Space target object modeling method and system

Abstract

The invention relates to the technical field of spatio-temporal data modeling, in particular to a space target object modeling method and system, and the method comprises the steps: determining model construction parameters and a to-be-modeled three-dimensional space, and constructing a three-dimensional space initial spatio-temporal object model according to the model construction parameters, the model construction parameters comprise attribute information, ephemeris orbits, attitude parameters, entity models and behavior actions; obtaining target space-time object data in a three-dimensional space based on a preset semantic description framework, the preset semantic description framework comprises space-time reference semantic description, space-time 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 ability semantic description; and matching the target space-time object data to corresponding parameters of the initial space-time object model, and performing data filling to obtain a final space-time object model. According to the method, the distribution characteristics of the overall situation of the space target object in time, space and attributes can be established from the dimension of situation space-time development, and a foundation is laid for real-time driving, visual expression, omnibearing cognition and precise analysis of the space target.

Description

Technical Field

[0001] The present invention relates to the technical field of spatiotemporal data modeling, and in particular to a space target object modeling method and system suitable for situation awareness of space target objects. Background Art

[0002] With the development of space technology, space target situational awareness has been highly valued as a basic means to master space information advantages. Compared with ground targets, space targets have obvious spatiotemporal characteristics and prominent individual characteristics. Modeling, situation analysis, cognitive expression and application of space targets are urgently needed. A perfect model is the premise of data organization, management, expression and application. At present, there are many computational models related to the situation of space targets, while the research on the construction of spatiotemporal models based on ontology abstraction is relatively small and not in-depth. Therefore, how to construct a visual and all-round cognitive space target spatiotemporal behavior integrated model based on ontology semantic description is a technical problem that needs to be solved in the current space target situational awareness. Summary of the invention

[0003] To this end, the present invention provides a spatial target object modeling method and system, which can establish the distribution characteristics of the overall situation of the spatial target object in time, space, and attributes from the dimension of situational spatiotemporal development, laying the foundation for real-time driving, visual expression, all-round 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 a space target object is provided, comprising:

[0005] Determining model building parameters and a three-dimensional space to be modeled, and building an initial spatiotemporal object model of the three-dimensional space according to the model building parameters, wherein the three-dimensional space includes at least one spatial entity, and the model building parameters include attribute information, ephemeris orbit, attitude parameters, entity model, and behavior action;

[0006] Based on a preset semantic description framework, target spatiotemporal object data in three-dimensional space is obtained, 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;

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

[0008] As a spatial target object modeling method of the present invention, further, 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.

[0009] As a space target object modeling method of the present invention, further, the ephemeris orbit is 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 orbit calculation space reference, and orbit information composed of an orbit enumeration type and orbit parameters.

[0010] As a space target object modeling method of the present invention, further, the attitude parameters are composed of one or more attitude segments, and each attitude segment includes an attitude life cycle, a reference space coordinate system and specific attitude change data for representing the attitude ephemeris segment time lifeline, wherein 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, further, the entity model is composed of nested entity components, wherein entity parent-child components establish associations between parent-child component nodes in behavioral actions through component parent node identifiers, record component material properties on component nodes, and store entity component postures, forms and constraints through geometric variables.

[0012] As a space target object modeling method of the present invention, further, the behavior action is composed of a series of behavior fragments, each behavior fragment includes a behavior action identifier, a behavior action type, a behavior action object, a behavior action trigger condition, a behavior action parameter and a behavior action calculation model, wherein the behavior action type includes an attribute behavior type, an ephemeris behavior type, a posture behavior type and a model behavior type.

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

[0014] Based on the model construction parameters and the unified modeling language, the spatial entity object is formally represented as: SpaceObj = {OID, [Property], Trajectory, Attitude, EntityModel, [Behavior]}. According to the formal representation and using digital means, the spatial entity object is mapped to the digital space, and the spatiotemporal entity object model is obtained to update the spatial target object data content in the model according to the real-time data of the space target. Among them, SpaceObj is the spatial target spatiotemporal entity object, [] represents a parameter that can be empty; OID is the unique identifier of the target object, which is used to represent the index of recording associations and behaviors between different objects and between elements within the object; Property represents attribute information; Trajectory represents ephemeris orbit; Attitude represents attitude parameters; EntityModel represents entity model; Behavior represents the behavior of the spatial spatiotemporal entity object.

