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CN114972666B - A method and device for constructing a holographic navigation scene graph based on ontology modeling - Google Patents

A method and device for constructing a holographic navigation scene graph based on ontology modeling Download PDF

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CN114972666B
CN114972666B CN202210597104.XA CN202210597104A CN114972666B CN 114972666 B CN114972666 B CN 114972666B CN 202210597104 A CN202210597104 A CN 202210597104A CN 114972666 B CN114972666 B CN 114972666B
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CN114972666A (en
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文元桥
程小东
黄亮
黄亚敏
朱曼
周春辉
张帆
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Wuhan University of Technology WUT
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Abstract

The invention provides a holographic navigation scene graph construction method and device based on ontology modeling, and provides a scene semantic model based on ontology, which is used for carrying out structural description on objects in the scene, semantic relations among the objects and behaviors of the objects, so that the function of timely making accurate behavior decisions in the face of a dynamic complex environment is realized. The invention carries out layered modeling on a water traffic scene, which comprises an element layer, an object layer and a scene layer, takes time and place as a description frame of the scene, and independently constructs a body; the efficient organization and expression of the multi-source heterogeneous information in the scene are realized. According to the invention, the water traffic scene is accurately modeled and understood, and after the objects and behaviors are visualized, the holographic navigation scene graph based on the ontology is formed, so that the dynamic expression requirement of the full-element information of the water traffic scene in the space-time dimension is met.

Description

Holographic navigation scene graph construction method and device based on ontology modeling
Technical Field
The invention belongs to the technical field of intelligent navigation, and particularly relates to a holographic navigation scene graph construction method and device based on ontology modeling.
Background
At present, navigation charts such as electronic sea charts only comprise the spatial position states of the entities and the motion characteristics of dynamic entities, and do not comprise descriptions of layering of entity attributes and relevance among a plurality of entities. To obtain this information, the current practice is grid decomposition: firstly, mapping environment perception information into a local raster image, and then obtaining required entity attributes or correlations among entities from the raster image by a progressive search method. In addition, the data of the electronic chart is organized in the form of geographic coordinates, and the spatial objects are simply combined in the form of spatial coordinates, so that the data is difficult to understand by a machine.
Disclosure of Invention
The invention aims to solve the technical problems that: the holographic navigation scene graph construction method and device based on ontology modeling are used for achieving the function of timely making accurate behavior decisions in the face of a dynamic complex environment.
The technical scheme adopted by the invention for solving the technical problems is as follows: a holographic navigation scene graph construction method based on ontology modeling comprises the following steps:
S1: collecting information related to a ship navigation task by adopting a means comprising ubiquitous sensing to form an element layer of a water traffic scene, wherein the element layer comprises navigation environment elements, shore-based scene elements, infrastructure elements and traffic flow elements;
S2: the element layer is used for accommodating all-element information of the scene perceived by various means, and extracting key information in the element layer according to the elements in the step S1 to provide an ontology model Scenario= { Object, behavior, condition }; analyzing knowledge concept layers and relations of traffic objects, behaviors and conditions included in the water traffic scene, and constructing Object classes, behavior classes and conditions;
s3: defining object attributes and data attributes of the classes to form an object layer, and obtaining an ontology concept model;
s4: and instantiating the body model according to the environment priori knowledge, the real-time environment perception information and the ship behavior information, and establishing the relation between the object and the behavior to form a navigation scene, namely a scene layer.
According to the above scheme, in the step S2, the traffic objects include people, ships and environments; behaviors include actions and events; the conditions include weather, hydrology and traffic conditions; in the step S4, the environment priori knowledge is the navigation environment of the topology acquired in advance, including a channel, an anchor ground and a berth; the real-time context awareness information includes weather, hydrologic and traffic conditions detected in real-time.
According to the above scheme, in the step S1, elements included in the water traffic scene in the element layer include time, space, traffic objects, things, events and phenomena; the bottom data for constructing the water traffic scene comprises related information of water traffic objects or events, and comprises structural information, weather hydrologic information, traffic flow state information and ship behavior state information of a navigation environment and associated information among elements.
According to the above scheme, in the step S2, objects are objects, including people, ships, and environments; the person is used for describing the type, the number, the physiological attribute and the psychological attribute of the crews; the ship is used for describing the type, the scale, the size of the number lamp, the motion state, the maneuvering capability and the avoidance roles of the ship; the environment is used to describe navigation environment elements, shore-based scene elements, and infrastructure elements; the environment information is acquired through environment priori knowledge, and the updating frequency is low, and the environment information comprises navigation environment elements, infrastructure elements and shore-based scene elements; the navigation environment elements are channel elements, including shoreline, underwater topography, water depth and shoal; the navigation environment elements are acquired through a sounding system comprising multiple beams and sonar; the infrastructure elements include navigation-aid service facility data and navigation-related facility data; the infrastructure elements are integrated through a database and extracted through electronic channel map data; the shore-based scene elements include offshore oblique photogrammetric traffic and pipeline facility data, landform and vegetation data, and boundary data; the shore-based scene feature is acquired by oblique photogrammetry.
According to the above scheme, in the step S2, behavior is a Behavior, including an action and an event; the actions refer to changes in the speed or heading of the vessel, including acceleration, deceleration, stopping, left-hand turning, right-hand turning, and steering; the event is a higher-level ship semantic behavior, including navigation in a channel, entering a channel, exiting a channel, anchoring, entering an anchor, exiting an anchor, berthing, preparing for berthing, leaving, ship following, ship meeting; the Behavior information updating frequency is high, and the static information, the dynamic information and the environment information of the ship are obtained through topology calculation after equipment including AIS, CCTV and radar senses.
