A method and system for representing perception resources supporting dynamic collaborative management and control

Abstract

The present invention provides a method for characterizing perceptual resources that supports dynamic collaborative management and control, which relates to the field of information services and solves the problem of inaccurate resource configuration. The method includes: obtaining perceptual resources to be characterized; extracting multiple types of characterization elements from perceptual resources based on application layer information requirements; using a presentation layer state transformation service architecture to abstractly describe multiple types of characterization elements, including: specifying a unique uniform resource identifier for each of the multiple types of characterization elements; performing multiple preset types of operations on each characterization element based on the uniform resource identifier; using a network ontology language to semantically describe each characterization element; and normalizing and encapsulating each characterization element after the abstract description to complete the characterization of perceptual resources. The method facilitates task-oriented perceptual resource matching; reduces the coupling between perceptual resources and functions, and improves the flexible assembly capabilities of perceptual resources based on service requirements.

Description

Technical Field

[0001] The present invention relates to the field of information services, and in particular to a method and system for representing perception resources that supports dynamic collaborative management and control. Background Art

[0002] As the earth's environment changes, people's needs for earth observation are becoming increasingly complex, and perception equipment, as the source of geospatial data acquisition, has developed rapidly. However, perception resources are diverse in type, observation mechanisms are different, and the number is huge. They are independently built and operated by various departments, forming separate closed-loop control within the system, forming a "demand proposal-task control-sensing detection-data reception-data processing-product production" This kind of contingency-based solidified perception workflow belongs to the "chimney" architecture. This "chimney" architecture and usage mode of perception resources makes it impossible to build an integrated perception detection network with dynamic combination and elastic expansion, the utilization rate of perception resources is low, and the resource aggregation efficiency cannot be fully utilized.

[0003] In recent years, with the increasing demand for joint perception, certain breakthroughs have been made in the joint use of multiple perception methods, including the coordinated design of standards such as network interfaces, transmission protocols, message formats, and product data for various perception resources and information systems at all levels under unified planning by various users. However, in actual applications, the original separate closed-loop circuits and fixed workflows of each perception system have not been broken. Most of the joint perception methods remain at the information synthesis and system integration of the output results of each perception equipment, lacking the fusion verification and mutual guidance of the signal level, data level, and feature level, and cannot achieve soft integration at the element level.

[0004] The fundamental reason for the lack of element-level joint perception is the lack of a shareable perception resource description model and a scientific association method. When faced with specific events, the configuration of sensor resources is inaccurate, incomplete, and untimely, which directly leads to inefficient sensor planning and scheduling during emergency response.

[0005] Therefore, how to integrate geographically dispersed and logically independent physical resources into a logically centralized virtual resource set through virtualization requires solving key problems such as physical resource modeling and control interface service encapsulation. Summary of the invention

[0006] 1. Technical issues to be resolved

[0007] In view of the above shortcomings, the main purpose of the present invention is to provide a method for representing perception resources that supports dynamic collaborative management and control. This method extracts multi-granularity perception resource abstract representation elements based on application layer information requirements, and adds information describing the guidance capabilities, collaborative capabilities, usage constraints, and scheduling control of perception resources from an application perspective, so as to facilitate task-oriented perception resource matching. In addition, this method uses a RESTful (presentation layer state transfer) service architecture to describe virtual perception resources, and implements resource operations based on HTTP (communication protocol) operations, providing the meaning of perception resources and the correct way to use them for perception resource applications, ensuring support for resource applications based on semantic information consistency.

[0008] (II) Technical solution

[0009] In order to achieve the above-mentioned objectives, the first aspect of the present invention provides a method for characterizing perception resources that supports dynamic collaborative management and control, including: obtaining the perception resources to be characterized; extracting multiple types of characterization elements from the perception resources based on application layer information requirements; using a presentation layer state transformation service architecture to abstractly describe the multiple types of characterization elements, including: specifying a unique uniform resource identifier for each of the multiple types of characterization elements; based on the uniform resource identifier, performing multiple preset types of operations on each characterization element; using a network ontology language to semantically describe each characterization element; and normalizing and encapsulating each characterization element after the abstract description to complete the characterization of the perception resources.

