A space situation integrated perception system of a global observation station
By constructing an integrated space situational awareness system with global observation stations, the problems of efficient monitoring of large-scale target groups and unified multi-source data have been solved, achieving high-precision, real-time space situational awareness and dynamic target management.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- BEIJING CREATUNION INFORMATION TECH CO LTD
- Filing Date
- 2026-05-11
- Publication Date
- 2026-07-31
AI Technical Summary
Existing space situational awareness systems struggle to achieve parallel and efficient monitoring of large-scale target groups, and multi-source heterogeneous data lacks unified semantic associations, failing to meet real-time and accuracy requirements.
By constructing a space situational awareness system for global observation stations, including an observation station module, an observation collaboration module, a full-dimensional cataloging module, an orbital asset map construction module, and an intent-driven early warning module, we can achieve multi-target synchronous observation and interferometric enhanced orbit determination, unify multi-source data, and perform semantic reasoning.
It enables parallel monitoring of large-scale target groups such as low-Earth orbit mega-constellations, improving perception accuracy and timeliness, reducing hardware costs, and breaking down data silos through knowledge graphs to achieve real-time target behavior recognition and dynamic value scoring.
Smart Images
Figure CN122490362A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of space situational awareness technology, specifically to an integrated space situational awareness system for global observation stations. Background Technology
[0002] Space situational awareness refers to the continuous monitoring, tracking, identification, and cataloging of targets such as spacecraft, space debris, and meteorites in Earth's orbit, in order to support space asset management, collision avoidance, debris management, and national security decision-making. With the increasing frequency of global space activities, especially the large-scale deployment of low-Earth orbit mega-constellations and the exponential growth in the number of space debris, space situational awareness is facing unprecedented technological challenges.
[0003] Current space situational awareness systems primarily rely on a globally distributed network of optical observation stations to locate and determine the orbit of space targets through independent observations from a single station or post-hoc fusion of data from multiple stations. However, existing technologies suffer from the following prominent problems:
[0004] 1. Traditional optical observation modes are difficult to achieve parallel and efficient monitoring of large-scale target groups. Existing optical observation stations usually adopt a single-station, single-target tracking mode. If each target is tracked one by one, the real-time requirements cannot be met or the orbit determination accuracy will be greatly reduced. In the existing technology, although there are attempts to improve accuracy through multi-station joint observation, there is a lack of real-time coordination and scheduling between the observation stations, and it is still impossible to dynamically switch the observation mode according to the actual situation.
[0005] 2. There is a lack of unified semantic association between multi-source heterogeneous data. The data involved in space situational awareness have significant differences in different aspects. In the existing technology, these data are usually processed by independent systems. There is a lack of effective integration mechanism between the data, making it impossible to establish a unified orbital asset knowledge system and meet differentiated needs. Summary of the Invention
[0006] The purpose of this invention is to provide an integrated space situational awareness system for global observation stations, thereby solving the problems mentioned in the background art.
[0007] To achieve the above objectives, the present invention provides the following technical solution: an integrated space situational awareness system for a global observation station, comprising:
[0008] Observation station module: used to acquire optical images of space targets in real time and process the optical images to obtain standardized basic observation data;
[0009] Observation coordination module: The observation station module is organized into a virtual optical phased array to realize multi-target synchronous staring and interferometric enhanced orbit determination.
[0010] Full-dimensional cataloging module: performs precise orbit determination and cataloging management of space targets based on the standardized basic observation data.
[0011] Track asset mapping module: used to integrate multi-source data to provide a semantic reasoning basis for early warning;
[0012] Intent-driven early warning module: used to calculate the rendezvous risk between space targets and generate differentiated early warning information and avoidance decision suggestions;
[0013] Visualization module: Used to intuitively present the system's operating status, track conditions, and early warning events;
[0014] External data module: used to collect external data, standardize and unify it before inputting it into the track asset graph construction module to enrich the semantic associations of the knowledge graph;
[0015] The observation coordination module includes a resource abstraction module, a collaborative observation scheduling module, a data fusion module, and an interferometry processing module. These modules are all bidirectionally connected. The orbital asset map construction module includes a multi-source data access module, an entity relationship extraction module, a map storage module, and a behavior reasoning module. These modules are also bidirectionally connected.
[0016] The bidirectional signal output from the observation station module is connected to the input of the data fusion module in the observation collaboration module, and the output signal from the external data module is connected to the input of the multi-source data access module in the orbital asset mapping module.