According to the above scheme, in the step S2, conditions are conditions including weather, hydrology and traffic conditions; weather is used to describe the state of wind, flow, visibility, and rainfall; hydrology is used to describe the state of water flow, water level; the traffic condition class is used to describe the state of traffic flow, traffic density and traffic speed; the update frequency of the Condition information is higher than that of the environment information, and a real-time acquisition mode is adopted.
According to the above scheme, in the step S3, in the object layer, object attributes and data attributes of each class are defined according to the class in the element, and the element and the attributes are packaged or the element and the element are combined to form a space-time object of the scene, which is used as a template for real-time extraction of the subsequent object;
The object comprises a space position, a space shape, an attribute characteristic, a composition structure, a behavior capability and an association relation; the space position is described by a semantic position model and comprises a place name, coordinates and landmarks; the space morphology is described by a geometric object model and a hierarchical detail model, wherein the geometric object model comprises points, lines, planes, volumes and composite objects; the attribute features include common attributes and unique attributes; the composition structure comprises a space structure and a hierarchical structure; behavioral capabilities include individual dynamic behaviors and object linkage behaviors; the association relationship comprises a spatial relationship, a time relationship and an attribute relationship; the attribute relationship comprises a correlation relationship and a function relationship;
Object attributes include Decide decided, isUnderConditionOf under certain conditions, restrict restricted, HASRIGHTCHANNEL right lane, HASLEFTCHANNEL left lane, hasFrontChannel front lane, hasBehindChannel back lane, hasLine wired, hasPoint dotted, isApproachTo near, isAwayFrom far away, isConnectedTo connected to a certain connection, isDisconnectedTo disconnected from a certain connection, isOn above a certain connection, isFollowing following;
decide the definition domain is a shipship or a Human, and the value domain is Behavior Behavior;
isUnderConditionOf under a certain Condition, the definition domain is a clip Ship, and the value domain is a Condition;
Restrict the definition domain of the restriction is an Environment, and the value domain is Behavior Behavior;
HASRIGHTCHANNEL the definition domain with the right Channel is a Channel, and the value domain is a Channel;
HASLEFTCHANNEL the definition domain of the left Channel is a Channel, and the value domain is a Channel;
hasFrontChannel the definition domain of the front Channel is a Channel, and the value domain is a Channel;
hasBehindChannel the definition domain of the back Channel is a Channel, and the value domain is a Channel;
the hasLine wired definition domain is a Channel or Berth berth or Anchorage anchor, and the value domain is a Line boundary Line;
hasPoint the dotted definition domain is Channel or Berth berth or Anchorage anchor, the value domain is PointEntity point entity;
isApproachTo is a shipship, the value domain is a Channel or Berth berth or Anchorage anchor or Lock Ship Lock or Bridge or Obstacle obstacle or shipship;
isAwayFrom is a shipship, the value domain is a Channel or Berth berth or Anchorage anchor or Lock Ship Lock or Bridge or Obstacle obstacle or shipship;
isConnectedTo and a certain connection are defined as a Channel or a Berth berth or a Anchorage anchor, and the value domain is a Channel or a Berth berth or a Anchorage anchor;
isDisconnectedTo and a definition domain which is not connected with the map are a Channel or a Berth berth or a Anchorage anchor, and a value domain is a Channel or a Berth berth or a Anchorage anchor;
isOn above a certain definition domain is Obstacle obstacle or Lock or Navigation aids navigation mark, and the value domain is Channel navigation Channel;
isFollowing is followed by a definition field of a Ship, and a value field of the Ship;
The data attributes include Distance, hasBoundaryPosition with boundary position, hasChannelDirection with course direction, HASCHANNELWIDTH with course width, hasDepthOfWater with depth, HASCLEARANCEHEIGHT with slack height, hasFlowDirection with flow direction, hasFlowSpeed with flow rate, hasWindDirection with wind direction, HASWINDSPEED with wind speed, hasVisibilityDistance with visible Distance, HASTRAFFICDENSITY with traffic density, hasTrafficFlow with traffic flow, hasTrafficVelocity with traffic speed, HASSHIPNAME with name, HASSHIPTYPE with vessel type, hasMMSI with mobile identification code, hasHeightAboveWaterline with water line height, HASSHIPDEPTH with vessel height, HASSHIPWIDTH with vessel width, HASSHIPLENGTH with vessel length, hasCourse with heading, hasDraft with draft, HASHEADING with bow direction, hasPosition with position, hasSpeed with speed;
The Distance is defined as the field of the Ship, and the value field is the Float single-precision floating point;
hasBoundaryPosition the definition domain of boundary position is Channel or Berth berth or Anchorage anchor, the value domain is Double precision floating point type;
hasChannelDirection the definition domain with the Channel direction is Channel, and the value domain is Float single-precision floating point;
HASCHANNELWIDTH the definition domain with Channel width is Channel, and the value domain is Float single-precision floating point;
hasDepthOfWater has a definition domain of water depth of Channel or Berth berth or Anchorage anchor, and has a value domain of Float single-precision floating point;
HASCLEARANCEHEIGHT has a definition domain with a rich height as Bridge, and a value domain as Float single-precision floating point;
hasFlowDirection the definition domain with Flow direction is Flow, and the value domain is Flow single-precision floating point type;
hasFlowSpeed has a Flow rate definition domain as Flow, and a value domain as Flow single-precision floating point;
hasWindDirection has Wind direction definition domain as Wind, and value domain as Float single precision floating point;
HASWINDSPEED has a Wind speed definition domain of Wind, and a value domain of Float single-precision floating point;
hasVisibilityDistance the definition domain with visible distance is Visibility, and the value domain is Float single-precision floating point type;
HASTRAFFICDENSITY the definition domain of the traffic density is a Channel, and the value domain is a Float single-precision floating point;
hasTrafficFlow the definition domain of traffic flow is Channel, and the value domain is Float single-precision floating point;
hasTrafficVelocity the definition domain of the traffic speed is a Channel, and the value domain is a Float single-precision floating point;
HASSHIPNAME has the definition domain of Ship name as the Ship, and the value domain as String characters;
HASSHIPTYPE the definition domain of the Ship type is a clip Ship, and the value domain is String characters;
hasMMSI the definition domain with the mobile identification code is a clip Ship, and the value domain is Long integer;
hasHeightAboveWaterline the definition domain of the upper water line height is a clip Ship, and the value domain is a Float single-precision floating point;
HASSHIPDEPTH the definition domain with Ship height is a Ship, and the value domain is a Float single-precision floating point;
HASSHIPWIDTH has a definition domain of Ship width as a Ship, and a value domain as a Float single-precision floating point;
HASSHIPLENGTH has the definition domain of the captain as the shipship, and the value domain as the Float single-precision floating point;
hasCourse has a definition domain of heading as a Ship, and a value domain as a Float single-precision floating point;
hasDraft has draft defined domain as the Ship, and value domain as Float single-precision floating point;
HASHEADING has a definition domain of the bow direction as a clip Ship, and a value domain as a Float single-precision floating point;
hasPosition the definition domain with the position is a Ship, and the value domain is a Float single-precision floating point;
hasSpeed has a speed definition field of a Ship, and a value field of a Float single-precision floating point type.
