Spatial target object modeling method and system

Abstract

This invention relates to the field of spatiotemporal data modeling technology, and particularly to a method and system for modeling spatial target objects. The method involves determining model construction parameters and the three-dimensional space to be modeled, and constructing an initial spatiotemporal object model in the three-dimensional space based on the model construction parameters. The three-dimensional space includes at least one spatial entity. The model construction parameters include attribute information, ephemeris orbit, attitude parameters, entity model, and behavioral actions. Data of the target spatiotemporal object in the three-dimensional space is acquired based on a preset semantic description framework. This preset semantic description framework includes: spatiotemporal baseline semantic description, spatiotemporal position semantic description, attitude parameter semantic description, morphological material semantic description, state information semantic description, attribute information semantic description, internal and external relationship semantic description, and behavioral capability semantic description. The target spatiotemporal object data is matched to the corresponding parameters of the initial spatiotemporal object model and data is filled in to obtain the final spatiotemporal object model. This invention can establish the distribution characteristics of the overall situation of spatial target objects in time, space, and attributes from the perspective of situational spatiotemporal development, laying the foundation for real-time driving, visualization, comprehensive cognition, and precise analysis of spatial targets.

Description

Technical Field

[0001] This invention relates to the field of spatiotemporal data modeling technology, and in particular to a method and system for modeling space target objects, applicable to situational awareness of space target objects. Background Technology

[0002] With the development of space technology, space target situational awareness, as a fundamental means of gaining an advantage in space information, has received high attention. Compared with ground targets, space targets exhibit distinct spatiotemporal characteristics and prominent individual features, making the modeling, situational analysis, cognitive representation, and application of space targets urgently needed research. A robust model is a prerequisite for data organization, management, representation, and application. Currently, there are many computational models related to space target situational awareness, but research on the construction of spatiotemporal models based on ontology abstraction is relatively limited and lacks depth. Therefore, how to construct a visualized, comprehensive, and integrated spatiotemporal behavior model of space targets based on ontology semantic description is a pressing technical problem that needs to be solved in current space target situational awareness. Summary of the Invention

[0003] Therefore, this invention provides a method and system for modeling spatial target objects, which can establish the distribution characteristics of the overall situation of spatial target objects in time, space and attributes from the perspective of situational spatiotemporal development, laying the foundation for real-time driving, visualization, comprehensive cognition and precise analysis of spatial targets.

[0004] According to the design scheme provided by the present invention, on the one hand, a method for modeling spatial target objects is provided, comprising:

[0005] The model construction parameters and the three-dimensional space to be modeled are determined, and an initial spatiotemporal object model of the three-dimensional space is constructed according to the model construction parameters. The three-dimensional space includes at least one spatial entity, and the model construction parameters include attribute information, ephemeris orbit, attitude parameters, entity model and behavior action.

[0006] Data of target spatiotemporal objects in three-dimensional space are obtained based on a preset semantic description framework. The preset semantic description framework includes: spatiotemporal reference semantic description, spatiotemporal position semantic description, posture parameter semantic description, morphological material semantic description, state information semantic description, attribute information semantic description, internal and external relationship semantic description, and behavioral capability semantic description.

[0007] The target spatiotemporal object data is matched to the corresponding parameters of the initial spatiotemporal object model and the data is filled in to obtain the final spatiotemporal object model.

[0008] As a spatial target object modeling method of the present invention, the attribute information further includes: static attribute information that is the same as the life cycle of the spatial entity and / or dynamic attribute information composed of multiple indivisible attribute fragments, wherein the dynamic attribute information is represented by the attribute fragment period and the fixed attribute value within the attribute fragment period.

[0009] As a spatial target object modeling method of the present invention, the ephemeris orbit is further composed of multiple ephemeris segments, and each ephemeris segment includes a life cycle for representing the time life of the ephemeris segment, a coordinate system for representing the spatial reference of orbit calculation, and orbit information composed of orbit enumeration type and orbit parameters.

[0010] As a spatial target object modeling method of the present invention, the attitude parameters are further composed of one or more attitude segments, and each attitude segment includes an attitude life cycle, a reference spatial coordinate system, and specific attitude change data for representing the attitude ephemeris time lifeline. The specific attitude change data is composed of an attitude change enumeration type and an attitude parameter representation type.

[0011] As a spatial target object modeling method of the present invention, the entity model is further composed of nested entity components, wherein the parent and child entity components establish the association between the parent and child component nodes in terms of behavior and action through the component parent node identifier, the component material characteristics are recorded on the component node, and the posture, shape and constraints of the entity component are stored through geometric variables.

[0012] As a spatial target object modeling method of the present invention, the behavior action is further composed of a series of behavior segments. Each behavior segment includes a behavior action identifier, a behavior action type, a behavior action target, a behavior action triggering condition, a behavior action parameter, and a behavior action calculation model. The behavior action type includes attribute behavior type, ephemeris behavior type, posture behavior type, and model behavior type.

