Knowledge graph construction method and device for radar echo data, equipment and medium

Abstract

The invention relates to the technical field of computers, in particular to a knowledge graph construction method and device for radar echo data, equipment and a medium. The method comprises the following steps: firstly, acquiring radar echo data, analyzing the radar echo data through a preset transmission protocol to obtain entity nodes, parameter value nodes and parameter types of the radar echo data, and constructing a triple of the radar echo data according to the entity nodes, the parameter value nodes and the parameter types; wherein the number in the radar echo data number node of the parameter value node has a mapping relationship with the actual storage address of the corresponding data, classifying the plurality of triads to obtain a knowledge graph of the radar echo data, and performing data mining by using the knowledge graph of the radar echo data to improve the mining efficiency of the radar echo data.

Description

Technical Field

[0001] The present invention relates to the field of computer technology, and in particular to a method, device, equipment and medium for constructing a knowledge graph of radar echo data. Background Art

[0002] The storage of radar echo data's signal waveform, signal band, target type and other related parameter information is of great significance for subsequent SAR imaging, radar target characteristic analysis, radar target detection and recognition, deep learning model training to solve various problems and other data processing.

[0003] In the related technologies, the storage carriers of radar echo data related parameters are mostly relational databases, which have the disadvantages of serious data redundancy, low visualization, and inconvenience in data mining.

[0004] Based on this, there is an urgent need for a knowledge graph construction method, device, equipment and medium for radar echo data to solve the technical problem of how to improve the mining efficiency of radar echo data. Summary of the invention

[0005] In order to solve the technical problem of how to improve the mining efficiency of radar echo data, the embodiments of the present invention provide a method, device, equipment and medium for constructing a knowledge graph of radar echo data.

[0006] In a first aspect, an embodiment of the present invention provides a method for constructing a knowledge graph of radar echo data, comprising:

[0007] Get radar echo data;

[0008] Parsing the radar echo data through a preset transmission protocol to obtain entity nodes, parameter value nodes and parameter types of the radar echo data;

[0009] Based on the entity node, the parameter value node and the parameter type, a triplet of radar echo data is constructed; wherein a mapping relationship exists between the number in the radar echo data number node of the parameter value node and the actual storage address of the corresponding data;

[0010] The plurality of triples are classified to obtain a knowledge graph of radar echo data, and data mining is performed using the knowledge graph of radar echo data.

[0011] In a second aspect, an embodiment of the present invention further provides a knowledge graph construction device for radar echo data, comprising:

[0012] An acquisition module is used to acquire radar echo data;

[0013] A first data processing module, used for parsing the radar echo data through a preset transmission protocol to obtain entity nodes, parameter value nodes and parameter types of the radar echo data;

[0014] A second data processing module is used to construct a triple of radar echo data based on the entity node, the parameter value node and the parameter type; wherein a mapping relationship exists between the number in the radar echo data number node of the parameter value node and the actual storage address of the corresponding data;

[0015] The third data processing module is used to classify the multiple triples to obtain a knowledge graph of radar echo data, and perform data mining based on the knowledge graph of radar echo data.

[0016] In a third aspect, an embodiment of the present invention further provides an electronic device, including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the method described in any embodiment of the present invention is implemented.

[0017] In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon, which, when executed in a computer, causes the computer to execute the method described in any embodiment of the present invention.

[0018] The embodiment of the present invention provides a method, device, equipment and medium for constructing a knowledge graph of radar echo data, which obtains radar echo data, parses the radar echo data through a preset transmission protocol, and obtains entity nodes, parameter value nodes and parameter types of the radar echo data, wherein the preset transmission protocol technicians can customize the specific categories of the preset transmission protocol according to the type of radar echo data; then construct triples of radar echo data according to the entity nodes, parameter value nodes and parameter types; wherein there is a mapping relationship between the number in the radar echo data number node of the parameter value node and the actual storage address of the corresponding data, and multiple triplets are classified to obtain a knowledge graph of radar echo data, and data mining is performed based on the knowledge graph of radar echo data to improve the mining efficiency of radar echo data. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0020] Figure 1It is a flow chart of a method for constructing a knowledge graph of radar echo data provided by an embodiment of the present invention;

[0021] Figure 2 is a hardware architecture diagram of an electronic device provided by an embodiment of the present invention;

[0022] Figure 3 It is a structural diagram of a knowledge graph construction device for radar echo data provided by an embodiment of the present invention;

[0023] Figure 4 It is a schematic diagram of a radar echo data knowledge graph data layer provided by an embodiment of the present invention;

[0024] Figure 5 It is a schematic diagram of a radar echo data knowledge graph model layer provided by an embodiment of the present invention;

