invention does not impose any limitations on this method.

[0131] S2324, Using the station center polar coordinate information, the satellite overpass scan strip is processed to obtain satellite nadir point strip information;

[0132] It should be noted that the process of using the station-centered polar coordinate information to process the satellite transit scan strip to obtain the satellite nadir point strip information includes:

[0133] As can be seen, the multi-satellite collaborative three-dimensional observation method described in the embodiments of the present invention overcomes the limitations and errors of single-satellite observation, visualizes and intuitiveizes difficult-to-understand spatial information, and improves the efficiency of data analysis and processing.

[0134] In another optional embodiment, in step S232 above, the expression for the satellite nadir latitude and longitude calculation model is:

[0135]

[0136] Where (L0, B0) represent geodetic coordinates (latitude and longitude); (X0, Y0, Z0) represent sphere-centered rectangular coordinates; (X, Y, Z) represent sphere-centered rectangular coordinates; (x, y, z) represent station-centered horizontal rectangular coordinates; R represents the slope distance between the station and the target point; A represents the slope distance azimuth angle between the station and the target point; and E represents the slope distance elevation angle between the station and the target point.

[0137] As can be seen, the multi-satellite collaborative three-dimensional observation method described in the embodiments of the present invention overcomes the limitations and errors of single-satellite observation, visualizes and intuitiveizes difficult-to-understand spatial information, and improves the efficiency of data analysis and processing.

[0138] In another optional embodiment, in step S233 above, the step of processing the collaborative observation task based on the payload information using a satellite side-swing latitude and longitude calculation model to obtain satellite side-swing strip information includes:

[0139] S2331, based on the rotation matrix acquisition model, processes the satellite's roll angle, pitch angle and yaw angle to obtain the rotation matrix from the satellite's body coordinate system to the geocentric inertial coordinate system;

[0140] The expression for obtaining the rotation matrix is:

[0141]

[0142] Where R represents the rotation matrix; α represents the satellite's roll angle; β represents the satellite's pitch angle; and θ represents the satellite's yaw angle.

[0143] S2332, Process the load information and the satellite body coordinate system to obtain the direction cosine of the load relative to the satellite body coordinate system;

[0144] It should be noted that the processing of the payload information and the satellite body coordinate system to obtain the direction cosine of the payload relative to the satellite body coordinate system is obtained by the satellite's optical payload, and this embodiment does not limit this.

[0145] S2333, Multiply the direction cosine and the rotation matrix to obtain the direction vector of the load in the reference coordinate system;

[0146] It should be noted that the direction vector is the direction vector of the load in the geocentric inertial coordinate system;

[0147] S2334, calculate the angle between the direction vector and the perpendicular vector of the geocentric inertial coordinate system to obtain the lateral sway angle;

[0148] It should be noted that the calculation expression is as follows:

[0149]

[0150] Where ω represents the lateral sway angle; Y represents the unit vector of the direction vector; The unit vector representing the perpendicular vector of the geocentric inertial coordinate system;

[0151] S2335, Process the load information and the side sway angle to obtain satellite side sway strip information;

[0152] It should be noted that the processing of the payload information and the lateral tilt angle to obtain the satellite lateral tilt strip information includes:

[0153] Using the load information, the ground-fixed coordinates and target vector information of the target area are obtained;

[0154] Using the ground-fixed coordinates of the target area and the target vector information, the beam center vector is obtained;

[0155] The coordinates of the beam center point are obtained using satellite altitude, latitude and longitude information and ground-fixed coordinate information of the target area;

[0156] The coordinates of the beam center point are transformed to obtain the coordinates of the ground-fixed beam center point;

[0157] It should be noted that the conversion processing expression is the same as the satellite nadir latitude and longitude calculation model;

[0158] Based on the coordinates of the center point of the ground-fixed beam, the coordinate set of the edge points is obtained, and the satellite side-swing strip information is obtained.

[0159] As can be seen, the multi-satellite collaborative three-dimensional observation method described in the embodiments of the present invention overcomes the limitations and errors of single-satellite observation, visualizes and intuitiveizes difficult-to-understand spatial information, and improves the efficiency of data analysis and processing.

[0160] In another optional embodiment, in step S234 above, the processing of the satellite nadir strip information, the satellite side-swing strip information, and the observation task set based on the satellite coverage calculation model to obtain the satellite strip task intersection coordinate set includes:

[0161] Using the satellite coverage calculation model, the satellite nadir point strip information output by the satellite nadir point calculation model, the satellite side-slip strip information output by the satellite side-slip calculation model, and the observation task set are subjected to intersection calculation processing to obtain the satellite strip task intersection coordinate set;

[0162] The expression for the satellite coverage calculation model is as follows:

[0163] C = A∩B∩R;

[0164] Where C represents coverage; A represents satellite nadir strip information; and B represents satellite side-swing strip information.