[0013] As a spatial target object modeling method of the present invention, further, a three-dimensional initial spatiotemporal object model is constructed based on model construction parameters, including:

[0014] Based on the model construction parameters, and using the Unified Modeling Language, spatial entity objects are formally represented as follows: SpaceObj = { OID, [ Property ] , Trajectory, Attitude, EntityModel, [ Behavior Based on formal representation and utilizing digital means, spatial entity objects are mapped to digital space, and a spatiotemporal entity object model is obtained. This model is then updated with real-time data on spatial targets. SpaceObj For spatial target spatiotemporal entity objects ，[ ] represents a parameter that can be empty; OID is a unique identifier for the target object, which is used to represent the index of the relationship and behavior between different objects and between elements within an object; Property represents attribute information; Trajectory represents ephemeris orbit; Attitude represents attitude parameter; EntityModel represents entity model; Behavior represents the behavior of spatiotemporal entity objects.

[0015] Furthermore, the present invention also provides a spatial target object modeling system, comprising: a model initialization module, a data acquisition module, and a data filling module, wherein,

[0016] The model initialization module is used to determine the model construction parameters and the three-dimensional space to be modeled, and to construct an initial spatiotemporal object model of the three-dimensional space according to the model construction parameters. The three-dimensional space includes at least one spatial entity, and the model construction parameters include attribute information, ephemeris orbit, attitude parameters, entity model and behavior action.

[0017] The data acquisition module is used to acquire spatiotemporal object data of a target in three-dimensional space based on a preset semantic description framework. The preset semantic description framework includes: spatiotemporal reference semantic description, spatiotemporal position semantic description, posture parameter semantic description, morphological material semantic description, state information semantic description, attribute information semantic description, internal and external relationship semantic description, and behavioral capability semantic description.

[0018] The data filling module is used to match the target spatiotemporal object data with the corresponding parameters of the initial spatiotemporal object model and fill the data to obtain the final spatiotemporal object model.

[0019] The beneficial effects of this invention are:

[0020] This invention first defines a three-dimensional space to be modeled, wherein the three-dimensional space includes at least one spatial entity. Then, based on preset semantic description rules, it obtains the object semantic description of the spatial entity in the three-dimensional space. The object semantic description includes: attribute information, ephemeris orbit, attitude parameters, entity model, and behavioral actions. Next, it extracts individual features of the spatial entity based on the object semantic description, and constructs a spatiotemporal entity object model based on these individual features using digital means. The individual features of the spatial entity include: spatiotemporal variation characteristics, granularity characteristics, entity three-state characteristics, and system correlation characteristics. Using the above technical solution, based on clarifying the scope and classification of spatial targets, spatiotemporal benchmarks, and transformations, it extracts the individual features and overall situation of spatial targets. Based on the spatial entity semantic description and individual features, it preliminarily determines the spatiotemporal object model of the spatial target, thereby achieving integrated spatiotemporal model construction. This solves the problem of insufficient modeling accuracy in existing spatial target modeling technologies, improves the accuracy of spatial target modeling, facilitates the integration of spatial target spatiotemporal entities into the digital space world, generates spatial target spatiotemporal objects, and effectively solves the problem of updating spatial target spatiotemporal object data in space situational awareness. It has good application prospects. Attached Figure Description

[0021] Figure 1 This is a schematic diagram of the spatial target object modeling process in the embodiment;

[0022] Figure 2 This is a schematic diagram illustrating the correspondence between the semantic description of spatial targets and individual features in the embodiment;

[0023] Figure 3 This is a schematic diagram of the spatiotemporal object system of spatial targets in the embodiment;

[0024] Figure 4 This is a schematic diagram of the spatiotemporal object description framework for spatial targets in the embodiment;

[0025] Figure 5 This is a schematic diagram of the integrated spatiotemporal behavior model of a spatial target in the embodiment;

[0026] Figure 6 This is a schematic diagram of TSBM attribute information in the embodiment;

[0027] Figure 7 This is a schematic diagram of the TSBM ephemeris orbit in the embodiment;

[0028] Figure 8 This is a schematic diagram of the TSBM attitude parameters in the embodiment;

[0029] Figure 9 This is a schematic diagram of the TSBM entity model in the embodiment;

[0030] Figure 10 This is a schematic diagram of the TSBM behavior action elements in the embodiment. Detailed Implementation

[0031] To make the objectives, technical solutions, and advantages of this invention clearer and more understandable, the invention will be further described in detail below with reference to the accompanying drawings and technical solutions.