According to the above scheme, in the step S4, the scene layer is configured to describe the correlation between the object and the object, and between the object and the behavior, and instantiate according to the real-time information of the scene to form the structured expression of the scene; the related relations comprise spatial relations, time relations and semantic relations; the time relationship includes a time point relationship and a time period relationship, described as early, late, intervening, beginning or ending; the spatial relationship comprises a topological relationship, an azimuth relationship and a distance relationship; the semantic relationship is described as a triple structure < master, so-called guest > structure by adopting a resource description framework RDF.
Further, in the step S4, according to the scene elements actually existing in the traffic scene, the scenario knowledge in the assertion fact Abox is re-expressed by using the concept model set in advance in the axiom set Tbox forming the ontology knowledge base, and the ontology model is instantiated; instantiating the ontology model by using the environment priori knowledge, the real-time environment perception information and the ship behavior information to obtain an ontology knowledge base of OWL description; and inputting the real-time information into the ontology model and carrying out multi-scale dynamic expression after visualization so as to meet the change requirement of the full-element information on the time scale.
A holographic navigation scene graph construction device based on ontology modeling comprises a data preprocessing module, an element identification and extraction processing module, an object information packaging module, an object behavior information module, an object and behavior relation calculation module and a visualization module; the data preprocessing module is used for preprocessing the data of the perceived full-element information and providing the instantiated available information for the ontology model; the element identification and extraction processing module is used for extracting scene elements related to the navigation task so as to obtain an entity of the holographic navigation scene graph; the object information packaging module is used for forming space-time objects in the scene by combining the objects contained in the scene and the attributes of the objects or the objects; the object behavior information module is used for acquiring behavior information of the space-time object and processing the space-time object according to the ontology modeling method; the relation calculation module of the object and the behavior is used for calculating the correlation between the object and between the object and the behavior; and the visualization module is used for storing the navigation scene constructed by the body into the graph database and carrying out visual expression.
The beneficial effects of the invention are as follows:
1. According to the method and the device for constructing the holographic navigation scene graph based on the ontology modeling, which are disclosed by the invention, aiming at the problems that the water traffic scene modeling method is insufficient in expression and machine understanding of the scene can not be realized, the scene semantic model based on the ontology is provided, the semantic relation among objects in the scene and the behaviors of the objects are structurally described, and the function of timely making accurate behavior decisions in the face of a dynamic complex environment is realized.
2. The invention carries out layered modeling on the water traffic scene: at the element layer, mainly defining the class of the full element information in the scene; extracting elements related to tasks in navigation scenes and related attributes thereof in an object layer; at a scene layer, constructing a relation between an object and an object behavior; taking the time and the place as a description framework of the scene, and independently constructing an ontology; the efficient organization and expression of the multi-source heterogeneous information in the scene are realized.
3. The invention accurately models and understands the water traffic scene; after the objects and the behaviors are visualized, a holographic navigation scene graph based on an ontology is formed; the dynamic expression requirement of the full-element information of the water traffic scene on the space-time dimension is met.
Drawings
FIG. 1 is a flow chart of an embodiment of the present invention.
FIG. 2 is a descriptive model diagram of a water traffic object in accordance with an embodiment of the present invention.
FIG. 3 is a class diagram in a water traffic scenario in accordance with an embodiment of the present invention.
Fig. 4 is a functional block diagram of an embodiment of the present invention.
Detailed Description
The invention will be described in further detail with reference to the drawings and the detailed description.
Referring to fig. 4, an embodiment of the present invention includes a data preprocessing module, an element recognition extraction processing module, an object information encapsulation module, an object behavior information module, and a relationship calculation module and a visualization module of an object and a behavior;
The data preprocessing module is used for preprocessing the data of the perceived full-element information and providing the instantiated available information for the ontology model;
the element identification and extraction processing module is used for extracting scene elements related to the navigation task so as to obtain an entity of the holographic navigation scene graph;
The object information packaging module is used for forming space-time objects in the scene by combining the objects contained in the scene and the attributes of the objects or the objects;
The object behavior information module is used for acquiring behavior information of the space-time object and processing the space-time object according to the ontology modeling method;
The relation calculation module of the object and the behavior is used for calculating the correlation between the object and between the object and the behavior;
and the visualization module is used for storing the navigation scene constructed by the body into the graph database and carrying out visual expression.