[0017] Furthermore, the observation station module includes a real-time data acquisition module, a preprocessing module, an anomaly detection module, and a semantic compression module, all of which are bidirectionally connected.
[0018] Furthermore, the full-dimensional cataloging module includes a target value assessment module, a cataloging strategy generation module, and a cataloging database module, all of which are bidirectionally connected.
[0019] Furthermore, the intent-driven early warning module includes a rendezvous calculation module, a user intent understanding module, and an early warning generation module, all of which are bidirectionally connected.
[0020] Furthermore, the output signal of the real-time data acquisition module in the observation station module is connected to the input of the cataloging strategy generation module in the full-dimensional cataloging module.
[0021] Furthermore, the output signal of the data fusion module in the observation collaboration module is connected to the input of the cataloging strategy generation module in the full-dimensional cataloging module.
[0022] Furthermore, the output signal of the cataloging strategy generation module in the full-dimensional cataloging module is connected to the input of the multi-source data access module in the track asset map construction module, and the output signal of the cataloging strategy generation module in the full-dimensional cataloging module is connected to the input of the intersection calculation module in the intention-driven early warning module.
[0023] Furthermore, the output signal of the multi-source data access module in the track asset map construction module is connected to the input of the intersection calculation module in the intention-driven early warning module.
[0024] Furthermore, the output signal of the intersection calculation module in the intent-driven early warning module is connected to the input of the visualization module.
[0025] Furthermore, in the full-dimensional cataloging module, the target value scoring model is as follows:
[0026]
[0027] in, Rate the target value. The orbital value coefficients are set to 1.0 for GEO orbits, 0.7 for MEO orbits, 0.4 for LEO orbits, and 0.2 for debris. It is a user demand coefficient, dynamically weighted according to the type of user subscribing to this target. The collision risk coefficient is calculated based on real-time meeting probability. The orbital uncertainty coefficient is dynamically calculated based on the time interval since the last observation and the orbital prediction error. , , , These are preset weighting coefficients.
[0028] This invention provides an integrated space situational awareness system for global observation stations. It has the following beneficial effects:
[0029] (1) The space situation integrated perception system of the global observation station, through the use of the observation collaboration module, dynamically switches between wide-area staring mode, multi-target synchronous tracking mode and interferometric enhancement mode according to the observation task queue and resource status, organizes the globally distributed observation stations into a virtual optical phased array, breaks through the physical limitation of single station and single target of traditional optical telescopes, realizes parallel monitoring of large-scale target groups such as low-orbit giant constellations, significantly improves the accuracy, timeliness and resource utilization efficiency of space target perception, and at the same time, it can obtain high-precision positioning capability through multi-station collaboration without configuring high-precision interferometric measurement equipment at each station, reducing the hardware cost and expansion complexity of deployment.
[0030] (2) The space situational awareness system of the global observation station can standardize and map multi-source heterogeneous data into the same knowledge graph framework through the use of the orbital asset map construction module, break the semantic barriers between different types of data, eliminate the information island phenomenon between optical data and radio data, public data and declared data in the traditional space situational awareness system, and at the same time, can automatically identify the target status and can identify abnormal intentions in a timely manner.
[0031] (3) The space situation integrated perception system of the global observation station, through the coordinated use of the observation collaboration module and the orbital asset map construction module, realizes the transition from passive collection to active cognition. By using multi-source data fusion and behavioral reasoning, it identifies the behavioral intentions of the target in real time and dynamically updates its value score and cataloging priority. It automatically adjusts the most suitable node in the observation station to achieve the selection of the optimal observation position. Attached Figure Description
[0032] Figure 1 This is a general system diagram of an integrated space situational awareness system for a global observation station according to the present invention;
[0033] Figure 2 This is a schematic diagram of the observation station module of a global observation station integrated space situational awareness system according to the present invention.
[0034] Figure 3 This is a schematic diagram of the observation coordination module of a global observation station integrated space situational awareness system according to the present invention;
[0035] Figure 4 This is a schematic diagram of the full-dimensional cataloging module of a global observation station integrated space situational awareness system according to the present invention;
[0036] Figure 5 This is a schematic diagram of the orbital asset map construction module of a global observation station integrated space situational awareness system according to the present invention;
[0037] Figure 6This is a schematic diagram of the intent-driven early warning module of a global observation station space situation integrated perception system according to the present invention.