[0032] Modeling is an abstraction made to understand things. In the traditional field of geospatial information, spatial data modeling is the process of abstracting geospatial data into digital maps, transforming the real geographical world into a digital map world. With the popularization and deepening application of computer technology, spatial data that changes over time has attracted attention, giving rise to the concept of spatiotemporal data. Numerous spatiotemporal data models have been proposed, including spatiotemporal composite, continuous snapshot, ground state correction, spatiotemporal cube, and object-oriented / event / process spatiotemporal data models. In recent years, technologies such as aerospace, sensors, mobile internet, and big data have developed rapidly. From the surface to the ocean, underground, and deep space, from outdoors to indoors, and from macro to micro, the types, volume, and timeliness of spatiotemporal data have undergone tremendous changes. Traditional geographic information systems and spatiotemporal data models are struggling to meet the requirements in terms of scale space, continuous change, and relational description. Concepts such as full-space information systems, multi-granularity entities, multi-granularity spatiotemporal objects, and multi-granularity spatiotemporal object data models have been proposed.

[0033] Space targets, as relatively new entities with unique operational ranges, possess certain distinctive characteristics compared to common entities. This invention addresses the needs for situational awareness of space targets in areas such as space security, information warfare, and aerospace support. (See embodiments below.) Figure 1 As shown, a method for modeling spatial target objects is provided, comprising:

[0034] S101. Determine the model construction parameters and the three-dimensional space to be modeled, and construct an initial spatiotemporal object model of the three-dimensional space according to the model construction parameters. The three-dimensional space includes at least one spatial entity, and the model construction parameters include attribute information, ephemeris orbit, attitude parameters, entity model, and behavior actions.

[0035] The three-dimensional space requires three-dimensional modeling, which can be determined based on preset three-dimensional space selection instructions. After the three-dimensional space is determined, spatial target object models can be constructed to recreate various spatial entities and environments in the three-dimensional space.

[0036] Based on the model building parameters, an initial spatiotemporal object model for three-dimensional space can be constructed, which can be designed to include:

[0037] Using a unified modeling language such as structs, spatial entity objects can be formally represented as: SpaceObj = { OID, [ Property ] , Trajectory, Attitude, EntityModel,[ Behavior Based on formal representation and utilizing digital means, spatial entity objects are mapped to digital space, and a spatiotemporal entity object model is obtained. This model is then updated with real-time data on spatial targets. SpaceObj For spatial target spatiotemporal entity objects ， [ ] represents a parameter that can be empty; OID is a unique identifier for the target object, which is used to represent the index of the relationship and behavior between different objects and between elements within an object; Property represents attribute information; Trajectory represents ephemeris orbit; Attitude represents attitude parameter; EntityModel represents entity model; Behavior represents the behavior of spatiotemporal entity objects.

[0038] S102. Obtain target spatiotemporal object data in three-dimensional space based on a preset semantic description framework, wherein the preset semantic description framework includes: spatiotemporal reference semantic description, spatiotemporal position semantic description, posture parameter semantic description, morphological material semantic description, state information semantic description, attribute information semantic description, internal and external relationship semantic description, and behavioral capability semantic description.

[0039] Selecting the fifth-generation high-resolution Earth observation satellite WorldView-4 from a certain company, the static information of the satellite is summarized as follows based on multiple information sources: (1) Basic attributes, which mainly describe the basic situation of the space target, including individual information such as name, former name, type, and owner, as well as launch information such as launch date, location, and launch vehicle model; (2) Platform information, which, as the main body of the space target, records the platform type, expected lifespan, structural shape, and basic storage and transmission capabilities; (3) Orbit information, which is affected by the gravity of the central celestial body and other perturbations and makes periodic motions. Orbit parameters are often used to describe its position, shape, and orientation, including reference frame, semi-major axis, inclination, and eccentricity; (4) Attitude control information, which is the pointing state of the space target during orbital operation. The parameters mainly include attitude control type, actuator, and sensors used; (5) Payload, which is the instrument and equipment loaded on the space target that directly performs the mission. It is an important component with various types and compositions. For Earth imaging satellites, it mainly includes information such as imaging mode, sensor band, resolution, and coverage width. The above five descriptions cover all the static aspects of a spatial target, from appearance to internal structure and from outward manifestation to function.