[0015] In another aspect, the present invention further provides a space target object modeling system, comprising: a model initialization module, a data acquisition module and a data filling module, wherein:

[0016] A model initialization module, used to determine model construction parameters and a 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, wherein 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] A data acquisition module is used to acquire 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;

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

[0019] Beneficial effects of the present invention:

[0020] The present invention first determines the three-dimensional space to be modeled, wherein the three-dimensional space includes at least one spatial entity; then, according to the preset semantic description rules, the object semantic description of the spatial entity in the three-dimensional space is obtained, and the object semantic description includes: attribute information, ephemeris orbit, attitude parameters, entity model and behavior action; then, according to the object semantic description, the individual characteristics of the spatial entity are extracted, so as to construct a spatiotemporal entity object model based on the individual characteristics and by using digital means, and the individual characteristics of the spatial entity include: spatiotemporal change characteristics of the spatial entity, granularity characteristics, entity three-state characteristics and system association characteristics. By using the above technical scheme, the individual characteristics and overall situation of the spatial target are extracted on the basis of clarifying the scope and classification of the spatial target, the spatiotemporal benchmark and conversion, and the spatiotemporal object model of the spatial target is preliminarily determined based on the semantic description of the spatial entity and the individual characteristics, so as to realize the construction of an integrated spatiotemporal model, solve the problem of insufficient modeling accuracy in the existing spatial target modeling technology, improve the modeling accuracy of the spatial target, facilitate the loading of the spatial target spatiotemporal entity into the digital space world, generate the spatial target spatiotemporal object, and timely and effectively solve the problem of updating the spatial target spatiotemporal object data in the spatial situation awareness, and have a good application prospect. BRIEF DESCRIPTION OF THE DRAWINGS

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

[0022] Figure 2 It is a schematic diagram of the correspondence between the semantic description of the space target and the individual characteristics in the embodiment;

[0023] Figure 3 This is a schematic diagram of the space-time object system of the space target in the embodiment;

[0024] Figure 4 This is a schematic diagram of the space target spatiotemporal object description framework in the embodiment;

[0025] Figure 5 It is a schematic diagram of the integrated model of space-time behavior of space targets in the embodiment;

[0026] Figure 6 Schematic diagram of TSBM attribute information in the embodiment;

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

[0028] Figure 8 TSBM attitude parameters in the embodiment are shown;

[0029] Fig. 9 It is a schematic diagram of the TSBM entity model in the embodiment;

[0030] Fig.10 Schematic diagram of TSBM behavior action elements in the embodiment. DETAILED DESCRIPTION

[0031] In order to make the purpose, technical solutions and advantages of the present invention clearer and more understandable, the present invention is further described in detail below in conjunction with the accompanying drawings and technical solutions.

[0032] Modeling is an abstraction made to understand things. In the field of traditional geographic spatial information, spatial data modeling is the process of abstracting geographic spatial data into digital maps from the real geographic world to the digital map world. With the promotion and in-depth application of computer technology, spatial data that changes over time has attracted people's attention. The concept of spatiotemporal data has emerged, and many spatiotemporal data models have been proposed one after another. The more typical ones include spatiotemporal composite, continuous snapshot, ground state correction, spatiotemporal cube, object-oriented\event\process spatiotemporal data models. In recent years, technologies such as aerospace, sensors, mobile Internet, and big data have developed by leaps and bounds. From the surface to the ocean, underground, deep space, from outdoor to indoor, from macro to micro, the type, amount, and timeliness of spatiotemporal data have undergone earth-shaking changes. Traditional geographic information systems and spatiotemporal data models are difficult to meet the requirements in terms of scale space, continuous change, and association description. Concepts such as full spatial information system, multi-granularity entity, multi-granularity spatiotemporal object, and multi-granularity spatiotemporal object data model have been proposed one after another.