[0038] The diagram shows: 1. Observation station module; 2. Observation collaboration module; 3. Full-dimensional cataloging module; 4. Track asset map construction module; 5. Intent-driven early warning module; 6. Visualization module; 7. External data module. Detailed Implementation
[0039] 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.
[0040] Examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain the invention, and should not be construed as limiting the invention.
[0041] The present invention will be further described below with reference to the accompanying drawings and embodiments:
[0042] Please see Figure 1-6 This invention provides a technical solution: an integrated space situational awareness system for global observation stations, comprising:
[0043] Observation Module 1: Used to acquire optical images of space targets in real time and process the optical images to obtain standardized basic observation data;
[0044] Observation Coordination Module 2: Organizes Observation Station Module 1 into a virtual optical phased array to achieve multi-target synchronous staring and interferometric enhanced orbit determination.
[0045] Full-Dimensional Cataloging Module 3: Performs precise orbit determination and cataloging management of space targets based on standardized basic observation data.
[0046] Track Asset Mapping Module 4: Used to integrate multi-source data and provide a semantic reasoning basis for early warning;
[0047] Intent-driven early warning module 5: used to calculate the rendezvous risk between space targets and generate differentiated early warning information and avoidance decision suggestions;
[0048] Visualization Module 6: Used to intuitively present the system's operating status, track conditions, and early warning events;
[0049] External data module 7: Used to collect external data, which is then standardized and input into the track asset graph construction module 4 to enrich the semantic associations of the knowledge graph;
[0050] The observation coordination module 2 includes a resource abstraction module, a collaborative observation scheduling module, a data fusion module, and an interferometry processing module. The resource abstraction module, collaborative observation scheduling module, data fusion module, and interferometry processing module are all connected by bidirectional signals. The track asset map construction module 4 includes a multi-source data access module, an entity relationship extraction module, a map storage module, and a behavior reasoning module. The multi-source data access module, entity relationship extraction module, map storage module, and behavior reasoning module are all connected by bidirectional signals.
[0051] The bidirectional signal output from the observation station module 1 is connected to the input of the data fusion module in the observation collaboration module 2, and the output signal from the external data module 7 is connected to the input of the multi-source data access module in the track asset map construction module 4.
[0052] The observation station module 1 consists of multiple optical observation stations deployed in different geographical locations around the world. Each observation station is equipped with an edge intelligent computing unit. The resource abstraction module is used to maintain the archive information, real-time status and capability vector of each observation station. The archive information includes latitude and longitude, equipment type, field of view and detection limit. The real-time status includes weather conditions, equipment health and task load rate. The capability vector includes low-orbit detection capability, high-orbit detection capability and rapid response capability. The collaborative observation scheduling module, data fusion module and interferometric processing module are used together to perform time alignment and spatial coordinate transformation on the data of multiple observation stations synchronously observing the same target, and perform optical interferometric processing to improve angular resolution.
[0053] The multi-source data access module in the track asset graph construction module 4 includes optical observation data, radio monitoring data, user-declared data, and internationally shared catalog data. This module is equipped with multiple data source adapters to access optical observation data, radio monitoring data, user-declared track maneuver plans and ownership change data, and internationally shared catalog data. The entity relationship extraction module extracts target entities, event entities, and subject entities from the multi-source data, as well as spatial relationships, ownership relationships, and causal relationships between entities. The graph storage module stores the knowledge graph. The behavior reasoning module extracts behavioral baselines based on the target's historical track data and event sequences, calculates behavioral anomaly indices, and infers behavioral intentions. The behavior reasoning module uses a temporal pattern mining algorithm to extract the target's behavioral baseline and employs a large language model to perform semantic understanding on unstructured user-declared data and historical event descriptions to infer the target's behavioral intentions. These intentions include normal operation, track drift, abnormal maneuvering, uncontrolled rollover, and debris cloud diffusion.
[0054] Specifically, the observation station module 1 includes a real-time data acquisition module, a preprocessing module, an anomaly detection module, and a semantic compression module. The real-time data acquisition module, the preprocessing module, the anomaly detection module, and the semantic compression module are all bidirectionally connected.
[0055] Specifically, the full-dimensional cataloging module 3 includes a target value assessment module, a cataloging strategy generation module, and a cataloging database module. The target value assessment module, the cataloging strategy generation module, and the cataloging database module are all connected by bidirectional signals.