[0040] After obtaining semantic description information, several prominent features can be extracted, including spatiotemporal changes, granularity, entity states, and system relationships of spatial targets. The correspondence between semantic description and individual features is as follows: Figure 2As shown. Among them, time scale and spatial coordinates are two fundamental characteristics that identify all things in nature and social phenomena. Together, they constitute two basic facts of the existence of moving matter and possess objectivity. All five aspects of the semantic description of spatial targets are related to spatiotemporal information, and as a more mobile new phenomenon, its spatiotemporal change characteristics are more prominent. Compared with general moving targets, the spatiotemporal characteristics of spatial targets, besides being reflected in attributes, behaviors, and relationships, are mainly reflected in complex spatiotemporal reference systems and high-speed operating states. Granularity, also known as particle size, refers to the degree to which an object or system can be subdivided. The granularity characteristics of spatial targets are mainly reflected in spatiotemporal scale comparisons, which are related to all five aspects of the semantic description. In terms of time scale, the universe inhabited by space targets is 13.8 billion years old, while the accuracy of atomic clocks, serving as timekeeping benchmarks, has reached a level where the error is less than one second in 3.7 billion years. In terms of spatial scale, the average distance between the Earth and the Moon is 380,000 kilometers, and the average distance between the Earth and the Sun is 149.6 million kilometers. However, even in this seemingly vast expanse of space, the 2009 collision between US and Russian satellites still occurred, reflecting to some extent the relativity of the granularity of space targets. The space environment and space targets are the two main elements of current space operations. Compared to the former, space targets have more obvious physical characteristics, possessing a certain degree of observability and measurability. Attitude, shape, and state become the focus of attention, from which information such as the target's mission, intent, and structural composition can be further extracted. These characteristics are closely related to the platform, attitude control, and payload status. Given the global nature of space target operations and the specific nature of their missions, their system integration and link-related characteristics are more pronounced. Taking navigation satellites as an example, in principle, at least three satellites are needed in the area above a user's head to complete the positioning of the standing point. In order to achieve global and real-time coverage of navigation signals, global networking of navigation satellites has become an inevitable choice. In addition, satellites operate hundreds of kilometers above the ground, and their ultimate purpose is to provide services for human activities on the Earth's surface. Therefore, they are not isolated entities. Command uploading, data downloading, relay communication, etc., all need to be associated with ground targets or other space targets.

[0041] As a more distant, vast, and entirely new space, our understanding of the outer world becomes increasingly clear with deeper exploration. Space targets, as a vital and active component within this space, require abstract modeling as a crucial element in describing and representing the real space world. The relationships between space targets, space target data, space target spatiotemporal entities, space target spatiotemporal objects, the real space world, the space model world, and the digital space world are as follows: Figure 3 As shown.

[0042] In this embodiment, the real space world can be considered to be composed of an infinite number of space targets. Through extraction, simplification, abstraction, and description, these targets are abstracted into spatiotemporal entities of space targets in a space simulation world, endowed with spatiotemporal variations, granularity, entity three states, and system correlation characteristics. Digital modeling methods are used to load these spatiotemporal entities into the digital space world, generating spatiotemporal objects of space targets. Space target data originates from data acquisition and collection of space targets in both the real space world and the space model world, and is used to update the data content of the spatiotemporal objects of space targets. Therefore, in this embodiment, the spatiotemporal objects of space targets are considered as an abstraction and digital mapping of space targets in the real space world; they are a concrete description of the spatiotemporal entities of space targets in digital space. The corresponding process is considered as modeling the spatiotemporal objects of space targets, and the constructed digital model is the spatiotemporal object model of space targets, also known as the spatiotemporal model of space targets.

[0043] Building a model first requires a comprehensive analysis and description of the object under study, considering factors such as data, rules, and logic, to create a "precise profile." This involves describing multi-granularity spatiotemporal objects from eight aspects, including spatiotemporal reference, spatial location, and spatial morphology. Based on the analysis of current spatial target data, individual characteristics, and situational statistics, a matching spatial target spatiotemporal object description framework is developed, such as... Figure 4 As shown, it can include eight aspects: spatiotemporal reference, spatiotemporal position, attitude parameters, shape and material, state information, attribute information, internal and external relationships, and behavior. Among them, the spatiotemporal reference serves as a scale for recording the spatiotemporal information of a space target, and the time and space reference coordinate system is the foundation for describing other information. Spatiotemporal position information is one of the most basic and important contents of describing a space target's spatiotemporal object. The corresponding orbit determination (orbit determination) work generally requires post-processing of the tracking and measurement data from the aerospace telemetry and control network. After initial orbit determination or even precise orbit determination, the basic state quantities of the space target are calculated, that is, the position and velocity vector of the space target at any given time in the selected spatial coordinate system. For "orbiting" space targets, elliptical orbital elements can also be used for representation. Attitude parameters describe the motion of a space target's spacetime object around its center of mass. Determining attitude parameters is not only a requirement for performing specific space missions but is also closely related to orbit determination. Attitude parameters are typically defined using Euler angles of the local coordinate system relative to a reference coordinate system. Or Euler quaternions The description includes: morphology and material properties; a comprehensive description of the geometric shape, composition, and physical material of the space target / space object, typically represented by a three-dimensional geometric model; additionally, material information of its constituent structures and surfaces; state information describing the internal environment and operational status of the space target / space object, such as the target's liveness / death status, component temperature, and payload on / off status; attribute information describing name, number, type, background, etc. It's important to note that attribute information can be divided into static and dynamic attributes. For example, the WorldView-4 satellite's NASA number has always been 41848, but its ownership changed around 2013, belonging to different companies, GeoEye and Digital Global; internal and external relationships encompassing the spatial, attribute, and comprehensive relationships between internal elements and between different objects, such as parent-child joints in geometric construction, constellation networking, and communication links. These relationships themselves also possess characteristics such as timeliness, strength, and rule constraints; and behavior / actions referring to a series of actions performed by the object according to instructions or programs, as well as the capabilities possessed by the object itself (including components). Behaviors can be categorized into spatial, attribute, relational, and composite behaviors, supporting actions such as orbit changes, rendezvous and docking, solar orientation, and attack countermeasures.