[0010] In the above scheme, based on the application layer information requirements, multiple types of representation elements are extracted from the perception resources, including: abstracting the perception resources to be represented into objects; based on the application layer information requirements, multiple types of representation elements of the objects are obtained through multi-granularity calculations.

[0011] In the above scheme, multiple types of characterization elements include: sensing characteristics, mobility, guidance parameters and collaborative capabilities, among which: sensing characteristics describe the characteristics of sensors, including shape feature detection, radiation feature detection, scattering feature detection, voiceprint feature detection, intention feature detection, group feature detection and motion parameter detection; mobility describes the mobility of various types of perception resources, including initial position, orbital parameters, activity speed, activity radius, duration and detection angle range; guidance parameters describe the guidance capabilities of various types of perception resources, including point information guidance, area information guidance, radar fingerprint guidance, frequency band information guidance, electronic fingerprint guidance and intention information guidance; collaborative capabilities describe the collaborative capabilities of various types of perception resources, including collaborative modes, networking requirements, collaborative objects, collaborative links and collaborative constraints.

[0012] In the above scheme, multiple types of characterization elements include: information processing, data transmission, additional constraints and scheduling control, among which: information processing describes the information processing capabilities of various types of perception resources, including product type, product level, failure requirements, processing mode and number of processing nodes; data transmission describes the characteristics of various types of perception resources in data transmission, including transmission mode, transmission bandwidth, transmission delay and transmission link; additional constraints describe the limiting conditions that various types of perception resources need to meet during use, including electromagnetic environment constraints, lighting condition constraints, meteorological condition constraints and sea conditions; scheduling control describes the characteristics of scheduling control of various types of perception resources, including control frequency band, control range, power-on time, power-off time, interval time and working mode.

[0013] In the above scheme, multiple preset types of operations include acquisition, creation, modification and deletion, among which: the acquisition operation includes accessing the representation element of the uniform resource identifier based on the communication protocol; the creation operation includes creating a target representation element according to the uniform resource identifier based on the communication protocol, and re-specifying the corresponding uniform resource identifier for the target representation element; the modification operation includes updating the status of the representation element according to the uniform resource identifier based on the communication protocol; the deletion operation includes deleting the representation element corresponding to the uniform resource identifier based on the communication protocol.

[0014] In the above scheme, the network ontology language is used to semantically describe each representation element, including: matching the corresponding service configuration file and executing the service according to the results of multiple preset types of operations on each representation element; using the dynamic description logic method to uniformly semantically describe the service input, output, operation premise and results after the operation.

[0015] In the above scheme, each representation element after the abstract description is expressed and encapsulated in a standardized manner, including: determining the service access form of the representation element after the abstract description; defining the connection parameters and interface location of the service access, and expressing and encapsulating it in a standardized manner in the form of an application.

[0016] The second aspect of the present invention provides a perception resource representation system that supports dynamic collaborative management and control, including: a perception resource acquisition module, used to obtain the perception resources to be represented; a representation element extraction module, used to extract multiple types of representation elements from the perception resources based on application layer information requirements; a representation element description module, used to use the presentation layer state transformation service architecture to abstractly describe multiple types of representation elements, including: specifying a unique uniform resource identifier for each of the multiple types of representation elements; based on the uniform resource identifier, performing multiple preset types of operations on each representation element; using a network ontology language to semantically describe each representation element; a representation element encapsulation module, used to standardize the expression and encapsulation of each representation element after the abstract description to complete the representation of the perception resources.

[0017] (III) Beneficial effects

[0018] The technical solution of the embodiment of the present invention has at least the following beneficial effects:

[0019] (1) Based on the information requirements of the application layer, multi-granularity perception resource abstract representation elements are extracted. From the application perspective, information describing the guidance capability, coordination capability, usage constraints, and scheduling control of the perception resources is added to facilitate task-oriented perception resource matching.

[0020] (2) Use the RESTful service architecture to describe virtual perception resources and implement resource operations based on HTTP operations, providing the meaning of perception resources and the correct way to use them for perception resource applications, ensuring support for resource applications based on semantic information consistency.