[0056] The target value assessment module calculates the dynamic value score of each target based on the weighted sum of the orbital value coefficient, user demand coefficient, collision risk coefficient, and orbital uncertainty coefficient, and divides the targets into different cataloging priority levels according to the score results, and implements a hierarchical observation strategy.
[0057] Specifically, the intent-driven early warning module 5 includes a rendezvous calculation module, a user intent understanding module, and an early warning generation module, all of which are bidirectionally connected.
[0058] The rendezvous calculation module includes a fast screener and a precision calculator. The fast screener uses spatial grid indexing and time window filtering algorithms to screen potential rendezvous pairs globally. The precision calculator uses high-precision numerical integration and covariance analysis methods to calculate the rendezvous probability, relative velocity, collision energy, and position covariance. The risk classifier classifies warning events into four levels based on the rendezvous probability: red warning, orange warning, yellow attention, and blue record. The user intent understanding module stores the user's target interest type, event interest type, and push preference configuration. The warning generation module calls the corresponding warning template based on the user type to generate differentiated warning information, providing avoidance timing suggestions and fuel consumption estimates.
[0059] Specifically, the output signal of the real-time data acquisition module in the observation station module 1 is connected to the input of the cataloging strategy generation module in the full-dimensional cataloging module 3.
[0060] Specifically, the output signal of the data fusion module in the observation collaboration module 2 is connected to the input of the cataloging strategy generation module in the full-dimensional cataloging module 3.
[0061] Specifically, the output signal of the cataloging strategy generation module in the full-dimensional cataloging module 3 is connected to the input of the multi-source data access module in the track asset map construction module 4, and the output signal of the cataloging strategy generation module in the full-dimensional cataloging module 3 is connected to the input of the intersection calculation module in the intent-driven early warning module 5.
[0062] Specifically, the output signal of the multi-source data access module in the track asset mapping module 4 is connected to the input of the intersection calculation module in the intention-driven early warning module 5.
[0063] Specifically, the output signal of the intersection calculation module in the intent-driven early warning module 5 is connected to the input of the visualization module 6.
[0064] Specifically, in the full-dimensional cataloging module 3, the target value scoring model is as follows:
[0065]
[0066] in, Rate the target value. The orbital value coefficients are set to 1.0 for GEO orbits, 0.7 for MEO orbits, 0.4 for LEO orbits, and 0.2 for debris. It is a user demand coefficient, dynamically weighted according to the type of user subscribing to this target. The collision risk coefficient is calculated based on real-time meeting probability. The orbital uncertainty coefficient is dynamically calculated based on the time interval since the last observation and the orbital prediction error. , , , These are preset weighting coefficients.
[0067] In operation, the observation station module 1 acquires optical images of space targets in real time, performs local preprocessing, anomaly detection, and semantic compression through the edge intelligence unit, and outputs standardized observation reports. The observation collaboration module 2 receives the observation reports, maintains the status of global observation stations through the resource abstraction module, selects the observation mode through the collaborative observation scheduling module, and performs multi-station data alignment and angular resolution enhancement through the data fusion and interferometry processing module to output high-precision orbital data. The full-dimensional cataloging module 3 receives the orbital data, the target value assessment module calculates dynamic value scores and classifies them into levels, the cataloging strategy generation module executes the hierarchical observation strategy, the cataloging database module stores orbital elements and triggers re-observations, and outputs cataloging data to the map module and the early warning module. The orbital asset map construction module 4 connects to the radio monitoring and user declaration of the external data module 7. The system includes: an internationally shared data module for multi-source data access to adapt data; an entity and relation extraction module to extract entities and relations; a knowledge graph storage module to build a knowledge graph; a behavior reasoning module to output behavior profiles using time-series mining and large language models; an intent-driven early warning module 5 to receive cataloged data and knowledge graphs; a cross-intersection calculation module to quickly screen potential cross-intersections and precisely calculate cross-intersection probabilities; a risk classifier to divide risks into four levels: red, orange, yellow, and blue; a user intent understanding module to match user profiles; an early warning generation module to output differentiated early warning information and avoidance decision suggestions; and a visualization module 6 to receive early warning events and present system status and situation information in the form of 3D Earth orbit visualization, heat maps, and dashboards. Simultaneously, it provides orbital data query, early warning subscription, catalog subscription, and graph query services to government, enterprise, and research users through data service interfaces.
[0068] The above are merely preferred embodiments of the present invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the inventive concept of the present invention, and these all fall within the protection scope of the present invention.