[0033] As a relatively new entity with a unique range of activities, space targets have certain particularities compared to common entities. In view of the needs for space target situational awareness in space security, information confrontation, and aerospace support, the embodiments of the present invention refer to Figure 1 As shown, a spatial target object modeling method is provided, comprising:

[0034] S101. Determine model construction parameters and a three-dimensional space to be modeled, and construct an initial spatiotemporal object model of the three-dimensional space according to the model construction parameters, wherein 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.

[0035] Among them, the three-dimensional space needs to be three-dimensionally modeled, which can be determined based on a preset three-dimensional space selection instruction. After the three-dimensional space is determined, a spatial target object model can be constructed to restore various spatial entity objects and environments in the three-dimensional space.

[0036] The initial spatiotemporal object model of the three-dimensional space is constructed based on the model construction parameters, which can be designed to include:

[0037] The spatial entity object is formally represented by a unified modeling language such as structure as: SpaceObj = {OID, [Property], Trajectory, Attitude, EntityModel, [Behavior]}. Based on the formal representation and using digital means, the spatial entity object is mapped to the digital space, and the spatiotemporal entity object model is obtained to update the spatial target object data content in the model according to the real-time data of the space target. Among them, SpaceObj is the spatial target spatiotemporal entity object, [] represents a parameter that can be empty; OID is the unique identifier of the target object, which is used to represent the index of recording associations and behaviors between different objects and between elements within the object; Property represents attribute information; Trajectory represents ephemeris orbit; Attitude represents attitude parameters; EntityModel represents entity model; Behavior represents the behavior of the spatial spatiotemporal entity object.

[0038] S102. Acquire 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] The fifth-generation high-resolution earth observation satellite WorldView-4 of a certain company was selected, and the static information of the satellite was 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, owner, etc., as well as launch information such as launch date, location and type of carrier rocket used; (2) Platform status, as the main body of the space target, records the type, expected life, structural shape and basic storage and transmission capabilities of the platform; (3) Orbital status, the space target is affected by the gravity of the central celestial body and other perturbations and performs periodic motion. Orbital parameters are often used to describe its operating position, shape and orientation, including reference system, semi-major axis, inclination, eccentricity, etc.; (4) Attitude control status, the pointing state of the space target in orbit, and the parameters mainly include attitude control type, actuator, sensors used, etc.; (5) Payload, the instruments and equipment directly carrying out the mission carried by the space target, is an important component of it, with various types and compositions. For earth imaging satellites, it mainly includes imaging mode, sensor band, resolution, coverage width and other information. The descriptions of the above five aspects cover all the static contents of the space target, from appearance to interior, from representation to function.

[0040] After obtaining the semantic description information, the temporal and spatial changes, granularity, entity three states and system association of the spatial target can be extracted. The corresponding relationship between the semantic description and the individual characteristics is as follows: Figure 2 As shown. Among them, time scale and space coordinates are two basic characteristics that identify all natural things and social phenomena. Together, they constitute two basic facts of the existence of moving matter and are objective. The five aspects of the semantic description of space targets are all related to time and space information, and as a new thing with stronger mobility, the characteristics of time and space changes are more prominent. Compared with general moving targets, the time and space characteristics of space targets are mainly reflected in complex time and space reference systems and high-speed operation states in addition to their attributes, behaviors, and relationships. Granularity, also known as granularity, refers to the degree to which an object or system can be subdivided. The granularity characteristics of space targets are mainly reflected in the comparison of time and space scales, which are related to the five aspects of semantic description. In terms of time scale, the universe where the space target is located has a history of 13.8 billion years, and the accuracy of the atomic clock used as a timing benchmark has reached an error of no more than 1 second in 3.7 billion years; in terms of space 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, in the seemingly vast space, the collision between the US and Russian satellites in 2009 still occurred, which to some extent reflects the relativity of the granularity of space targets. Space environment and space targets are the two main elements of the current space. Compared with the former, the entity characteristics of space targets are more obvious, with certain observability and measurability. The attitude, form, and state have become the focus of attention, from which we can further extract information such as the target's mission, intention structure, etc. This aspect of the characteristics is closely related to the platform, attitude control, and payload. At present, for non-cooperative targets, three means are mainly used for identification, detection, and monitoring: optics (visible light, infrared), radar, and radio. In view of the global nature of the operation of space targets and the particularity of the execution of tasks, their system integration and link association characteristics are more obvious. Taking navigation satellites as an example, in principle, at least three satellites are needed above the 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 in the air, and their ultimate goal is to provide services for human activities on the surface of the earth. Therefore, they are not isolated individuals. Command uploading, data downloading, relay communications, etc. all need to be associated with ground targets or other space targets.