[0021] (3) It reduces the coupling between perception resources and functions, improves the flexible assembly capability of perception resources based on service requirements, improves the interconnection and interoperability between perception resources, and makes task-oriented perception resource matching more accurate.

[0022] (4) By providing standardized expression and encapsulation after virtualization, and a unified interface calling method, users do not need to understand the details of sensor control instructions, and can achieve virtual control and scheduling of different sensors, thereby lowering the user usage threshold and enabling users to fully control various types of perception resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 A flowchart of a method for characterizing perception resources supporting dynamic collaborative management and control according to an embodiment of the present invention is schematically shown;

[0024] Figure 2 Schematically shows a flow chart of extracting multiple types of representation elements according to an embodiment of the present invention;

[0025] Figure 3Schematically illustrates a flow chart for abstractly describing multiple types of representation elements according to an embodiment of the present invention;

[0026] Figure 4 A flowchart of semantically describing each representation element according to an embodiment of the present invention is schematically shown;

[0027] Figure 5 A flowchart for normalizing and packaging each representation element according to an embodiment of the present invention is schematically shown;

[0028] Figure 6 The structural block diagram of the perception resource representation system supporting dynamic collaborative management and control according to an embodiment of the present invention is schematically shown. DETAILED DESCRIPTION

[0029] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with specific embodiments and with reference to the accompanying drawings.

[0030] Figure 1 A flowchart of a method for representing perception resources supporting dynamic collaborative management and control according to an embodiment of the present invention is schematically shown.

[0031] Please refer to Figure 1 The perception resource characterization method supporting dynamic collaborative management and control in an embodiment of the present invention may include operations S110~S140.

[0032] In operation S110, a sensory resource to be characterized is acquired.

[0033] In operation S120, multiple types of representation elements are extracted from the perception resources based on the application layer information requirements.

[0034] In operation S130, a presentation layer state conversion service architecture is used to abstractly describe multiple types of representation elements.

[0035] In operation S140, each representation element after the abstract description is expressed and encapsulated in a standardized manner to complete the representation of the perception resource.

[0036] The technical solution of the present invention is described in detail below.

[0037] Figure 2 The flowchart of extracting multiple types of representation elements according to an embodiment of the present invention is schematically shown.

[0038] See also Figure 2 As shown, in the embodiment of the present invention, the above operation S120 specifically includes operations S210~S220.

[0039] In operation S210, the perceptual resources to be represented are abstracted into objects.

[0040] In operation S220, based on the requirements of the application layer information, multiple types of representation elements of the object are obtained through multi-granularity calculations.

[0041] Due to the characteristics of multiple types of sensing resources, large attribute differences, and complex relationships, various sensing resource entities are abstracted into objects, each of which contains several attributes to describe the object's form, characteristics, and usage conditions. The division and selection of attributes are determined according to the purpose and requirements of use.

[0042] In order to better support the efficient sharing and intelligent dynamic scheduling of perception resources, multi-granularity perception resource abstract representation elements are extracted based on the information requirements of the application layer to complete the division and selection of attributes. For example, the perception resource representation elements can be divided into 8 categories: sensing characteristics, mobility, guidance parameters, collaborative capabilities, information processing, data transmission, additional constraints and scheduling control. The following is a specific explanation of each type of perception representation element.

[0043] The sensing characteristics mainly describe the characteristics of the sensor. The sensing characteristics mainly include shape feature detection (geometric size, shape contour, etc.), radiation feature detection (emissivity, absorption ratio, etc.), scattering feature detection (scattering interface, polarization characteristics, etc.), soundprint feature detection (sonar characteristics, hydroacoustic characteristics, etc.), intention feature detection (departure, change of guard and return to port, etc.), group feature detection (formation, affiliation, etc.), motion parameter detection (heading, speed, acceleration, etc.), etc.

[0044] Maneuverability mainly describes the maneuverability of various sensing resources, which is mainly determined by the sensing platform. Maneuverability mainly includes initial position (coordinate system, starting coordinate point, etc.), orbit parameters (orbit semi-major axis, orbit eccentricity, etc.), activity speed (maximum speed, cruising speed, etc.), activity radius (platform activity radius, payload sensing range, etc.), duration (hovering time, revisit time, etc.), detection angle range (side swing angle, detection width, etc.), etc.