[0044] S103. Match the target spatiotemporal object data to the corresponding parameters of the initial spatiotemporal object model and fill in the data to obtain the final spatiotemporal object model.

[0045] After obtaining the target spatiotemporal object data, the model parameters can be updated based on the data to make the spatiotemporal object model more realistically reflect the real state of the spatial target object and improve the model accuracy.

[0046] When constructing a spatiotemporal object model for spatial targets, it is necessary to achieve a high degree of abstraction of the object ontology while also ensuring the comprehensiveness of the descriptive information and reflecting individual characteristics, such as... Figure 5 The Time-Space-Behavior Model (TSBM) shown consists of five elements: attribute information, ephemeris orbit, attitude parameters, entity model, and behavior actions. Each element can be described using the Unified Modeling Language (UML).

[0047] The attribute information includes: static attribute information that is the same as the life cycle of the spatial entity and / or dynamic attribute information composed of multiple indivisible attribute fragments, wherein the dynamic attribute information is represented by the attribute fragment period and the fixed attribute value within the attribute fragment period.

[0048] Most of the attribute information of space targets cannot be changed or will not change after the start of operation, such as launch date, launch site, and launch vehicle; however, some attributes may change due to human operation or space events, such as the association and updating of target numbers by space situational awareness departments, and the change of target category if a satellite collides and disintegrates into debris. Therefore, TSBMs design attribute information into two types: static and dynamic, the difference being whether or not attribute changes are included. Figure 6 As shown, the formal representation of attribute information can be expressed as follows:

[0049] Property = {[ StaticProperty ] , [ ActiveProperty: List <propertysegment>< / propertysegment> ]}

[0050] in, StaticProperty This represents static attributes (more than one), whose lifecycle is the same as that of the target object. ActiveProperty Represents dynamic properties (more than one), consisting of multiple indivisible property fragments. PropertySegment Its composition, in its formal expression, can be described as follows:

[0051] PropertySegment = { Period: { StartTime, EndTime} , Value}

[0052] in, Period Represents the period of a segment, starting from the beginning time. StartTime and end time EndTime composition, Value These are fixed attribute values ​​within this period.

[0053] An ephemeris orbit consists of multiple ephemeris segments, and each ephemeris segment includes a life cycle representing the ephemeris segment's time life, a coordinate system representing the spatial reference for orbit calculation, and orbit information consisting of orbit enumeration types and orbit parameters.

[0054] Ephemeris orbits are used to determine the spatial position of a space target in a reference coordinate system at any given time. They consist of multiple ephemeris segments, each containing a description of its lifecycle, coordinate system, and orbital information. The orbits themselves are categorized into Keplerian, two-element, and discrete-point orbit types. The first two types require specific orbit prediction models to calculate the target's position. The design of ephemeris orbits in TSBMs is as follows... Figure 7 As shown, the formal expression of the ephemeris orbit can be represented as follows:

[0055] Trajectory = { TrajectorySegment: { TimeLine, CoordinateSystem, Type,

[0056] {LoiteringKepler | LoiteringTLE | LoiteringPoint | LoiteringEquation}}}

[0057] in, TrajectorySegment Represents at least one ephemeris segment; TimeLine The ephemeris represents a time lifeline, including start and end times and step size; coordinate system. CoordinateSystem The spatial reference for orbit calculation; orbit type Type It is an enumeration type, including Kepler. Kepler Double-row roots TLE Discrete point navigation Point The first two types support position estimation with known orbital elements, while the latter supports offline or real-time tracking data for non-orbiting targets such as ballistic missiles and spaceplanes; the corresponding orbital parameters include Kepler orbits. LoiteringKepler Double-row roots LoiteringTLE Discrete point navigation LoiteringPoint、 Equation-driven LoiteringEquation The composition of each orbital parameter is different and needs to be specifically defined, taking the Kepler orbit as an example. LoiteringKepler For example, the formal expression can be described as follows:

[0058] LoiteringKepler= { PropagationPostion, InitialPos}

[0059] in, PropagationPostion Represents orbital predictors, including predictor types. Propagator The types of mechanics considered include unperturbed two-body motion, J2 perturbation, J4 perturbation, etc.; integral types. Integrator This represents the type of numerical solution, such as the RK method, RKF method, Adams method, Cowell method, etc. TimeStep Represents the integration step size. Initial orbital elements. InitialPos Including epochal moments InitialEpoch and Kepler's six roots KeplerianElements .

[0060] The attitude parameters consist of one or more attitude segments, and each attitude segment includes the attitude lifecycle, reference space coordinate system, and specific attitude change data used to represent the attitude ephemeris time lifeline. The specific attitude change data consists of an attitude change enumeration type and an attitude parameter representation type.