[0025] Figure 6 It is a schematic diagram of a parameter information relationship knowledge graph provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0026] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0027] Please refer to Figure 1 , an embodiment of the present invention provides a method for constructing a knowledge graph of radar echo data, the method comprising:

[0028] Step 100: Acquire radar echo data;

[0029] Step 102: parsing the radar echo data through a preset transmission protocol to obtain entity nodes, parameter value nodes and parameter types of the radar echo data;

[0030] Step 104: constructing a triplet of radar echo data based on the entity node, the parameter value node and the parameter type; wherein there is a mapping relationship between the number in the radar echo data number node of the parameter value node and the actual storage address of the corresponding data;

[0031] Step 106: Classify the multiple triples to obtain a knowledge graph of the radar echo data, and perform data mining based on the knowledge graph of the radar echo data.

[0032] In an embodiment of the present invention, radar echo data is obtained, and the radar echo data is parsed through a preset transmission protocol to obtain entity nodes, parameter value nodes and parameter types of the radar echo data, wherein a person skilled in the art of the preset transmission protocol can customize the specific category of the preset transmission protocol according to the type of radar echo data; then, according to the entity nodes, parameter value nodes and parameter types, triples of radar echo data are constructed; wherein there is a mapping relationship between the number in the radar echo data numbering node of the parameter value node and the actual storage address of the corresponding data, multiple triplets are classified to obtain a knowledge graph of the radar echo data, and data mining is performed using the knowledge graph of the radar echo data to improve the mining efficiency of the radar echo data.

[0033] Described below Figure 1 How the various steps are performed.

[0034] For step 100:

[0035] In one embodiment of the present invention, radar echo data may be collected by a radar receiver.

[0036] Regarding step 102:

[0037] In one embodiment of the present invention, a person skilled in the art may customize the specific category of the preset transmission protocol according to the type of radar echo data.

[0038] Regarding step 104:

[0039] In one embodiment of the present invention, the parameter information related to the radar echo data is parsed, and the relationship between the radar echo data entity node, parameter value node and parameter type is extracted, such as "(signal data) 1-band-(band) 3", to construct a knowledge graph data layer. At the same time, a comparison table between the number in the radar echo data number node and the actual storage address of the corresponding data is constructed to achieve the mapping of the radar echo data and its corresponding entity node in the knowledge graph.

[0040] Regarding step 106:

[0041] In one embodiment of the present invention, step 106 may specifically include:

[0042] Eliminate redundancy on multiple triplets to obtain triples after redundancy elimination;

[0043] The radar echo data numbering nodes of the triplet after redundancy is eliminated are classified into one category, and the parameter information corresponding to the radar echo data of the triplet after redundancy is eliminated is classified into one category to obtain a knowledge graph of the radar echo data, and data mining is performed based on the knowledge graph of the radar echo data.

[0044] In this embodiment, in terms of various parameter information of signal data, duplicate nodes are queried and deleted, one of the nodes is retained, and the relationship between the signal data and its corresponding parameter information value in each triple is recorded to build the relationship between the signal data and the retained nodes in the corresponding parameter information. All entity nodes are classified to facilitate the query and management of the subsequent knowledge graph. Specifically, entity classification can be divided into two categories: all radar echo data number nodes are divided into one category, and all parameter information corresponding to radar echo data are divided into one category.

[0045] In one embodiment of the present invention, the parameter information category includes multiple subcategories, including a band information category, a transmission signal waveform category, and a radar echo data target category.

[0046] In one embodiment of the present invention, after step 106, the following steps may also be included:

[0047] Relational reasoning is performed based on the knowledge graph of the radar echo data to obtain a search result.

[0048] In this embodiment, the relational reasoning is mainly based on the knowledge graph of radar echo data and its parameter information, with the radar echo data number node as the center, to reason about the relationship between two different signal data parameter information. Specifically, according to the needs of relational reasoning, the relationship between different parameter information is constructed by querying indirect relationships, so as to obtain the triples between new parameter information and form the parameter information relationship knowledge graph data layer. Then, by removing redundancy, the triples between all parameter information are merged into a knowledge graph network to complete the construction of the parameter information relationship knowledge graph pattern layer. For example, there are multiple triplets of "(signal data) 1, 2, 3, ... - band - (band) 3", "(signal data) 1, 2, 3, ... - signal waveform - (waveform) 2", and "(signal data) 1, 2, 3, ... - target category - (target category) 4". Now it is necessary to infer the relationship between the transmitted signal band and waveform corresponding to the radar echo data, and the relationship between the transmitted signal waveform and the identified target type. According to the above triplets, the band nodes "(band) 3" and "(waveform) 2", "(waveform) 2" and "(target category) 4" connecting the same signal data node are established to obtain the triplets of "(band) 3-band waveform-(waveform) 2" and "(waveform) 2-waveform target-(target category) 4", and then combine these two triplets to obtain the relationship network of "(band) 3-band waveform-(waveform) 2-waveform target-(target category) 4".