[0045] Guidance parameters mainly describe the guidance capabilities of various sensing resources. Guidance parameters mainly include point information guidance (coordinate system, guidance point, effective time, etc.), area information guidance (regional center, regional boundary coordinates, etc.), radar fingerprint guidance (radiation source, radar fingerprint, etc.), frequency band information guidance (uplink frequency, downlink frequency, bandwidth, etc.), electronic fingerprint guidance (frequency band, update cycle, etc.), intention information guidance (departure, change of guard, etc.), etc.

[0046] Collaboration capability mainly describes the collaboration capability of various sensing resources. Collaboration capability mainly includes collaboration mode (one master and one slave, one master and multiple slaves, peer-to-peer collaboration, etc.), networking requirements (common view networking, guided networking, etc.), collaboration objects (object name, object type, etc.), collaboration links (on-board links, wired links, wireless links, etc.), collaboration constraints (time constraints, space constraints, etc.), etc.

[0047] Information processing mainly describes the information processing capabilities of various sensing resources. Information processing capabilities mainly include product types (full color, visible light, SAR, electronic, fusion), product levels (level 0, level 1, level 2, level 3, level 4, etc.), failure requirements (single node processing capability, concurrent processing capability, etc.), processing mode (online processing, offline processing, etc.), number of processing nodes (number of regular nodes, maximum number of nodes), etc.

[0048] Data transmission mainly describes the characteristics of various sensing resources in data transmission. Data transmission mainly includes transmission mode (continuous transmission, breakpoint resume, etc.), transmission bandwidth (upload bandwidth, download bandwidth, total bandwidth, etc.), transmission delay (delay time, number of packet loss, etc.), transmission link (electromagnetic transmission, satellite relay, etc.), etc.

[0049] Additional constraints mainly describe the limiting conditions that various sensing resources need to meet during use. Additional constraints mainly include electromagnetic environment constraints (spectrum, power, polarization characteristics, etc.), lighting condition constraints (lighting angle, light intensity, light time), meteorological condition constraints (wind speed, wind direction, temperature, visibility, etc.), sea conditions (wave height, ocean currents, sea temperature, salinity, etc.), etc.

[0050] Scheduling control mainly describes the characteristics of scheduling control of various sensing resources. Scheduling control mainly includes control frequency band (spectrum, power, etc.), control range (maximum control range, maximum control number, etc.), power-on time (maximum power-on time, fixed power-on time, etc.), power-off time (shortest power-off time, fixed power-off time, etc.), interval time (shortest interval time, average interval time, etc.), working mode selection (scheduling, control, etc.), etc.

[0051] Based on the above 8 types of elements, the perception resources are characterized in an all-round and multi-angle manner from multiple angles, including static attributes (such as sensing characteristics, etc.), dynamic attributes (such as mobility), usage modes (such as guidance parameters, collaborative modes, etc.), and usage constraints (such as accessory constraints, scheduling control, etc.), laying the foundation for subsequent task-oriented perception resource matching.

[0052] Through the embodiments of the present invention, multi-granularity perception resource abstract representation elements are extracted based on application layer information requirements, changing the traditional representation method centered on resource static attributes (describing resources, their attributes and attribute values). The present invention not only describes the static attribute information of perception resources, but also adds information describing the guidance capability, coordination capability, usage constraints and scheduling control of perception resources from an application perspective, so as to facilitate task-oriented perception resource matching.

[0053] Figure 3 The flowchart for abstractly describing multiple types of representation elements according to an embodiment of the present invention is schematically shown.

[0054] See also Figure 3 As shown, in the embodiment of the present invention, the above operation S130 uses the presentation layer state conversion service architecture to abstractly describe multiple types of representation elements, specifically including operations S310~S330.

[0055] In operation S310 , a unique uniform resource identifier is assigned to each of the multiple types of representation elements.

[0056] In operation S320, multiple preset types of operations are performed on each representation element based on the uniform resource identifier.

[0057] In operation S330, a network ontology language is used to semantically describe each representation element.