[0061] Attitude parameters are used to determine the attitude of the target's body coordinate system in the reference coordinate system at any given time. They can consist of one or more attitude segments, each containing a description of the lifecycle, reference coordinate system, and specific attitude changes. The design of attitude parameters in a TSBM is as follows: Figure 8 As shown, the formal expression of the attitude parameters is as follows:

[0062] Attitude = { AttitudeSegment: { TimeLine, CoordinateSystem, Type,Style,

[0063] { AttitudeFixed | AttitudeEquation | AttitudeDispersed}}}

[0064] in, AttitudeSegment Represents at least one attitude segment; TimeLine The lifeline of the posture ephemeris; CoordinateSystem Represents the reference spatial coordinate system, typically the orbital coordinate system; Type This is an enumeration type for attitude change, including fixed-pointing types. Fixed Equation-driven type Equation and discrete attitude type Dispersed Three types, expandable; attitude representation types Style This refers to the representation of attitude parameters, including Euler angles (identifying different orders) and quaternion representation. Different types of attitude parameters include: fixed-pointing attitude. AttitudeFixed The attitude of the spatial target relative to the reference coordinate system remains constant within this cycle; the equation drives the attitude. AttitudeEquation The attitude of a space target changes according to certain rules or models, such as uniform rotation, three-axis stability, spin stability, etc., specifically defined by equations; discrete attitude. AttitudeDispersed, The attitude data of space targets are discrete and irregular, and mainly come from tracking and observation data of targets such as missiles and space shuttles.

[0065] The entity model is composed of nested entity components. The parent and child components establish the relationship between the parent and child component nodes in terms of behavior and action through the component parent node identifier. The component material characteristics are recorded on the component node, and the pose, shape and constraints of the entity component are stored through geometric variables.

[0066] The solid model comprehensively considers the composition of the target entity (including materials) and the three states, capabilities, and constraints of sensors. The model is composed of nested components, with parent and child nodes linked by identifiers. Materials are related to target characteristics and are recorded on component nodes. Geometric variables store the pose, shape, and constraints of the internal components of the solid. Furthermore, the model can also record the parameters and constraints of the sensors attached to the components. Solid model design in TSBM is as follows: Figure 9 As shown, the formal expression of the entity model can be described as follows:

[0067] EntityModel = { ID, Component: { ID, FID, Material, ComponentList , PrimitiveList,

[0068] Geometry, [Sensor ] , State}}

[0069] in, ID It serves as a unique identifier for an entity model or component, allowing external objects to establish an association with the model. Component Represents a model component (at least one). FID Identifier for the parent node of the component ， Establish the relationship between internal parent and child nodes in terms of behavior and actions; Material Recording component material properties can further include information such as material composition, emissivity, reflectivity, and roughness, providing support for property analysis; ComponentList This is a list of child node components contained in this component. By nesting, the hierarchical relationship between components is established, enabling more complex model construction. PrimitiveList It consists of primitives that cannot be further divided into components. Primitive types include model files, points, lines, surfaces, and texture information created using commercial modeling software (such as Maya, 3ds Max, AutoCAD). State The parameters record the detailed status of each component, such as the component's temperature, humidity, on / off status, and whether it is alive or dead. Geometry This represents the geometric deformation and constraints of the existing component shape, with deformation variables including translation. Translate Rotation Rotate and scaling Scale All three types include a local coordinate system relative to the parent node. X ,Y ,Z The changes in the three directions can be uniformly expressed as ( xVariable, yVariable, zVariable ); Sensor Record information about the sensor capabilities of the components (leaning towards a virtual level), such as optical lenses, radar antennas, and radio signal transmitters. Type The sensor type (expandable) and sensor parameter list are recorded. ParameterList and constraint list ConstraintList A specific definition is needed. Taking a CCD reconnaissance camera with an area array as an example, its rectangular sensor... ParameterList It should at least include the vertical field of view and the horizontal field of view, and if combined with Geometry The rotation in three directions can be used to simulate side-view, front-back, and horizontal rotation reconnaissance imaging.

[0070] A behavior consists of a series of behavior segments. Each behavior segment includes a behavior identifier, behavior type, behavior target, behavior triggering condition, behavior parameters, and behavior calculation model. Among them, the behavior type includes attribute behavior type, ephemeris behavior type, posture behavior type, and model behavior type.

[0071] Actions are primarily used to express changes in the four types of ontology elements and their contained relationships. A series of action fragments constitute all the actions in the model. Each action fragment includes an identifier, type, target, triggering condition, action parameters, and action calculation model. Action design in TSBM is as follows: Figure 10 As shown, the formal expression of behavior and action can be described as follows:

[0072] Behavior = { BehaviorSegment: { ID, BehaviorType, ReceptorID, Condition,

[0073] Parameters, Model}}

[0074] in, BehaviorSegment Represents a single behavioral segment. ID It is a unique identifier for a behavior or action; BehaviorType These represent four types of behavior: attributes, ephemeris, pose, and model behavior. ReceptorID This serves as an identifier for the target object, which could be the entire target, a specific component, a sensor, etc. Condition The triggering conditions cover various aspects that may trigger behavioral actions, and the application scenarios for each condition setting are shown in Table 1.