[0041] As a more distant, vast and new space, the cognition of the space world becomes clearer with the deepening of exploration. Space targets are an important part of the active space, and abstract modeling is an important part of describing and expressing the real space world. The relationship 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, such as Figure 3 shown.

[0042] In the embodiments of this case, it can be considered that the real space world is composed of an infinite number of space targets; through extraction, simplification, abstraction and description, it is abstracted into a space target space-time entity in the space simulation world, and endowed with space-time changes, granularity, entity three states, and system association characteristics; digital modeling means are used to load the space target space-time entity into the digital space world to generate a space target space-time object. The space target data comes from the data acquisition and collection of space targets in the real space world and the space model world, and is used to update the data content of the space target space-time object. Therefore, in the embodiments of this case, the space target space-time object is used as an abstract and digital mapping of the space target in the real space world, which is a specific description of the space target space-time entity in the digital space. The corresponding process is used as the space target space-time object modeling, and the constructed digital model is the space target space-time object model, which can also be called the space target space-time model.

[0043] To build a model, we first need to start from data, rules, logic and other aspects, comprehensively analyze and describe the object under study, and complete a "precise portrait". Describe the multi-granularity spatiotemporal objects from eight aspects, such as spatiotemporal reference, spatial position, and spatial form. Based on the analysis of the current spatial target data, individual characteristics, and situation statistics, a matching spatial target spatiotemporal object description framework is developed, such as Figure 4 As shown in the figure, it can include eight aspects: space-time reference, space-time position, attitude parameters, morphological material, state information, attribute information, internal and external relations, and behavioral actions. Among them, the space-time reference is used as a scale to record the space-time information of space targets, and the time and space reference coordinate system is the basis for describing other information; space-time position information is one of the most basic and important contents in describing the space-time object of space targets. The corresponding orbit determination (orbit determination) work generally requires post-processing of the tracking and measurement data of the aerospace measurement and control network. After the initial orbit determination or even precise orbit determination, the basic state quantity of the space target is calculated, that is, the position and velocity vector of the space target at time t in the selected space coordinate system. For "orbiting" space targets, elliptical orbit roots can also be used to represent them; attitude parameters describe the motion of space target space-time objects around the center of mass. The determination of attitude parameters is not only a requirement for performing specific space missions, but also closely related to orbit determination. The definition of attitude parameters can usually be expressed by the Euler angle of the local coordinate system relative to a certain reference coordinate system. Or Euler quaternion (q 1 ,q 2 ,q 3 ,q 4) to describe; morphological material comprehensively describes the geometric shape, composition and physical material of the space target space-time object, which can usually be represented in the form of a three-dimensional geometric model. In addition, its composition structure and surface material information can be annotated; state information describes the internal environment and working status of the space target space-time object, such as the life and death status of the target, the temperature of the components, the on / off of the load, etc.; attribute information describes the name, number, type, background, etc. It should be noted that attribute information can also be divided into static and dynamic attributes. For example, the NASA number of the WorldView-4 satellite has always been 41848, but its asset ownership changed around 2013 and belonged to different companies, GeoEye and Digital Global; internal and external relationships include the space, attribute, and comprehensive association relationships between the internal elements of the object and between different objects, such as the parent-child joints in geometric structures, constellation networking, communication links, etc. The relationship itself also has characteristics such as timeliness, strength, and rule constraints; behavior refers to a series of actions performed by the object according to instructions or programs and the capabilities of the object itself (including components). Behavior can be divided into space, attribute, relationship, and composite behavior according to type, supporting such as orbit change, rendezvous and docking, solar orientation, attack confrontation, etc.