[0058] In an embodiment of the present invention, an abstract description of a perception resource entity is performed based on a RESTful (Representational State Transfer) service architecture. Specifically, a unique uniform resource identifier (URI) is specified for multiple types of representation elements, through which a specific resource can be accessed. According to the URI, operations are performed on each representation element, and the operations include: acquisition, creation, modification, and deletion. Among them, the acquisition operation includes accessing the representation element to the uniform resource identifier based on HTTP (communication protocol); the creation operation includes creating a target representation element based on the uniform resource identifier based on the communication protocol, and re-specifying the corresponding uniform resource identifier for the target representation element; the modification operation includes updating the status of the representation element based on the uniform resource identifier based on the communication protocol; the deletion operation includes deleting the representation element corresponding to the uniform resource identifier based on the communication protocol.

[0059] Figure 4 A flowchart for semantically describing each representation element according to an embodiment of the present invention is schematically shown.

[0060] See also Figure 4As shown, the above operation S330 uses the network ontology language to semantically describe each representation element, and specifically includes operations S410~S420.

[0061] In operation S410, according to the results of performing multiple preset types of operations on each representation element, a corresponding service configuration file is matched and a service is executed.

[0062] In operation S420, a unified semantic description is performed on the input, output, operation premise and result after the operation of the service by using a dynamic description logic method.

[0063] In the embodiment of the present invention, OWL Ontology Web Language is used for resource semantic description. Specifically, the result of the above-mentioned type of operation on each representation element is matched with the service configuration file, and service matching is implemented according to the service configuration file to find a service that meets the needs of the service requester and start executing the service.

[0064] In order to effectively support resource matching and operation combination reasoning, Dynamic Description Logic (DDL) is used to uniformly describe the operation premise and operation consequences of services. Dynamic Description Logic introduces the concept of action on the basis of description logic, adds an action definition set to the logic system, combines static semantics and dynamic semantics, and can effectively represent and reason about dynamic processes and operation mechanisms, providing a reasonable logical basis for the semantic web. Among them, the actions in the action definition set are divided into two categories: atomic actions and compound actions.

[0065] Through the embodiments of the present invention, the RESTful service architecture is used to describe virtual perception resources, and the operation of resources is implemented based on HTTP operations, providing the meaning of perception resources and the correct way to use them for perception resource applications, solving the semantic conflicts caused by differences in implicit meanings, views and assumptions for collaborative perception resource entities, and ensuring support for resource applications (resource discovery, resource matching, resource selection, resource scheduling, etc.) based on the consistency of semantic information. The abstract description capability of virtual resources based on network ontology semantics reduces the coupling between perception resources and functions, improves the flexible assembly capability of perception resources based on service requirements, and improves the interconnection and interoperability between perception resources. In addition, semantic descriptions such as the input, output, operation premise and results after the operation of the perception resource service are added to make task-oriented perception resource matching more accurate.

[0066] Figure 5 The flowchart for normalizing and packaging each representation element according to an embodiment of the present invention is schematically shown.

[0067] See also Figure 5 As shown, the above operation S140 specifically includes operations S510~S520.

[0068] In operation S510, a service access form of the representation element after the abstract description is determined.

[0069] In operation S520, connection parameters and interface locations for service access are defined, and are standardized and encapsulated in the form of an application program.

[0070] Specifically, each representation element after the abstract description is standardized and encapsulated in the form of Web services to complete the representation of the perception resources. Among them, the connection parameters and interface locations of service access must be consistent to achieve sharing and interoperability of perception resources.

[0071] Through the embodiments of the present invention, standardized expression and encapsulation after virtualization are provided, and a unified interface calling method is used, so that users do not need to understand the details of sensor control instructions, and virtual control and scheduling of different sensors can be achieved, thereby lowering the user usage threshold and enabling users to fully control various types of perception resources.

[0072] Based on the above-mentioned perception resource representation method supporting dynamic collaborative management and control, the present invention also provides a perception resource representation system supporting dynamic collaborative management and control. Figure 6 The system is described in detail.

[0073] Figure 6 The structural block diagram of the perception resource representation system supporting dynamic collaborative management and control according to an embodiment of the present invention is schematically shown.