Referring to fig. 1, the method for constructing the holographic navigation scene graph based on ontology modeling comprises the following steps:
s1: collecting information related to a ship navigation task through means such as ubiquitous sensing and the like to form an element layer comprising navigation environment elements, shore-based scene elements, infrastructure elements, traffic flow elements and the like;
S2: according to the scene elements in the step S1, extracting key information in an element layer, analyzing knowledge concept layers and relations of traffic objects (people, ships, environments), behaviors (actions, events), conditions (weather, hydrology, traffic conditions) and the like in a traffic scene, and constructing Object classes, behavior classes and Environment classes;
s3: defining object attributes and data attributes corresponding to the classes to obtain an ontology concept model;
S4: the body model is instantiated by using environment priori knowledge (topological navigation environment: navigation channel, anchor ground, berth and the like can be acquired in advance), real-time environment perception information (weather, hydrology and traffic conditions, and the environment perception system is required to detect in real time and serve as temporary knowledge storage) and ship behavior information, and the relationship between objects and behaviors is established to form a navigation scene.
The key of intelligent navigation is that the intelligent navigation faces a dynamic complex environment, accurate behavior decisions can be made in time, and the precondition and the basis of the behavior decisions are that the intelligent ship can accurately model and understand the water traffic scene. Because research on understanding of the water traffic scene is relatively lacking at present, standardized definition of the water navigation scene is not available, the water traffic scene is divided into three layers by the patent, and the layer construction steps refer to fig. 1.
1. In the element layer, elements such as time, space, traffic objects, things, events and phenomena are included in the water traffic scene, and the bottom data sources for constructing the water traffic scene are water traffic objects or event related information (such as positions, states and environments) and include structural information, weather hydrologic information, traffic flow state information, ship behavior state information and related information among elements of a navigation environment (such as a navigation channel). Therefore, the element layer mainly accommodates the full-element information of the scene perceived by various means, and the proposed ontology model classifies the classes in the scene into: scenario= { Object, behavior, condition }, see fig. 3.
Object class is an Object, including people, boats, environment. People mainly describe the type, quantity, physiological attributes and psychological attributes of crews; the ship is mainly used for describing the type, the scale, the number type, the motion state, the maneuvering capability, the avoidance roles and the like of the ship; the environment is mainly used for describing navigation environment elements, shore-based scene elements and infrastructure elements, such as channels, anchors, berths, bridges and the like, the update frequency of the environment information is low, and the environment information is acquired by using the priori knowledge of the environment, as shown in table 1.
TABLE 1 classification and connotation of environmental class elements
Behavior is a Behavior, including actions, events. The actions refer to the change of the speed or the course of the ship, such as acceleration, deceleration, stay, left turn, right turn, direction keeping and the like; the event is a higher level of semantic behavior of the ship, including sailing in the channel, entering the channel, exiting the channel, anchoring, entering the anchor, exiting the anchor, leaning in, preparing to lean in, leaving, following the ship, meeting the ship, and the like. The information updating frequency is relatively high, and the information is acquired by performing topology calculation on ship static and dynamic information and environment information perceived by equipment such as AIS, CCTV, radar and the like.
Condition type conditions including weather, hydrology, traffic conditions, etc. Weather mainly describes the states of wind, flow, visibility, rainfall, etc.; hydrology is used to describe the state of water flow, water level, etc.; traffic conditions are used to describe the state of traffic flow, traffic density, traffic speed. Compared with the navigation environment of the topology, the information has higher updating frequency and needs to be acquired in real time.
2. At the object layer, according to the classes in the elements, the data attribute and the object attribute of each class are respectively defined, the elements and the attributes are packaged or combined to form the space-time object of the scene, and the space-time object is used as a template for extracting the subsequent object in real time. A description model of the object is shown in fig. 2.
Wherein the object properties (also referred to as relationship properties) and the data properties are shown in tables 2 and 3.
TABLE 2 object Properties in Water traffic scene
TABLE 3 data Properties in Water traffic scenarios
3. At a scene layer, the relation problem among objects and behaviors is mainly solved, and then the structural expression of the scene is formed after instantiation is carried out according to the real-time information of the scene.
The correlation relationship mainly comprises a spatial relationship, a time relationship and a semantic relationship. The spatial relationship comprises a topological relationship, an azimuth relationship and a distance relationship; the time point relationship, time period relationship may be described as early, late, intervening, beginning, ending. The semantic relationships are relatively complex, and can be described as a triple structure < master, slave, guest > structure, e.g., a event triggers B behavior, C event causes D event, using a resource description framework (Resource description framework, RDF).
Instantiating a portion. The foregoing describes the modeling process of knowledge such as objects and behaviors related to the water traffic scene, which is equivalent to filling the Tbox forming the ontology knowledge base with background knowledge, but the scene knowledge in Abox still lacks, and the concept model set in advance in Tbox is used for re-expression according to the scene elements actually existing in the traffic scene, namely, the instantiation of the ontology model.
The instantiation process of the onto-model has two aspects: firstly, the prior information of the traffic scene is instantiated, and secondly, the real-time perception information of the environment is instantiated. The ontology model is instantiated by using environment priori knowledge (such as navigation environment: navigation channel, anchor ground, berth and the like, which can be acquired in advance), real-time environment perception information (weather, hydrology and traffic conditions, which need real-time detection of an environment perception system and serve as temporary knowledge storage) and ship behavior information, so as to obtain an ontology knowledge base of OWL description. The real-time information is input into the ontology model and visualized, then the multi-scale dynamic expression can be carried out, and the change requirement of the full-element information on the time scale is met.
The above embodiments are merely for illustrating the design concept and features of the present invention, and are intended to enable those skilled in the art to understand the content of the present invention and implement the same, the scope of the present invention is not limited to the above embodiments. Therefore, all equivalent changes or modifications according to the principles and design ideas of the present invention are within the scope of the present invention.