[0165] As can be seen, the multi-satellite collaborative three-dimensional observation method described in the embodiments of the present invention overcomes the limitations and errors of single-satellite observation, visualizes and intuitiveizes difficult-to-understand spatial information, and improves the efficiency of data analysis and processing.

[0166] In another optional embodiment, step S235 above, which involves fusing the satellite orbital coordinate data information and the satellite strip mission intersection coordinate set to obtain detailed mission satellite information, includes:

[0167] S2351, The satellite orbit coordinate data information is parsed and processed to obtain the first time, the first satellite number and orbit coordinate data;

[0168] It should be noted that the parsing process refers to obtaining the first time, first satellite number, and orbital coordinate data based on the field identifier.

[0169] S2352, The coordinate set of the intersection of the satellite strip missions is parsed to obtain the second time, the second satellite number, and the satellite side-swing strip information;

[0170] It should be noted that the parsing process refers to obtaining the second time, the second satellite number, and the satellite side-swing strip information based on the field identifier bits;

[0171] S2353, compare whether the first satellite number and the second satellite number are consistent to obtain the satellite consistency judgment result;

[0172] Compare whether the first time and the second time are consistent to obtain the first time comparison result;

[0173] S2354, when both the satellite consistency judgment result and the first time comparison result are yes, the first time, the first satellite number, the orbital coordinate data and the satellite side-swing strip information are combined in sequence to obtain detailed information of the mission satellite;

[0174] If either the satellite consistency judgment result or the time consistency judgment result is not true, return to S2351.

[0175] As can be seen, the multi-satellite collaborative three-dimensional observation method described in the embodiments of the present invention overcomes the limitations and errors of single-satellite observation, visualizes and intuitiveizes difficult-to-understand spatial information, and improves the efficiency of data analysis and processing.

[0176] In another optional embodiment, step S3 above, which involves using a 3D digital globe to perform 3D visualization simulation processing on the mission satellite detailed information set based on the payload information to obtain multi-satellite collaborative 3D visualization observation results, includes:

[0177] S31, Traverse the mission satellite detailed information set to obtain all mission satellite detailed information;

[0178] S32, parse and process the detailed information set of any of the mission satellites to obtain the third time, the third satellite number, orbital coordinate data and satellite side-swing strip information;

[0179] It should be noted that the parsing process refers to extracting and obtaining the third time, the third satellite number, the orbital coordinate data, and the satellite side-swing strip information based on the field identifier;

[0180] S33, obtain the current display time and current location of the 3D digital globe;

[0181] S34, compare whether the current display time and the third time are consistent to obtain the second time comparison result;

[0182] S35, when the second time comparison result is yes, obtain the fourth satellite number, satellite orbit coordinate data and satellite side-swing strip information, and execute S36;

[0183] If the result of the second time comparison is negative, execute S33;

[0184] S36, The satellite orbital coordinate data is parsed and processed to obtain the satellite ID, satellite name, TLE version number and satellite position;

[0185] It should be noted that the parsing process refers to extracting the satellite ID, satellite name, TLE version number, and satellite location based on the field identifier;

[0186] The satellite side-swing strip information is parsed to obtain satellite ID, satellite name, satellite coverage information, and satellite status information;

[0187] It should be noted that the satellite status information includes the satellite pitch angle, satellite roll angle, and satellite yaw angle;

[0188] It should be noted that the parsing process refers to extracting the satellite ID, satellite name, satellite coverage information, and satellite status information based on the field identifier;

[0189] S37, determine whether the current position and the satellite position are consistent, and obtain the position determination result;

[0190] S38, when the location determination result is yes, the satellite status information, the satellite ID, the satellite name and the satellite coverage information are standardized to obtain satellite three-dimensional data, which is then displayed on the three-dimensional digital globe to obtain multi-satellite collaborative three-dimensional visualization observation results;

[0191] It should be noted that the standardization process refers to assembling the data according to the data format that a 3D globe can load (CZML) to obtain the satellite 3D data;

[0192] If the position determination result is negative, execute S33.

[0193] It should be noted that, as Figure 4 As shown, Figure 4 This is a simulation diagram of observing a target area using three satellites. The green line represents the trajectory of the first satellite; the blue line represents the trajectory of the second satellite; and the red line represents the trajectory of the third satellite. The green area represents the observation area of ​​the first satellite at a given observation point; the blue area represents the observation area of ​​the second satellite at a given observation point. Figure 4 As can be seen, by specifying a batch of task points to be observed, the time interval for observation, and the priority weight of each task point, and coordinating multiple satellite nodes through scheduling strategies, as many task points as possible can be observed under the condition of satisfying satellite imaging constraints, and the observation task benefits can be maximized. This reduces the limitations and errors of single satellite observation. At the same time, 3D visualization can display data and information in a three-dimensional and intuitive way, allowing users to understand and analyze data more intuitively. Compared with two-dimensional planar graphics, 3D visualization can better present the spatial distribution, shape, and size characteristics of data, making it easier for users to understand and accept.