[0074] like Figure 6 As shown, the perception resource representation system 600 supporting dynamic collaborative management and control in this embodiment includes a perception resource acquisition module 610 , a representation element extraction module 620 , a representation element description module 630 and a representation element encapsulation module 640 .

[0075] The sensing resource acquisition module 610 is used to acquire the sensing resource to be characterized. In one embodiment, the sensing resource acquisition module 610 may perform the operation S110 described above, which will not be described in detail herein.

[0076] The characterization element extraction module 620 is used to extract multiple types of characterization elements from the sensing resources based on the application layer information requirements. In one embodiment, the characterization element extraction module 620 may perform the operation S120 described above, which will not be described in detail here.

[0077] The representation element description module 630 is used to abstractly describe multiple types of representation elements using the presentation layer state conversion service architecture, including: assigning a unique uniform resource identifier to each of the multiple types of representation elements; performing multiple preset type operations on each representation element based on the uniform resource identifier; and using the network ontology language to semantically describe each representation element. In one embodiment, the representation element description module 630 can perform the operation S130 described above, which will not be repeated here.

[0078] The representation element encapsulation module 640 is used to perform standardized expression and encapsulation on each representation element after abstract description to complete the representation of the perception resource. In one embodiment, the representation element encapsulation module 640 may perform the operation S140 described above, which will not be described in detail here.

[0079] According to the embodiments of the present invention, any multiple of the modules, or at least part of the functions of any multiple of them, can be implemented in one module. According to the embodiments of the present invention, any one or more of the modules can be split into multiple modules for implementation. According to the embodiments of the present invention, any one or more of the modules can be at least partially implemented as a hardware circuit, such as a field programmable gate array (FPGA), a programmable logic array (PLA), a system on a chip, a system on a substrate, a system on a package, an application-specific integrated circuit (ASIC), or can be implemented by hardware or firmware in any other reasonable way of integrating or packaging the circuit, or implemented in any one of the three implementation methods of software, hardware and firmware or in any appropriate combination of any of them. Alternatively, according to the embodiments of the present invention, one or more of the modules can be at least partially implemented as a computer program module, and when the computer program module is run, the corresponding function can be executed.

[0080] For example, any multiple of the perception resource acquisition module 610, the characterization element extraction module 620, the characterization element description module 630 and the characterization element encapsulation module 640 can be combined in one module for implementation, or any one of the modules can be split into multiple modules. Alternatively, at least part of the functions of one or more of these modules can be combined with at least part of the functions of other modules and implemented in one module. According to an embodiment of the present invention, at least one of the perception resource acquisition module 610, the characterization element extraction module 620, the characterization element description module 630 and the characterization element encapsulation module 640 can be at least partially implemented as a hardware circuit, such as a field programmable gate array (FPGA), a programmable logic array (PLA), a system on a chip, a system on a substrate, a system on a package, an application specific integrated circuit (ASIC), or can be implemented by hardware or firmware such as any other reasonable way of integrating or encapsulating the circuit, or implemented in any one of the three implementation methods of software, hardware and firmware or in an appropriate combination of any of them. Alternatively, at least one of the perception resource acquisition module 610, the characterization element extraction module 620, the characterization element description module 630 and the characterization element encapsulation module 640 may be at least partially implemented as a computer program module, and when the computer program module is executed, the corresponding function may be executed.

[0081] The above specific embodiments further illustrate the purpose, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above are only specific embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for representing perception resources to support dynamic collaborative management and control. It is characterized in that include: Acquire the perceptual resources to be represented; Extracting multiple types of representation elements from the perception resources based on application layer information requirements; The presentation layer state conversion service architecture is used to abstractly describe the multiple types of representation elements, including: Assigning a unique uniform resource identifier to each of the plurality of types of representation elements; Based on the uniform resource identifier, performing multiple preset types of operations on each representation element; Use network ontology language to semantically describe each representation element; Use dynamic description logic to uniformly describe the service's operating premise and consequences; Each representation element after the abstract description is expressed and encapsulated in a standardized manner to complete the representation of the perception resource; The extracting of multiple types of representation elements from the perception resources based on the application layer information requirements includes: Abstracting the perception resource to be represented into an object; Based on the requirements of application layer information, multiple types of characterization elements of the object are obtained through multi-granularity calculations.