Claims (10)

1.一种基于本体建模的全息航行场景图构建方法，其特征在于：包括以下步骤：1. A method for constructing a holographic navigation scene graph based on ontology modeling, characterized in that it comprises the following steps: S1：采用包括泛在感知的手段收集与船舶航行任务相关的信息，形成水上交通场景的包括通航环境要素、岸基场景要素、基础设施要素和交通流要素的要素层；S1: Use ubiquitous sensing to collect information related to ship navigation tasks, and form an element layer of water traffic scenes including navigation environment elements, shore-based scene elements, infrastructure elements and traffic flow elements; S2：要素层用于容纳通过各种手段感知的场景全要素信息，根据步骤S1所述的要素抽取要素层中的关键信息，提出本体模型Scenario＝{Object、Behavior、Condition}；分析水上交通场景中包括的交通对象、行为、条件的知识概念层次和关系，构建Object类、Behavior类和Condition类；S2: The element layer is used to contain the full element information of the scene perceived by various means. According to the elements described in step S1, the key information in the element layer is extracted, and the ontology model Scenario = {Object, Behavior, Condition} is proposed; the knowledge concept hierarchy and relationship of the traffic objects, behaviors, and conditions included in the water traffic scene are analyzed, and the Object class, Behavior class, and Condition class are constructed; S3：定义类的对象属性和数据属性形成对象层，得到本体概念模型；S3: Define the object attributes and data attributes of the class to form the object layer and obtain the ontology conceptual model; S4：根据环境先验知识、实时环境感知信息和船舶行为信息对本体模型进行实例化，建立对象与行为的关系，形成航行场景即场景层。S4: Instantiate the ontology model based on environmental prior knowledge, real-time environmental perception information and ship behavior information, establish the relationship between objects and behaviors, and form a navigation scenario, namely the scenario layer. 2.根据权利要求1所述的一种基于本体建模的全息航行场景图构建方法，其特征在于：2. According to the ontology modeling-based holographic navigation scene graph construction method of claim 1, it is characterized by: 所述的步骤S2中，交通对象包括人、船和环境；行为包括动作和事件；条件包括气象、水文、交通条件；In step S2, traffic objects include people, ships and environment; behaviors include actions and events; conditions include meteorological, hydrological and traffic conditions; 所述的步骤S4中，环境先验知识为事先获取的拓扑的通航环境，包括航道、锚地和泊位；实时环境感知信息包括实时检测的气象、水文和交通条件。In step S4, the environmental prior knowledge is the topological navigation environment acquired in advance, including waterways, anchorages and berths; the real-time environmental perception information includes the real-time detected meteorological, hydrological and traffic conditions. 3.根据权利要求1所述的一种基于本体建模的全息航行场景图构建方法，其特征在于：所述的步骤S1中，要素层中的水上交通场景包括的元素有时间、空间、交通对象、事物、事件和现象；构建水上交通场景的底层数据包括水上交通对象或事件的相关信息，涵盖通航环境的结构信息、气象水文信息、交通流状态信息和船舶行为状态信息，以及各要素间的关联信息。3. According to the method for constructing a holographic navigation scene graph based on ontology modeling as described in claim 1, it is characterized in that: in the step S1, the elements of the water traffic scene in the element layer include time, space, traffic objects, things, events and phenomena; the underlying data for constructing the water traffic scene includes relevant information of water traffic objects or events, covering the structural information of the navigation environment, meteorological and hydrological information, traffic flow status information and ship behavior status information, as well as the correlation information between the elements. 4.根据权利要求1所述的一种基于本体建模的全息航行场景图构建方法，其特征在于：所述的步骤S2中，Object类为对象，包括人、船、环境；4. The method for constructing a holographic navigation scene graph based on ontology modeling according to claim 1 is characterized in that: in the step S2, the Object class is an object, including a person, a ship, and an environment; 人用于描述船员类型、数量、生理属性、心理属性；船用于描述船舶类型、尺度、号灯号型、运动状态、操纵能力和避让角色；环境用于描述通航环境要素、岸基场景要素和基础设施要素；环境信息通过环境先验知识获取，更新频率低，包括通航环境要素、基础设施要素和岸基场景要素；People are used to describe the type, number, physiological attributes, and psychological attributes of crew members; ships are used to describe the type, size, signal light type, motion state, maneuverability, and avoidance role of ships; environments are used to describe navigation environment elements, shore-based scene elements, and infrastructure elements; environmental information is obtained through environmental prior knowledge and has a low update frequency, including navigation environment elements, infrastructure elements, and shore-based scene elements; 通航环境要素的为航道要素，包括岸线、水下地形、水深和浅滩；通航环境要素通过包括多波束和声纳的测深系统获取；Navigable environment elements are channel elements, including coastline, underwater topography, water depth and shoals; Navigable environment elements are obtained through bathymetric systems including multi-beam and sonar; 基础设施要素包括助导航服务设施数据和与通航有关的设施数据；基础设施要素通过数据库集成和电子航道图数据提取；Infrastructure elements include data on aids to navigation services and facilities related to navigation; infrastructure elements are extracted through database integration and electronic navigation chart data; 岸基场景要素包括近岸倾斜摄影测量交通与管线设施数据、地貌与植被数据、境界数据；岸基场景要素通过倾斜摄影测量获取。Shore-based scene elements include nearshore oblique photogrammetry traffic and pipeline facility data, landform and vegetation data, and boundary data; shore-based scene elements are obtained through oblique photogrammetry. 5.