[0075] Table 1 Explanation of Action Triggering Conditions

[0076]

[0077] Four typical behaviors can be achieved by inheriting behavioral fragments, including attribute behaviors. PropertyBehavior Ephemeral behavior TrajectoryBehavior Postural behavior AttitudeBehavior and model behavior ModelBehavior The four behaviors correspond to changes in the first four categories of elements in the TSBM, and the magnitude of the change is related to the behavior parameters. Parameters and behavioral computation model Model Closely related, the specific form is determined by behavior type, scene setting, and physical model.

[0078] The Spatiotemporal Behavior Integrated Model (TSBM) can provide a comprehensive description of spatiotemporal objects of spatial targets. It is important to note that the internal and external relationships of spatial targets are not listed separately, but are incorporated into the design within the model. For example, parent-child joints in geometric construction are determined through component nesting, network relationships are recorded through constellation attributes, and communication links are defined through sensor parameters in the entity model.

[0079] Furthermore, based on the above method, this embodiment of the invention also provides a spatial target object modeling system, comprising: a model initialization module, a data acquisition module, and a data filling module, wherein,

[0080] The model initialization module is used to determine the model construction parameters and the three-dimensional space to be modeled, and to construct an initial spatiotemporal object model of the three-dimensional space according to the model construction parameters. The three-dimensional space includes at least one spatial entity, and the model construction parameters include attribute information, ephemeris orbit, attitude parameters, entity model and behavior action.

[0081] The data acquisition module is used to acquire spatiotemporal object data of a target in three-dimensional space based on a preset semantic description framework. The preset semantic description framework includes: spatiotemporal reference semantic description, spatiotemporal position semantic description, posture parameter semantic description, morphological material semantic description, state information semantic description, attribute information semantic description, internal and external relationship semantic description, and behavioral capability semantic description.

[0082] The data filling module is used to match the target spatiotemporal object data with the corresponding parameters of the initial spatiotemporal object model and fill the data to obtain the final spatiotemporal object model.

[0083] To verify the effectiveness of this solution, the following explanation is based on experimental data:

[0084] The construction of the TSBM model resembles a "loop," originating from the description of space target characteristics and evolving into an integrated spatiotemporal behavior model through abstraction and digital modeling. The ultimate goal of the model is to serve space target situational awareness applications, and its quality is evaluated accordingly. Therefore, the experiment started from the "end point" of the loop and analyzed the TSBM model's ability to describe and cover the WorldView-4 satellite (the "start point" of the loop), thus achieving closed-loop verification of the model, as shown in Table 2.

[0085] Table 2 Closed-loop coverage of WorldView-4 satellites as described by the TSBM model

[0086]

[0087] As can be seen from the corresponding coverage relationship in the table above, the TSBM model can complete a comprehensive description of the static and dynamic information of the WorldView-4 satellite, realize the closed loop of model construction, verify the effectiveness of the TSBM model constructed by the proposed solution, and can be applied to the situational awareness of space targets.

[0088] Unless otherwise specifically stated, the relative steps, numerical expressions, and values ​​of the components and steps described in these embodiments do not limit the scope of the invention.

[0089] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the systems disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the descriptions are relatively simple; relevant parts can be referred to the method section.

[0090] The units and method steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of each example have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations are not considered to be beyond the scope of this invention.

[0091] Those skilled in the art will understand that all or part of the steps in the above methods can be implemented by a program instructing related hardware, and the program can be stored in a computer-readable storage medium, such as a read-only memory, a disk, or an optical disk. Optionally, all or part of the steps in the above embodiments can also be implemented using one or more integrated circuits. Accordingly, each module / unit in the above embodiments can be implemented in hardware or as a software functional module. This invention is not limited to any particular combination of hardware and software.