Claims
1. A space situational awareness integrated perception system for a global observatory, characterized in that, include: Observation station module (1): used to acquire optical images of space targets in real time and process the optical images to obtain standardized basic observation data; Observation coordination module (2): Organizes the observation station module (1) into a virtual optical phased array to realize multi-target synchronous staring and interferometric enhanced orbit determination; Full-dimensional cataloging module (3): performs precise orbit determination and cataloging management of space targets based on the standardized basic observation data; Track asset mapping module (4): used to integrate multi-source data and provide a semantic reasoning basis for early warning; Intent-driven early warning module (5): used to calculate the rendezvous risk between space targets and generate differentiated early warning information and avoidance decision suggestions; Visualization module (6): used to intuitively present the system's operating status, track status, and early warning events; External data module (7): used to collect external data, and input it into the track asset graph construction module (4) after unification and standardization to enrich the semantic association of the knowledge graph; The observation coordination module (2) includes a resource abstraction module, a collaborative observation scheduling module, a data fusion module, and an interference processing module. The resource abstraction module, the collaborative observation scheduling module, the data fusion module, and the interference processing module are all bidirectionally connected. The track asset map construction module (4) includes a multi-source data access module, an entity relationship extraction module, a map storage module, and a behavior reasoning module. The multi-source data access module, the entity relationship extraction module, the map storage module, and the behavior reasoning module are all bidirectionally connected. The bidirectional signal at the output end of the observation station module (1) is connected to the input end of the data fusion module in the observation collaboration module (2), and the output signal of the external data module (7) is connected to the input end of the multi-source data access module in the orbital asset map construction module (4).
2. The integrated space situational awareness system for a global observation station according to claim 1, characterized in that: The observation station module (1) includes a real-time data acquisition module, a preprocessing module, an anomaly detection module, and a semantic compression module. The real-time data acquisition module, the preprocessing module, the anomaly detection module, and the semantic compression module are all bidirectionally connected.
3. The integrated space situational awareness system for a global observation station according to claim 1, characterized in that: The full-dimensional cataloging module (3) includes a target value assessment module, a cataloging strategy generation module, and a cataloging database module. The target value assessment module, the cataloging strategy generation module, and the cataloging database module are all bidirectionally connected.
4. The integrated space situational awareness system for a global observation station according to claim 1, characterized in that: The intent-driven early warning module (5) includes a rendezvous calculation module, a user intent understanding module, and an early warning generation module, and the rendezvous calculation module, the user intent understanding module, and the early warning generation module are all bidirectionally connected.
5. The integrated space situational awareness system for a global observation station according to claim 1, characterized in that: The output signal of the real-time data acquisition module in the observation station module (1) is connected to the input of the cataloging strategy generation module in the full-dimensional cataloging module (3).
6. The integrated space situational awareness system for a global observation station according to claim 1, characterized in that: The output signal of the data fusion module in the observation collaboration module (2) is connected to the input of the cataloging strategy generation module in the full-dimensional cataloging module (3).
7. The integrated space situational awareness system for a global observation station according to claim 1, characterized in that: The output signal of the cataloging strategy generation module in the full-dimensional cataloging module (3) is connected to the input of the multi-source data access module in the track asset map construction module (4), and the output signal of the cataloging strategy generation module in the full-dimensional cataloging module (3) is connected to the input of the intersection calculation module in the intention-driven early warning module (5).
8. The integrated space situational awareness system for a global observation station according to claim 1, characterized in that: The output signal of the multi-source data access module in the track asset map construction module (4) is connected to the input of the intersection calculation module in the intention-driven early warning module (5).
9. The integrated space situational awareness system for a global observation station according to claim 1, characterized in that: The output signal of the intersection calculation module in the intent-driven early warning module (5) is connected to the input of the visualization module (6).
10. A space situational awareness system for a global observation station according to claim 3, characterized in that: In the full-dimensional cataloging module (3), the target value scoring model is as follows: in, Rate the target value. The orbital value coefficients are set to 1.0 for GEO orbits, 0.7 for MEO orbits, 0.4 for LEO orbits, and 0.2 for debris. It is a user demand coefficient, dynamically weighted according to the type of user subscribing to this target. The collision risk coefficient is calculated based on real-time meeting probability. The orbital uncertainty coefficient is dynamically calculated based on the time interval since the last observation and the orbital prediction error. , , , These are preset weighting coefficients.