[0194] As can be seen, the multi-satellite collaborative three-dimensional observation method described in the embodiments of the present invention overcomes the limitations and errors of single-satellite observation, visualizes and intuitiveizes difficult-to-understand spatial information, and improves the efficiency of data analysis and processing.

[0195] Example 2

[0196] Please see Figure 2 , Figure 2 This is a schematic diagram of the structure of a multi-satellite collaborative three-dimensional observation device disclosed in an embodiment of the present invention. Figure 2 The described apparatus can be applied to satellite observation systems, such as local servers or cloud servers used for satellite observation, and the embodiments of the present invention are not limited thereto. Figure 2 As shown, the device may include:

[0197] The acquisition module 101 is used to acquire the observation task set and the target satellite set;

[0198] The first processing module 102 is used to process the observation task set and the target satellite set to obtain a detailed information set of the mission satellites;

[0199] The second processing module 103 is used to perform three-dimensional visualization simulation processing on the mission satellite detailed information set based on a three-dimensional globe to obtain multi-satellite collaborative three-dimensional visualization observation results.

[0200] As can be seen, the multi-satellite collaborative three-dimensional observation method described in the embodiments of the present invention overcomes the limitations and errors of single-satellite observation, visualizes and intuitiveizes difficult-to-understand spatial information, and improves the efficiency of data analysis and processing.

[0201] Example 3

[0202] Please see Figure 3 , Figure 3 This is a schematic diagram of the structure of another multi-satellite collaborative three-dimensional observation device disclosed in an embodiment of the present invention. Wherein, Figure 3 The described apparatus can be applied to satellite observation systems, such as local servers or cloud servers used for satellite observation, and the embodiments of the present invention are not limited thereto. Figure 3 As shown, the device may include:

[0203] Memory 201 storing executable program code;

[0204] Processor 202 coupled to the memory;

[0205] The processor 202 calls the executable program code stored in the memory 201 to execute the steps in the multi-satellite collaborative three-dimensional observation method described in Embodiment 1.

[0206] Example 4

[0207] This invention discloses a computer-readable storage medium storing a computer program for electronic data exchange, wherein the computer program causes a computer to execute the steps in the multi-satellite collaborative three-dimensional observation method described in Embodiment 1.

[0208] The device embodiments described above are merely illustrative. The modules described as separate components may or may not be physically separate, and the components shown as modules may or may not be physical modules; that is, they may be located in one place or distributed across multiple network modules. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0209] Through the detailed description of the above embodiments, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, including read-only memory (ROM), random access memory (RAM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), one-time programmable read-only memory (OTPROM), electrically-erasable programmable read-only memory (EEPROM), compact disc read-only memory (CD-ROM) or other optical disc storage, disk storage, magnetic tape storage, or any other computer-readable medium that can be used to carry or store data.