根据权利要求1所述的一种基于本体建模的全息航行场景图构建方法，其特征在于：所述的步骤S2中，Behavior类为行为，包括动作、事件；5. According to the method for constructing a holographic navigation scene graph based on ontology modeling in claim 1, it is characterized in that: in the step S2, the Behavior class is a behavior, including actions and events; 动作是指船舶速度或航向的改变，包括加速、减速、停留、左转、右转和保向；事件是更高级别的船舶语义行为，包括有航道内航行、进入航道、驶出航道、锚泊、进入锚地、驶出锚地、靠泊中、准备靠泊、离泊以及船舶跟随、船舶会遇；Behavior类信息更新频率快，通过包括AIS、CCTV、雷达的设备感知后船舶的静态信息、动态信息和环境信息进行拓扑计算获取。Action refers to the change of ship speed or course, including acceleration, deceleration, stop, left turn, right turn and direction keeping; event is a higher-level semantic behavior of the ship, including navigation in the channel, entering the channel, leaving the channel, anchoring, entering the anchorage, leaving the anchorage, berthing, preparing for berthing, leaving the anchorage, as well as ship following and ship encountering; Behavior information is updated frequently, and the static information, dynamic information and environmental information of the ship are perceived by equipment including AIS, CCTV and radar, and then obtained through topological calculation. 6.根据权利要求1所述的一种基于本体建模的全息航行场景图构建方法，其特征在于：所述的步骤S2中，Condition类为条件，包括气象、水文和交通条件；6. The method for constructing a holographic navigation scene graph based on ontology modeling according to claim 1, characterized in that: in the step S2, the Condition class is a condition, including meteorological, hydrological and traffic conditions; 气象用于描述风、流、能见度、降雨量的状态；Meteorology is used to describe the state of wind, current, visibility, and rainfall; 水文用于描述水流、水位的状态；Hydrology is used to describe the state of water flow and water level; 交通条件类用于描述交通流量、交通密度和交通速度的状态；Traffic condition class is used to describe the status of traffic flow, traffic density and traffic speed; Condition类信息的更新频率相对于环境信息更高，采用实时获取的方式。The update frequency of Condition information is higher than that of environmental information, and it is acquired in real time. 7.根据权利要求1所述的一种基于本体建模的全息航行场景图构建方法，其特征在于：所述的步骤S3中，在对象层，根据要素中的类分别定义各个类的对象属性和数据属性，将要素与属性封装或要素与要素组合形成场景的时空对象，作为后续对象实时提取的模板；7. According to the ontology modeling-based holographic navigation scene graph construction method of claim 1, it is characterized in that: in the step S3, at the object layer, the object attributes and data attributes of each class are defined according to the class in the element, and the elements and attributes are encapsulated or the elements and elements are combined to form the spatiotemporal object of the scene, which serves as a template for subsequent real-time extraction of objects; 对象包括空间位置、空间形态、属性特征、组成结构、行为能力、关联关系；空间位置通过语义位置模型描述，包括地名、坐标和地标；空间形态通过几何对象模型和层次细节模型描述，几何对象模型包括点、线、面、体和复合对象；属性特征包括共有属性和特有属性；组成结构包括空间结构和层次结构；行为能力包括个体动态行为和对象联动行为；关联关系包括空间关系、时间关系和属性关系；属性关系包括相关关系和函数关系；Objects include spatial position, spatial form, attribute characteristics, composition structure, behavioral ability, and association relationship; spatial position is described by semantic position model, including place name, coordinates and landmark; spatial form is described by geometric object model and hierarchical detail model, and geometric object model includes point, line, surface, body and composite object; attribute characteristics include common attributes and unique attributes; composition structure includes spatial structure and hierarchical structure; behavioral ability includes individual dynamic behavior and object linkage behavior; association relationship includes spatial relationship, time relationship and attribute relationship; attribute relationship includes correlation relationship and function relationship; 对象属性包括Decide决定、isUnderConditionOf在某条件下、Restrict限制、hasRightChannel有右航道、hasLeftChannel有左航道、hasFrontChannel有前航道、hasBehindChannel有后航道、hasLine有线、hasPoint有点、isApproachTo接近、isAwayFrom远离、isConnectedTo与某连接、isDisconnectedTo与某不连接、isOn在某之上、isFollowing跟随；The object attributes include Decide, isUnderConditionOf, Restrict, hasRightChannel, hasLeftChannel, hasFrontChannel, hasBehindChannel, hasLine, hasPoint, isApproachTo, isAwayFrom, isConnectedTo, isDisconnectedTo, isOn, isFollowing; Decide决定的定义域为Ship船或Human人，值域为Behavior行为；The domain of Decide is Ship or Human, and the range is Behavior; isUnderConditionOf在某条件下的定义域为Ship船，值域为Condition条件；The domain of isUnderConditionOf under a condition is Ship, and the range is Condition; Restrict限制的定义域为Environment环境，值域为Behavior行为；The domain of Restrict is Environment, and the range is Behavior. hasRightChannel有右航道的定义域为Channel航道，值域为Channel航道；hasRightChannel hasRightChannel, the domain is Channel, and the range is Channel; hasLeftChannel有左航道的定义域为Channel航道，值域为Channel航道；hasLeftChannel has a left channel, the domain is Channel, and the range is Channel; hasFrontChannel有前航道的定义域为Channel航道，值域为Channel航道；hasFrontChannel hasFrontChannel, the domain is Channel, and the range is Channel; hasBehindChannel有后航道的定义域为Channel航道，值域为Channel航道；hasBehindChannel has a behind channel, the domain is Channel, and the range is Channel; hasLine有线的定义域为Channel航道或Berth泊位或Anchorage锚地，值域为Line边界线；The definition domain of hasLine is Channel or Berth or Anchorage, and the value range is Line boundary line; hasPoint有点的定义域为Channel航道或Berth泊位或Anchorage锚地，值域为PointEntity点实体；The definition