[0092] Finally, it should be noted that the above-described embodiments are merely specific implementations of the present invention, used to illustrate the technical solutions of the present invention, and not to limit it. The scope of protection of the present invention is not limited thereto. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that any person skilled in the art can still modify or easily conceive of changes to the technical solutions described in the foregoing embodiments within the technical scope disclosed in the present invention, or make equivalent substitutions for some of the technical features; and these modifications, changes, 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, and should all be covered within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for modeling spatial target objects, characterized in that, Include: The model construction parameters and the 3D space to be modeled are determined, and an initial spatiotemporal object model of the 3D space is constructed based on the model construction parameters. The 3D space includes at least one spatial entity, and the model construction parameters include attribute information, ephemeris orbit, attitude parameters, entity model, and behavioral actions. Constructing the initial spatiotemporal object model of the 3D space based on the model construction parameters includes: Based on the model construction parameters, and using the Unified Modeling Language, spatial entity objects are formally represented as follows: SpaceObj ={ OID, [ Property ] , Trajectory, Attitude, EntityModel, [ Behavior Based on formal representation and utilizing digital means, spatial entity objects are mapped to digital space, and a spatiotemporal entity object model is obtained. This model is then updated with real-time data on spatial targets. SpaceObj For spatial target spatiotemporal entity objects ， [ ] represents a parameter that can be null; OID is a unique identifier for the target object, used to represent the index of records, associations, and behaviors between different objects and between elements within an object; Property represents attribute information; Trajectory represents ephemeris orbit; Attitude represents attitude parameters; EntityModel represents entity model; Behavior represents the behavior of spatiotemporal entity objects; Data of target spatiotemporal objects in three-dimensional space are obtained based on a preset semantic description framework. The preset semantic description framework includes: spatiotemporal reference semantic description, spatiotemporal position semantic description, posture parameter semantic description, morphological material semantic description, state information semantic description, attribute information semantic description, internal and external relationship semantic description, and behavioral capability semantic description. The target spatiotemporal object data is matched to the corresponding parameters of the initial spatiotemporal object model and the data is filled in to obtain the final spatiotemporal object model.

2. The spatial target object modeling method according to claim 1, characterized in that, The attribute information includes: static attribute information that is the same as the life cycle of the spatial entity and / or dynamic attribute information composed of multiple indivisible attribute fragments, wherein the dynamic attribute information is represented by the attribute fragment period and the fixed attribute value within the attribute fragment period.

3. The spatial target object modeling method according to claim 1, characterized in that, The ephemeris orbit consists of multiple ephemeris segments, and each ephemeris segment includes a life cycle representing the ephemeris segment's time life, a coordinate system representing the spatial reference for orbit calculation, and orbit information composed of orbit enumeration types and orbit parameters.

4. The spatial target object modeling method according to claim 1, characterized in that, The attitude parameters consist of one or more attitude segments, and each attitude segment includes an attitude lifecycle, a reference spatial coordinate system, and specific attitude change data to represent the attitude ephemeris time lifeline. The specific attitude change data consists of an attitude change enumeration type and an attitude parameter representation type.

5. The spatial target object modeling method according to claim 1, characterized in that, The entity model is composed of nested entity components. The parent and child components establish the relationship between the parent and child component nodes in terms of behavior and action through the component parent node identifier. The component material characteristics are recorded on the component node, and the posture, shape and constraints of the entity component are stored through geometric variables.

6. The spatial target object modeling method according to claim 1, characterized in that, The behavior consists of a series of behavior segments. Each behavior segment includes a behavior identifier, behavior type, behavior target, behavior triggering condition, behavior parameters, and behavior calculation model. The behavior type includes attribute behavior type, ephemeris behavior type, posture behavior type, and model behavior type.

7. A spatial target object modeling system, characterized in that, It includes: a model initialization module, a data acquisition module, and a data population module. The model initialization module is used to determine the model construction parameters and the 3D space to be modeled, and to construct an initial spatiotemporal object model of the 3D space based on the model construction parameters. The 3D space includes at least one spatial entity, and the model construction parameters include attribute information, ephemeris orbit, attitude parameters, entity model, and behavioral actions. Constructing the initial spatiotemporal object model of the 3D space based on the model construction parameters includes: Based on the model construction parameters, and using the Unified Modeling Language, spatial entity objects are formally represented as follows: SpaceObj ={ OID, [ Property ] , Trajectory, Attitude, EntityModel, [ Behavior Based on formal representation and utilizing digital means, spatial entity objects are mapped to digital space, and a spatiotemporal entity object model is obtained. This model is then updated with real-time data on spatial targets. SpaceObj For spatial target spatiotemporal entity objects ， [ ] represents a parameter that can be null; OID is a unique identifier for the target object, used to represent the index of records, associations, and behaviors between different objects and between elements within an object; Property represents attribute information; Trajectory represents ephemeris orbit; Attitude represents attitude parameters; EntityModel represents entity model; Behavior represents the behavior of spatiotemporal entity objects; The data acquisition module is used to acquire spatiotemporal object data of a target in three-dimensional space based on a preset semantic description framework. The preset semantic description framework includes: spatiotemporal reference semantic description, spatiotemporal position semantic description, posture parameter semantic description, morphological material semantic description, state information semantic description, attribute information semantic description, internal and external relationship semantic description, and behavioral capability semantic description. The data filling module is used to match the target spatiotemporal object data with the corresponding parameters of the initial spatiotemporal object model and fill the data to obtain the final spatiotemporal object model.

8. An electronic device, characterized in that, include: At least one processor, and a memory coupled to said at least one processor; The memory stores a computer program that can be executed by the at least one processor to implement the method as described in any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed, enables the implementation of the method as described in any one of claims 1 to 6.

Images