[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 actual state of the spatial target object and improve the model accuracy.

[0046] When constructing the spatiotemporal object model of a space target, it is necessary to achieve a high degree of abstraction of the object ontology, while taking into account the comprehensiveness of the description information and reflecting the individual characteristics, such as Figure 5 The time-space-behavior integrated model (TSBM) shown in the figure is composed of five types of elements: attribute information, ephemeris orbit, attitude parameters, entity model and behavior action. Each type of 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 space entity and / or dynamic attribute information composed of multiple indivisible attribute segments, wherein the dynamic attribute information is represented by the attribute segment period and the fixed attribute value within the attribute segment period.

[0048] Most of the attribute information of space targets cannot be changed or will not change from the beginning of operation, such as the launch date, launch location, launch vehicle, etc. However, due to human operations or space events, some attributes may change, such as the association and update of target numbers by the space situational awareness department, and the target category may change if the satellite becomes fragments after collision and disintegration. Therefore, TSBM divides attribute information into two types of design: static and dynamic, and the difference lies in whether it contains attribute changes. Figure 6 As shown, the formal expression of attribute information can be expressed as follows:

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

[0050] Among them, StaticProperty represents static properties (more than one), and its life cycle is the same as the target ontology; ActiveProperty represents dynamic properties (more than one), which is composed of multiple indivisible property segments PropertySegment, and its formal expression can be described as follows:

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

[0052] Among them, Period represents the segment period, which is composed of the start time StartTime and the end time EndTime, and Value is the fixed attribute value within the period.

[0053] An ephemeris orbit is composed of multiple ephemeris segments, and each ephemeris segment includes a life cycle for representing the temporal life of the ephemeris segment, a coordinate system for representing a spatial reference for orbit calculation, and orbit information consisting of an orbit enumeration type and orbit parameters.

[0054] The ephemeris orbit is used to determine the spatial position of a space target in the reference coordinate system at any time. It consists of multiple ephemeris segments, each of which contains a description of the life cycle, coordinate system and orbit information. The orbit itself is divided into Kepler, two-row root, discrete point navigation and other forms. The first two orbit types require the calculation of the target position through a specific orbit prediction model. Figure 7 As shown, the formal expression of the ephemeris orbit can be expressed as follows:

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

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

[0057] Among them, TrajectorySegment represents the ephemeris segment (at least one); TimeLine represents the time lifeline of the ephemeris segment, including the start and end times and the step size; the coordinate system CoordinateSystem represents the spatial reference for orbit calculation; the orbit type Type is an enumeration type, including Kepler Kepler, double line element TLE, discrete point Point, etc. The first two types support position calculation with known orbit elements, and the latter supports offline or real-time tracking data for non-orbiting targets such as ballistic missiles and aerospace planes; the corresponding orbital parameters include Kepler orbit LoiteringKepler, double line element LoiteringTLE, discrete point LoiteringPoint, equation-driven LoiteringEquation. The composition of each orbital parameter is different and needs to be specifically defined. Taking Kepler orbit LoiteringKepler as an example, the formal expression can be described as follows:

[0058] LoiteringKepler={PropagationPostion,InitialPos}

[0059] Among them, PropagationPosition represents the orbit predictor, including the predictor type Propagator represents the type of mechanics considered, including non-perturbation two-body motion, J2 perturbation, J4 perturbation, etc.; the integral type Integrator represents the type of numerical solution, such as RK method, RKF method, Adams method, Cowell method, etc.; TimeStep represents the integration step. The initial orbit element InitialPos includes the epoch time InitialEpoch and Keplerian six elements KeplerianElements.