domain of hasPoint is Channel or Berth or Anchorage, and the value range is PointEntity. isApproachTo接近的定义域为Ship船，值域为Channel航道或Berth泊位或Anchorage锚地或Lock船闸或Bridge桥梁或Obstacle障碍物或Ship船；The domain of isApproachTo is Ship, and the range is Channel or Berth or Anchorage or Lock or Bridge or Obstacle or Ship; isAwayFrom远离的定义域为Ship船，值域为Channel航道或Berth泊位或Anchorage锚地或Lock船闸或Bridge桥梁或Obstacle障碍物或Ship船；The domain of isAwayFrom isShip, and the range isChannel or Berth or Anchorage or Lock or Bridge or Obstacle or Ship; isConnectedTo与某连接的定义域为Channel航道或Berth泊位或Anchorage锚地，值域为Channel航道或Berth泊位或Anchorage锚地；The domain of isConnectedTo and a connection is Channel or Berth or Anchorage, and the range is Channel or Berth or Anchorage; isDisconnectedTo与某不连接的定义域为Channel航道或Berth泊位或Anchorage锚地，值域为Channel航道或Berth泊位或Anchorage锚地；isDisconnectedTo has a domain of Channel or Berth or Anchorage and a range of Channel or Berth or Anchorage. isOn在某之上的定义域为Obstacle障碍物或Lock船闸或Navigation aids航标，值域为Channel航道；The domain of isOn is Obstacle, Lock or Navigation Aids, and the range is Channel. isFollowing跟随的定义域为Ship船，值域为Ship船；The domain of isFollowing is Ship, and the range is Ship; 数据属性包括Distance距离、hasBoundaryPosition有边界位置、hasChannelDirection有航道方向、hasChannelWidth有航道宽度、hasDepthOfWater有水深、hasClearanceHeight有富裕高度、hasFlowDirection有流向、hasFlowSpeed有流速、hasWindDirection有风向、hasWindSpeed有风速、hasVisibilityDistance有能见距离、hasTrafficDensity有交通密度、hasTrafficFlow有交通流量、hasTrafficVelocity有交通速度、hasShipName有船名、hasShipType有船舶类型、hasMMSI有移动识别码、hasHeightAboveWaterline有水线上高度、hasShipDepth有船高、hasShipWidth有船宽、hasShipLength有船长、hasCourse有航向、hasDraft有吃水、hasHeading有船首向、hasPosition有位置、hasSpeed有速度；The data attributes include Distance, hasBoundaryPosition, hasChannelDirection, hasChannelWidth, hasDepthOfWater, hasClearanceHeight, hasFlowDirection, hasFlowSpeed, hasWindDirection, hasWindSpeed, hasVisibilityDistance, hasTrafficDensity, hasTrafficFlow, hasTrafficVelocity, hasShipName, hasShipType, hasMMSI, hasHeightAboveWaterline, hasShipDepth, hasShipWidth, hasShipLength, hasCourse, hasDraft, hasHeading, hasPosition, hasSpeed; Distance距离的定义域为Ship船，值域为Float单精度浮点型；The domain of Distance is Ship, and the value range is Float single-precision floating point type; hasBoundaryPosition有边界位置的定义域为Channel航道或Berth泊位或Anchorage锚地，值域为Double双精度浮点型；The domain of hasBoundaryPosition is Channel, Berth or Anchorage, and the value range is Double. hasChannelDirection有航道方向的定义域为Channel航道，值域为Float单精度浮点型；hasChannelDirection has a channel direction whose domain is Channel and whose value range is Float single-precision floating point type; hasChannelWidth有航道宽度的定义域为Channel航道，值域为Float单精度浮点型；hasChannelWidth has the channel width with a domain of Channel and a value range of Float single-precision floating point type; hasDepthOfWater有水深的定义域为Channel航道或Berth泊位或Anchorage锚地，值域为Float单精度浮点型；The definition domain of hasDepthOfWater is Channel or Berth or Anchorage, and the value range is Float single-precision floating point type; hasClearanceHeight有富裕高度的定义域为Bridge桥梁，值域为Float单精度浮点型；hasClearanceHeight has a domain of Bridge and a value of Float. hasFlowDirection有流向的定义域为Flow流，值域为Float单精度浮点型；hasFlowDirection has a flow direction, and its domain is Flow, and its value range is Float single-precision floating point type; hasFlowSpeed有流速的定义域为Flow流，值域为Float单精度浮点型；hasFlowSpeed has a flow speed whose domain is Flow and whose value range is Float single-precision floating point type; hasWindDirection有风向的定义域为Wind风，值域为Float单精度浮点型；hasWindDirection has the wind direction with the domain of Wind and the value range of Float single-precision floating point type; hasWindSpeed有风速的定义域为Wind风，值域为Float单精度浮点型；hasWindSpeed has the wind speed whose domain is Wind and whose value range is Float single-precision floating point type; hasVisibilityDistance有能见距离的定义域为Visibility能见度，值域为Float单精度浮点型；hasVisibilityDistance has visibility distance with a domain of Visibility and a value range of Float single-precision floating point type; hasTrafficDensity有交通密度的定义域为Channel航道，值域为Float单精度浮点型；hasTrafficDensity has a traffic density whose domain is Channel and whose value range is Float single-precision floating point type; hasTrafficFlow有交通流量的定义域为Channel航道，值域为Float单精度浮点型；hasTrafficFlow has a traffic flow whose domain is Channel and whose value range is Float single-precision floating point type; hasTrafficVelocity有交通速度的定义域为Channel航道，值域为Float单精度浮点型；hasTrafficVelocity has the traffic velocity whose domain is Channel and whose value range is Float single-precision floating point type; hasShipName有船名的定义域为Ship船，值域为String字符型；hasShipName has a ship name, the domain is Ship, and the value range is String character type; hasShipType有船舶类型的定义域为Ship船，值域为String字符型；hasMMSI有移动识别码的定义域为Ship船，值域为Long长整型；hasShipType has the domain of ship type as Ship and the value domain as String; hasMMSI has the domain of mobile identification code as Ship and the value domain as Long; hasHeightAboveWaterline有水线上高度的定义域为Ship船，值域为Float单精度浮点型；hasHeightAboveWaterline has the height above the waterline, the domain is Ship, and the value range is Float single-precision floating point type; hasShipDepth有船高的定义域为Ship船，值域为Float单精度浮点型；hasShipDepth has a ship height whose