[0049] like Figure 4 , 5As shown, in this embodiment, the orange circle in the radar echo data knowledge graph data layer represents the executed task, the red circle represents the band of the radar echo data, the brown circle represents the type of the waveform of the radar echo data, and the blue circle represents the index.

[0050] like Figure 6 As shown, in this embodiment, the orange circle in the parameter information relationship knowledge graph represents the executed task, the red circle represents the band of the radar echo data, and the brown circle represents the type of the waveform of the radar echo data.

[0051] like Figure 2 , Figure 3 As shown, an embodiment of the present invention provides a device for constructing a knowledge graph of radar echo data. The device embodiment can be implemented by software, or by hardware or a combination of software and hardware. From the hardware level, Figure 2 As shown, it is a hardware architecture diagram of an electronic device where a knowledge graph construction device for radar echo data provided by an embodiment of the present invention is located, except Figure 2 In addition to the processor, memory, network interface, and non-volatile memory shown, the electronic device in the embodiment may also include other hardware, such as a forwarding chip responsible for processing messages, etc. Taking software implementation as an example, Figure 3 As shown, as a device in a logical sense, the CPU of the electronic device in which it is located reads the corresponding computer program in the non-volatile memory into the internal memory and runs it.

[0052] like Figure 3 As shown, this embodiment provides a knowledge graph construction device for radar echo data, and the device includes:

[0053] An acquisition module 300 is used to acquire radar echo data;

[0054] The first data processing module 302 is used to parse the radar echo data through a preset transmission protocol to obtain the entity node, parameter value node and parameter type of the radar echo data;

[0055] A second data processing module 304 is used to construct a triple of radar echo data based on the entity node, the parameter value node and the parameter type; wherein a mapping relationship exists between the number in the radar echo data number node of the parameter value node and the actual storage address of the corresponding data;

[0056] The third data processing module 306 is used to classify the multiple triples to obtain a knowledge graph of radar echo data, and perform data mining based on the knowledge graph of radar echo data.

[0057] In an embodiment of the present invention, the acquisition module 300 can be used to execute step 100 in the above method embodiment, the first data processing module 302 can be used to execute step 102 in the above method embodiment, the second data processing module 304 can be used to execute step 104 in the above method embodiment, and the third data processing module 306 can be used to execute step 106 in the above method embodiment.

[0058] In one embodiment of the present invention, the classifying the plurality of triples to obtain a knowledge graph of radar echo data, and performing data mining using the knowledge graph of radar echo data includes:

[0059] Eliminate redundancy on the plurality of triples to obtain triples after redundancy elimination;

[0060] The radar echo data numbering nodes of the triplet after redundancy is eliminated are grouped into one category, and the parameter information corresponding to the radar echo data of the triplet after redundancy is eliminated is grouped into one category to obtain a knowledge graph of the radar echo data, and data mining is performed based on the knowledge graph of the radar echo data.

[0061] In one embodiment of the present invention, it also includes:

[0062] The parameter information category includes a plurality of subcategories, including a band information category, a transmission signal waveform category, and a radar echo data target category.

[0063] In one embodiment of the present invention, after classifying the plurality of triples to obtain a knowledge graph of radar echo data, and performing data mining using the knowledge graph of radar echo data, the method further includes:

[0064] Relational reasoning is performed based on the knowledge graph of the radar echo data to obtain a search result.

[0065] It is to be understood that the structure illustrated in the embodiment of the present invention does not constitute a specific limitation on a knowledge graph construction device for radar echo data. In other embodiments of the present invention, a knowledge graph construction device for radar echo data may include more or fewer components than shown in the figure, or combine certain components, or split certain components, or arrange the components differently. The components shown in the figure may be implemented in hardware, software, or a combination of software and hardware.

[0066] The information interaction, execution process and other contents between the modules in the above-mentioned device are based on the same concept as the embodiment of the method of the present invention. For the specific contents, please refer to the description in the embodiment of the method of the present invention, and no further description is given here.

[0067] An embodiment of the present invention further provides an electronic device, including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, a knowledge graph construction method for radar echo data in any embodiment of the present invention is implemented.

[0068] An embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the processor executes a method for constructing a knowledge graph of radar echo data in any embodiment of the present invention.

[0069] Specifically, a system or device equipped with a storage medium can be provided, on which software program codes that implement the functions of any of the above-mentioned embodiments are stored, and a computer (or CPU or MPU) of the system or device can be enabled to read and execute the program codes stored in the storage medium.

[0070] In this case, the program code itself read from the storage medium can realize the function of any one of the above-mentioned embodiments, and thus the program code and the storage medium storing the program code constitute a part of the present invention.