2. According to the method for representing perception resources supporting dynamic collaborative management and control according to claim 1, It is characterized in that The multiple types of characterization elements include: sensing characteristics, mobility, guidance parameters and coordination capabilities, wherein: The sensing characteristics describe the sensor characteristics, and the sensing characteristics include shape feature detection, radiation feature detection, scattering feature detection, voiceprint feature detection, intention feature detection, group feature detection and motion parameter detection; The mobility describes the mobility of various sensing resources, including initial position, orbital parameters, activity speed, activity radius, duration and detection angle range; The guidance parameters describe the guidance capabilities of various sensing resources, and the guidance parameters include point information guidance, area information guidance, radar fingerprint guidance, frequency band information guidance, electronic fingerprint guidance and intention information guidance; The collaborative capability describes the collaborative capability of various sensing resources, and the collaborative capability includes collaborative mode, networking requirements, collaborative objects, collaborative links and collaborative constraints.

3. According to the method for characterizing perception resources supporting dynamic collaborative management and control according to claim 1, It is characterized in that The multiple types of characterization elements include: information processing, data transmission, additional constraints and scheduling control, wherein: The information processing describes the information processing capabilities of various types of sensing resources, and the information processing includes product type, product level, failure requirements, processing mode and number of processing nodes; The data transmission describes the characteristics of various types of sensing resources in terms of data transmission, and the data transmission includes transmission mode, transmission bandwidth, transmission delay and transmission link; The additional constraints describe the limiting conditions that various sensing resources need to meet during use, and the additional constraints include electromagnetic environment constraints, lighting condition constraints, meteorological condition constraints and sea conditions; The scheduling control describes the characteristics of the scheduling control of various types of sensing resources, and the scheduling control includes the control frequency band, control range, power-on time, power-off time, interval time and working mode.

4. According to claim 1, the method for representing perception resources supporting dynamic collaborative management and control, It is characterized in that The multiple preset type operations include obtaining, creating, modifying and deleting, wherein: The acquisition operation includes accessing the representation element of the uniform resource identifier based on the communication protocol; The creation operation includes creating a target representation element according to the uniform resource identifier based on the communication protocol, and again specifying the corresponding uniform resource identifier for the target representation element; The modification operation includes updating the state of the representation element according to the uniform resource identifier based on a communication protocol; The deletion operation includes deleting the representation element corresponding to the uniform resource identifier based on a communication protocol.

5. According to claim 4, the method for representing perception resources supporting dynamic collaborative management and control, It is characterized in that The semantic description of each representation element using network ontology language includes: According to the results of performing the multiple preset types of operations on each representation element, matching the corresponding service configuration file and executing the service; The input, output, operation premise and result after operation of the service are respectively described in a unified semantic manner using the method of dynamic description logic.

6. The method for representing perception resources supporting dynamic collaborative management and control according to claim 5, It is characterized in that The standardized expression and encapsulation of each representation element after the abstract description includes: Determine the service access form of the representation element after the abstract description; The connection parameters and interface locations for the service access are defined, and are standardized and encapsulated in the form of an application.

7. A perception resource representation system that supports dynamic collaborative management and control, It is characterized in that include: A perception resource acquisition module, used to acquire the perception resources to be represented; A representation element extraction module, used to extract multiple types of representation elements from the perception resources based on application layer information requirements; The representation element description module is used to abstractly describe the multiple types of representation elements using the presentation layer state conversion service architecture, including: Assigning a unique uniform resource identifier to each of the plurality of types of representation elements; Based on the uniform resource identifier, performing multiple preset types of operations on each representation element; Use network ontology language to semantically describe each representation element; Use dynamic description logic to uniformly describe the service's operating premise and consequences; A representation element encapsulation module is used to perform standardized expression and encapsulation on each representation element after the abstract description to complete the representation of the perception resource; The extracting of multiple types of representation elements from the perception resources based on the application layer information requirements includes: Abstracting the perception resource to be represented into an object; Based on the requirements of application layer information, multiple types of characterization elements of the object are obtained through multi-granularity calculations.

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