[0060] The attitude parameter is composed of one or more attitude segments, and each attitude segment includes an attitude life cycle for representing the attitude ephemeris segment time lifeline, a reference space coordinate system and specific attitude change data, wherein the specific attitude change data is composed of an attitude change enumeration type and an attitude parameter representation type.

[0061] The attitude parameters are used to determine the attitude of the space target's main coordinate system in the reference coordinate system at any time. They can be composed of one or more attitude segments, each of which contains a description of the life cycle, the reference coordinate system, and the specific attitude change. The attitude parameter design in TSBM is as follows: Figure 8 As shown, the formal expression of posture parameters is as follows:

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

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

[0064] Among them, AttitudeSegment represents the attitude segment (at least one); TimeLine is the time lifeline of the attitude ephemeris segment; CoordinateSystem represents the reference space coordinate system, which is generally the orbital coordinate system; Type is the attitude change enumeration type, which includes three types: fixed pointing type Fixed, equation driven type Equation and discrete attitude type Dispersed, which can be expanded; attitude representation type Style refers to the representation method of attitude parameters, including Euler angles (identified in different orders) and quaternion representation. Different attitude parameter types include: fixed pointing attitude AttitudeFixed, the attitude of the space target remains unchanged relative to the reference coordinate system during this period; equation driven attitude AttitudeEquation, the attitude of the space target changes according to certain rules or models, such as uniform rotation, three-axis stabilization, spin stabilization, etc., which are specifically defined by equations; discrete attitude AttitudeDispersed, the attitude data of the space target is discrete and irregular, and the main source is the tracking observation data of targets such as missiles and space shuttles.

[0065] The entity model is composed of nested entity components, in which entity parent-child components establish associations between parent-child component nodes in terms of behavioral actions through component parent node identifiers, record component material properties on component nodes, and store entity component postures, forms, and constraints through geometric variables.

[0066] The entity model comprehensively considers the composition of the target entity (including material) and the three states, capabilities and constraints of the sensor. The model is composed of nested components, and the parent-child node components are associated through identifiers; the material is related to the target characteristics and recorded on the component node; the internal component posture, form and constraints of the entity are stored through geometric variables; in addition, the model can also record the parameters and constraints of the sensors attached to the components. Fig. 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] Among them, ID is the unique identifier of the entity model or component, and external objects can establish an association with the model based on it. Component represents a model component (at least one). FID is the component parent node identifier, which establishes the association between internal parent and child nodes in terms of behavior and action; Material records the material properties of the component, which can further include information such as material composition, emissivity, reflectivity, roughness, etc., to provide support for characteristic analysis; ComponentList is a list of child node components contained in the component, and the hierarchical relationship between components is established through nesting to achieve more complex model construction; PrimitiveList is a primitive composition of components that cannot be further divided. Primitive types include those created using commercial modeling software (such as Maya, 3ds max, AutoCAD, etc.) The State parameter records the detailed status of each component, such as the temperature, humidity, open and closed, life and death status of the component; Geometry represents the geometric deformation and constraints of the existing component morphology. The deformation variables include translation, rotation and scale. All three contain the changes in the three directions relative to the local coordinate system (X, Y, Z) of the parent node, which can be uniformly expressed as (xVariable, yVariable, zVariable); Sensor records the sensor capability information attached to the component (biased at the virtual level), such as optical lens, radar antenna, radio signal transmitter, etc. Type records the sensor type (extensible), and the sensor parameter list ParameterList and constraint list ConstraintList need to be specifically defined. Taking the area array optical CCD reconnaissance camera as an example, the ParameterList of its rectangular sensor should at least contain the vertical field of view angle and the horizontal field of view angle. If combined with the rotation amount in the three directions in Geometry, the simulation of side view, front and back, and horizontal rotation reconnaissance imaging can be realized.