[0071] The storage medium embodiments for providing the program code include a floppy disk, a hard disk, a magneto-optical disk, an optical disk (such as CD-ROM, CD-R, CD-RW, DVD-ROM, DVD-RAM, DVD-RW, DVD+RW), a magnetic tape, a non-volatile memory card, and a ROM. Alternatively, the program code can be downloaded from a server computer by a communication network.

[0072] In addition, it should be clear that the functions of any of the above embodiments can be implemented not only by executing the program code read by the computer, but also by enabling an operating system operating on the computer to complete part or all of the actual operations based on instructions from the program code.

[0073] In addition, it can be understood that the program code read from the storage medium is written to a memory provided in an expansion board inserted into the computer or to a memory provided in an expansion module connected to the computer, and then based on the instructions of the program code, a CPU installed on the expansion board or expansion module is enabled to perform part or all of the actual operations, thereby realizing the functions of any of the above-mentioned embodiments.

[0074] It should be noted that, in this article, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0075] A person of ordinary skill in the art can understand that all or part of the steps of implementing the above method embodiments can be completed by hardware related to program instructions, and the aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it executes the steps of the above method embodiments; and the aforementioned storage medium includes: ROM, RAM, magnetic disk or optical disk, etc., various media that can store program codes.

[0076] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for constructing a knowledge graph of radar echo data, characterized in that: include: Get radar echo data; Parsing the radar echo data through a preset transmission protocol to obtain an entity node of the radar echo data, the parameter value node, and the parameter type; Based on the entity node, the parameter value node and the parameter type, a triplet of radar echo data is constructed; wherein a mapping relationship exists between the number in the radar echo data number node of the parameter value node and the actual storage address of the corresponding data; The plurality of triples are classified to obtain a knowledge graph of radar echo data, and data mining is performed using the knowledge graph of radar echo data.

2. The method according to claim 1, characterized in that The step of classifying the plurality of triples to obtain a knowledge graph of radar echo data, and performing data mining using the knowledge graph of radar echo data includes: Eliminate redundancy on the plurality of triples to obtain triples after redundancy elimination; The radar echo data numbering nodes of the triplet after redundancy is eliminated are grouped into one category, and the parameter information corresponding to the radar echo data of the triplet after redundancy is eliminated is grouped into one category to obtain a knowledge graph of the radar echo data, and data mining is performed based on the knowledge graph of the radar echo data.

3. The method according to claim 2, characterized in that Also includes: The parameter information category includes a plurality of subcategories, including a band information category, a transmission signal waveform category, and a radar echo data target category.

4. The method according to claim 1, characterized in that: After classifying the plurality of triples to obtain a knowledge graph of radar echo data, and performing data mining using the knowledge graph of radar echo data, the method further includes: Relational reasoning is performed based on the knowledge graph of the radar echo data to obtain a search result.

5. A knowledge graph construction device for radar echo data, characterized in that: include: An acquisition module is used to acquire radar echo data; A first data processing module, used for parsing the radar echo data through a preset transmission protocol to obtain the entity node of the radar echo data, the parameter value node and the parameter type; A second data processing module is used to construct a triple of radar echo data based on the entity node, the parameter value node and the parameter type; wherein a mapping relationship exists between the number in the radar echo data number node of the parameter value node and the actual storage address of the corresponding data; The third data processing module is used to classify the multiple triples to obtain a knowledge graph of radar echo data, and perform data mining based on the knowledge graph of radar echo data.

6. The device according to claim 5, characterized in that The step of classifying the plurality of triples to obtain a knowledge graph of radar echo data, and performing data mining using the knowledge graph of radar echo data includes: Eliminate redundancy on the plurality of triples to obtain triples after redundancy elimination; The radar echo data numbering nodes of the triplet after redundancy is eliminated are grouped into one category, and the parameter information corresponding to the radar echo data of the triplet after redundancy is eliminated is grouped into one category to obtain a knowledge graph of the radar echo data, and data mining is performed based on the knowledge graph of the radar echo data.

7. The device according to claim 6, characterized in that Also includes: The parameter information category includes a plurality of subcategories, including a band information category, a transmission signal waveform category, and a radar echo data target category.

8. The device according to claim 5, characterized in that After classifying the plurality of triples to obtain a knowledge graph of radar echo data, and performing data mining using the knowledge graph of radar echo data, the method further includes: Relational reasoning is performed based on the knowledge graph of the radar echo data to obtain a search result.

9. An electronic device, characterized in that: The method comprises a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the method according to any one of claims 1 to 4 is implemented.

10. A computer-readable storage medium, characterized in that: A computer program is stored thereon, and when the computer program is executed in a computer, the computer is caused to execute the method according to any one of claims 1 to 4.

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