[0210] Finally, it should be noted that the multi-satellite collaborative three-dimensional observation method and apparatus disclosed in the embodiments of the present invention are merely preferred embodiments of the present invention and are only used to illustrate the technical solutions of the present invention, not to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A multi-satellite collaborative three-dimensional observation method, characterized in that, The method includes: S1, acquires the observation task set, target satellite set, and payload information; S2, process the observation task set, the target satellite set, and the payload information to obtain a detailed task satellite information set; The process of processing the observation task set, the target satellite set, and the payload information to obtain a detailed task satellite information set includes: S21, Process the observation task set and the target satellite set to obtain a multi-satellite collaborative observation task set; S22, Process the multi-satellite collaborative observation task set to obtain all collaborative observation tasks; S23, Based on the payload information, process any of the cooperative observation tasks to obtain detailed information about the mission satellites; The process of processing any of the cooperative observation tasks based on the payload information to obtain detailed information about the mission satellites includes: S231, Based on the payload information, the collaborative observation task is processed using an orbit calculation model to obtain satellite orbit coordinate data information; S232, Based on the payload information, the satellite orbit coordinate data information is processed using a satellite nadir point latitude and longitude calculation model to obtain satellite nadir point strip information; The expression for the satellite nadir latitude and longitude calculation model is as follows: ； ； in, Represents geodetic coordinates in latitude and longitude; Represents the rectangular coordinates of the sphere's center; Represents the rectangular coordinates of the sphere's center; Represents the horizontal rectangular coordinates of the station center; Indicates the slope distance between the station and the target point; Indicates the slant range and azimuth of the station relative to the target point; Indicates the slant distance and elevation angle of the station relative to the target point; S233, Based on the payload information, the collaborative observation task is processed using the satellite side-swing latitude and longitude calculation model to obtain satellite side-swing strip information; The step of processing the collaborative observation task based on the payload information using a satellite side-swing latitude and longitude calculation model to obtain satellite side-swing strip information includes: S2331, based on the rotation matrix acquisition model, processes the satellite's roll angle, pitch angle and yaw angle to obtain the rotation matrix from the satellite's body coordinate system to the geocentric inertial coordinate system; The expression for obtaining the rotation matrix is: ； in, Represents the rotation matrix; Indicates the satellite's roll angle; Indicates the satellite's elevation angle; Indicates the satellite's yaw angle; S2332, Process the payload information and the satellite body coordinate system to obtain the direction cosine of the payload relative to the satellite body coordinate system; S2333, Multiply the direction cosine and the rotation matrix to obtain the direction vector of the load in the reference coordinate system; S2334, calculate the angle between the direction vector and the perpendicular vector of the geocentric inertial coordinate system to obtain the lateral sway angle; The calculation expression is: ； in, Indicates the lateral sway angle; The unit vector representing the direction vector; The unit vector representing the perpendicular vector of the geocentric inertial coordinate system; S2335, The payload information and the side swing angle are processed to obtain satellite side swing strip information; S234, Based on the satellite coverage calculation model, the satellite nadir point strip information, the satellite side-swing strip information and the observation task set are processed to obtain the satellite strip task intersection coordinate set; The satellite coverage calculation model processes the satellite nadir strip information, the satellite side-swing strip information, and the observation task set to obtain the satellite strip task intersection coordinate set, including: Using the satellite coverage calculation model, the satellite nadir point strip information output by the satellite nadir point calculation model, the satellite side-slip strip information output by the satellite side-slip calculation model, and the observation task set are subjected to intersection calculation processing to obtain the satellite strip task intersection coordinate set; The expression for the satellite coverage calculation model is as follows: ； in, Indicates coverage rate; This indicates finding the intersection; This indicates the sub-satellite point stripe information; Indicates satellite side-swing strip information; This represents the set of observation tasks; S235, perform fusion processing on the satellite orbit coordinate data information and the satellite strip mission intersection coordinate set to obtain detailed mission satellite information; S24, Arrange all the mission satellite details in chronological order to obtain the mission satellite details set; S3. Based on the payload information, a three-dimensional digital globe is used to perform three-dimensional visualization simulation processing on the detailed information set of the mission satellite to obtain multi-satellite collaborative three-dimensional visualization observation results.

2. The multi-satellite collaborative three-dimensional observation method according to claim 1, characterized in that, The process of processing the observation task set and the target satellite set to obtain a multi-satellite collaborative observation task set includes: S211, Traverse the observation task set to obtain all observation tasks; traverse the target satellite set to obtain all task satellite information; S212, perform analytical processing on any of the observation tasks to obtain point task information and regional task information; S213, parse and process the information of any of the mission satellites to obtain the first row of orbit data information and the second row of orbit data information; S214, the point task information, the area task information, the first row orbit data information and the second row orbit data information are fused to obtain the satellite collaborative observation task; S215, Arrange all the satellite collaborative observation tasks according to time order to obtain a multi-satellite collaborative observation task set.

3. The multi-satellite collaborative three-dimensional observation method according to claim 1, characterized in that, The orbit calculation model expression is as follows: ； in, Indicates the semi-major axis of the track; Indicates a given time; express The location of the satellite at any given time; express The speed of the satellite at any given moment; Indicates the current time; express The location of the satellite at any given time; express The speed of the satellite at any given moment; This represents the angle difference between the current time and the point closest to a given time. This represents the gravitational constant.

4. The multi-satellite collaborative three-dimensional observation method according to claim 1, characterized in that, Based on the payload information, the satellite orbital coordinate data is processed using a satellite nadir latitude and longitude calculation model to obtain satellite nadir strip information, including: S2321, Using the satellite nadir latitude and longitude calculation model, coordinate transformation processing is performed on the satellite orbit coordinate data to obtain the station center horizontal rectangular coordinate information; S2322, using the satellite sub-satellite point latitude and longitude calculation model, the station center horizontal rectangular coordinate information is processed by coordinate transformation to obtain the station center polar coordinate information; S2323, The payload information is calculated and processed to obtain the satellite overpass scan strip; S2324, using the station center polar coordinate information, the satellite transit scan strip is processed to obtain the satellite nadir point strip information.

5. A multi-satellite collaborative three-dimensional observation device, characterized in that, The device includes: Memory containing executable program code; A processor coupled to the memory; The processor calls the executable program code stored in the memory to execute the multi-satellite collaborative three-dimensional observation method as described in any one of claims 1-4.

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