[0070] A behavior action is composed of a series of behavior fragments, each of which includes a behavior action identifier, a behavior action type, a behavior action object, a behavior action trigger condition, a behavior action parameter, and a behavior action calculation model. Among them, the behavior action type includes attribute behavior type, ephemeris behavior type, attitude behavior type, and model behavior type.

[0071] Behavior actions are mainly used to express the changes of the above four types of ontology elements and the relationships they contain. A series of behavior fragments constitute all the behavior actions of the model. Each behavior fragment contains identification, type, object, trigger condition, behavior parameter and behavior calculation model. Fig.10 As shown, the formal expression of the behavior action can be described as follows:

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

[0073] Parameters, Model}}

[0074] Among them, BehaviorSegment represents a single behavior segment, ID is the unique identifier of the behavior action; BehaviorType represents the behavior type, including attribute, ephemeris, attitude and model behavior; ReceptorID is the identifier of the object of action, which may be the target as a whole or a component, sensor, etc.; Condition is the trigger condition, covering all aspects that may trigger the behavior action. The application scenario description of each condition setting is shown in Table 1.

[0075] Table 1 Description of behavior action trigger conditions

[0076]

[0077] Four typical behaviors can be implemented by inheriting behavior fragments, including property behavior PropertyBehavior, ephemeris behavior TrajectoryBehavior, attitude behavior AttitudeBehavior and model behavior ModelBehavior. The four behaviors correspond to the changes of the first four elements of TSBM respectively. The change amount is closely related to the behavior parameters Parameters and the behavior calculation model Model. The specific form is determined by the behavior type, scene setting and physical model.

[0078] The space-time behavior integrated model TSBM can achieve a comprehensive description of the space-time objects of space targets. It should be noted that the internal and external relationships of space targets are not listed separately, but their design is included in the model. For example, the parent-child joints in geometric structure are determined by the nesting of components, the networking relationship is recorded by the constellation attributes, and the communication link is formulated by the sensor parameters in the physical model.

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

[0080] A model initialization module, used to determine model construction parameters and a 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, wherein 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] A data acquisition module is used to acquire 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;

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

[0083] In order to verify the effectiveness of this solution, the following is a further explanation based on experimental data:

[0084] The construction of the TSBM model is like a "loop", which originates from the description of space target characteristics and forms a spatiotemporal behavior integrated model through abstraction and digital modeling. The ultimate goal of the model is to serve the application of space target situation awareness, and its evaluation criteria also lie in this. To this end, the experiment starts from the "end point" of the loop and analyzes the description coverage capability of the TSBM model for the WorldView-4 satellite (the "starting point" of the loop), thereby realizing the closed-loop verification of the model, as shown in Table 2.

[0085] Table 2 Closed-loop coverage of TSBM model description of WorldView-4 satellite

[0086]

[0087]

[0088] It can be seen from the corresponding coverage relationship in the above table that the TSBM model can complete the 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 in this case, and can be applied to the situational awareness of space targets.

[0089] Unless otherwise specifically stated, the relative steps, numerical expressions and values ​​of the components and steps set forth in these embodiments do not limit the scope of the present invention.

[0090] In this specification, each embodiment is described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the embodiments can be referred to each other. For the system disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part.

[0091] The units and method steps of each example described in conjunction with the embodiments disclosed herein can be implemented by electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in the above description according to function. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. A person of ordinary skill in the art may use different methods to implement the described functions for each specific application, but such implementation is not considered to be beyond the scope of the present invention.

[0092] Those skilled in the art will appreciate that all or part of the steps in the above method can be completed by instructing related hardware through a program, 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 embodiment can also be implemented using one or more integrated circuits, and accordingly, each module / unit in the above embodiment can be implemented in the form of hardware or in the form of software function modules. The present invention is not limited to any specific form of combination of hardware and software.