domain is Ship and whose value range is Float single-precision floating point type; hasShipWidth有船宽的定义域为Ship船，值域为Float单精度浮点型；hasShipWidth has the definition domain of Ship width as Ship, and the value range is Float single-precision floating point type; hasShipLength有船长的定义域为Ship船，值域为Float单精度浮点型；hasShipLength has the definition domain of Ship as the length of the ship, and the value range is Float single-precision floating point type; hasCourse有航向的定义域为Ship船，值域为Float单精度浮点型；hasCourse has a heading whose domain is Ship and whose value range is Float single-precision floating point type; hasDraft有吃水的定义域为Ship船，值域为Float单精度浮点型；hasDraft has a draft whose domain is Ship and whose value range is Float single-precision floating point type; hasHeading有船首向的定义域为Ship船，值域为Float单精度浮点型；hasHeading has a heading direction, the domain is Ship, and the value range is Float single-precision floating point type; hasPosition有位置的定义域为Ship船，值域为Float单精度浮点型；The domain of hasPosition is Ship, and the value range is Float single-precision floating point type; hasSpeed有速度的定义域为Ship船，值域为Float单精度浮点型。The domain of hasSpeed is Ship, and the value range is Float single-precision floating point type. 8.根据权利要求1所述的一种基于本体建模的全息航行场景图构建方法，其特征在于：所述的步骤S4中，场景层用于描述对象与对象、对象与行为间的相关关系，并根据场景的实时信息进行实例化，构成场景的结构化表达；8. The method for constructing a holographic navigation scene graph based on ontology modeling according to claim 1 is characterized in that: in the step S4, the scene layer is used to describe the correlation between objects and objects, and between objects and behaviors, and is instantiated according to the real-time information of the scene to form a structured expression of the scene; 相关关系包括空间关系、时间关系和语义关系；Related relations include spatial relations, temporal relations and semantic relations; 时间关系包括时间点关系和时间段关系，描述为早于、晚于、介于、开始于或结束于；Temporal relations include time point relations and time period relations, which are described as earlier than, later than, between, starting at, or ending at; 空间关系包括拓扑关系、方位关系和距离关系；Spatial relations include topological relations, orientation relations, and distance relations; 语义关系采用资源描述框架RDF描述为三元组结构<主，谓，宾>的结构。The semantic relationship is described by using the Resource Description Framework (RDF) as a triple structure of <subject, predicate, object>. 9.根据权利要求8所述的一种基于本体建模的全息航行场景图构建方法，其特征在于：所述的步骤S4中，根据交通场景中真实存在的场景元素，使用组成本体知识库的公理集Tbox中事先设定的概念模型重新表达断言事实Abox中的情景知识，将本体模型的实例化；利用环境先验知识、实时环境感知信息和船舶行为信息对本体模型进行实例化，得到OWL描述的本体知识库；将实时信息输入到本体模型中并可视化后进行多尺度动态表达，满足全要素信息在时间尺度上的变化需求。9. According to the method for constructing a holographic navigation scene graph based on ontology modeling in claim 8, it is characterized in that: in the step S4, according to the scene elements that actually exist in the traffic scene, the situational knowledge in the asserted fact Abox is re-expressed using the conceptual model pre-set in the axiom set Tbox that constitutes the ontology knowledge base, and the ontology model is instantiated; the ontology model is instantiated using environmental prior knowledge, real-time environmental perception information and ship behavior information to obtain an ontology knowledge base described by OWL; real-time information is input into the ontology model and visualized for multi-scale dynamic expression to meet the change requirements of all-factor information on a time scale. 10.一种用于权利要求1至9中任意一项所述的基于本体建模的全息航行场景图构建方法的装置，其特征在于：包括数据预处理模块、要素识别抽取处理模块、对象信息封装模块、对象行为信息模块和对象与行为的关系计算模块和可视化模块；10. A device for the method of constructing a holographic navigation scene graph based on ontology modeling according to any one of claims 1 to 9, characterized in that it comprises a data preprocessing module, an element recognition and extraction processing module, an object information encapsulation module, an object behavior information module, and an object-behavior relationship calculation module and a visualization module; 数据预处理模块用于对感知的全要素信息进行数据预处理，为本体模型提供实例化的可用信息；The data preprocessing module is used to preprocess the perceived full-factor information and provide instantiated usable information for the ontology model; 要素识别抽取处理模块用于对与航行任务相关的场景要素进行抽取，以此得到全息航行场景图的实体；The element recognition and extraction processing module is used to extract scene elements related to the navigation task, so as to obtain the entity of the holographic navigation scene map; 对象信息封装模块用于场景中包含的对象及其属性或者对象与对象进行组合，形成场景中的时空对象；The object information encapsulation module is used to combine objects and their attributes contained in the scene or objects with each other to form spatiotemporal objects in the scene; 对象行为信息模块用于获取时空对象的行为信息并依照前述本体建模方法进行处理；The object behavior information module is used to obtain the behavior information of spatiotemporal objects and process it according to the aforementioned ontology modeling method; 对象与行为的关系计算模块用于计算对象与对象、对象与行为间的相关关系；可视化模块用于将本体构建的航行场景存至图数据库并进行可视化表达。The object-behavior relationship calculation module is used to calculate the correlation between objects and objects, and between objects and behaviors; the visualization module is used to store the navigation scene constructed by the ontology into the graph database and perform visual expression.
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