[0093] Finally, it should be noted that the above-described embodiments are only specific implementations of the present invention, which are used to illustrate the technical solutions of the present invention, rather than to limit them. The protection scope of the present invention is not limited thereto. Although the present invention is described in detail with reference to the above-described embodiments, ordinary technicians in the field should understand that any technician familiar with the technical field can still modify the technical solutions recorded in the above-described embodiments within the technical scope disclosed by the present invention, or can easily think of changes, or make equivalent replacements for some of the technical features therein; and these modifications, changes or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.< / propertysegment>

Claims

1. A spatial target object modeling method, characterized in that: Include: Determining model building parameters and a three-dimensional space to be modeled, and building an initial spatiotemporal object model of the three-dimensional space according to the model building parameters, wherein the three-dimensional space includes at least one spatial entity, and the model building parameters include attribute information, ephemeris orbit, attitude parameters, entity model, and behavior action; Based on a preset semantic description framework, target spatiotemporal object data in three-dimensional space is obtained, 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; The target spatiotemporal object data is matched to the corresponding parameters of the initial spatiotemporal object model and the data is filled 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 space entity and / or dynamic attribute information composed of multiple indivisible attribute segments, wherein the dynamic attribute information is represented by an attribute segment period and a fixed attribute value within the attribute segment period.

3. The spatial target object modeling method according to claim 1, characterized in that: The ephemeris orbit is composed of multiple ephemeris segments, and each ephemeris segment includes a life cycle for representing the temporal life of the ephemeris segment, a coordinate system for representing a spatial reference for orbit calculation, and orbit information composed of an orbit enumeration type and orbit parameters.

4. The spatial target object modeling method according to claim 1, characterized in that: The attitude parameter is composed of one or more attitude segments, and each attitude segment includes an attitude life cycle for representing the attitude ephemeris segment time lifeline, a reference space coordinate system and specific attitude change data, wherein the specific attitude change data is composed of an attitude change enumeration type and an attitude parameter representation type.

5. The method for modeling a space target object according to claim 1, characterized in that: The entity model is composed of nested entity components, wherein entity parent-child components establish associations between parent-child component nodes in terms of behavioral actions through component parent node identifiers, record component material properties on component nodes, and store entity component postures, forms, and constraints through geometric variables.

6. The method for modeling a space target object according to claim 1, characterized in that: The behavior action is composed of a series of behavior fragments, each of which includes a behavior action identifier, a behavior action type, a behavior action object, a behavior action triggering condition, a behavior action parameter and a behavior action calculation model, wherein the behavior action type includes an attribute behavior type, an ephemeris behavior type, a posture behavior type and a model behavior type.

7. The method for modeling a space target object according to claim 1, characterized in that: Construct the initial spatiotemporal object model of the three-dimensional space according to the model construction parameters, including: Based on the model construction parameters and using the unified modeling language to formally represent the space entity object as: SpaceObj = {OID, [Property], Trajectory, Attitude, EntityModel, [Behavior]}, based on the formal representation and using digital means to map the space entity object to the digital space, and obtain the spatiotemporal entity object model, so as to update the space target object data content in the model according to the real-time data of the space target, where SpaceObj is the space target spatiotemporal entity object, [] represents a parameter that can be empty; OID is the unique identifier of the target object, which is used to represent the index of recording associations and behaviors between different objects and between elements within the object; Property represents attribute information; Trajectory represents ephemeris orbit; Attitude represents attitude parameters; EntityModel represents the entity model; Behavior represents the behavior of spatial and temporal entity objects.

8. A space target object modeling system, characterized in that: Contains: model initialization module, data acquisition module and data filling module, among which, A model initialization module, used to determine model construction parameters and a 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, wherein 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; A data acquisition module is used to acquire 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; The data filling module is used to match the target spatiotemporal object data to the corresponding parameters of the initial spatiotemporal object model and perform data filling to obtain the final spatiotemporal object model.

9. An electronic device, characterized in that: include: at least one processor, and a memory coupled to the at least one processor; The memory stores a computer program, and the computer program can be executed by the at least one processor to implement the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed, the method according to any one of claims 1 to 7 can be implemented.

Images