A multi-source massive radar data management method and system

Abstract

The application discloses a kind of multi-source mass radar data management method and system, the method includes the following steps: multi-source data buffer: receiving various data, and carrying out buffer processing;File writing: network transceiver thread transmission data is stored to local hard disk in binary file form;Data analysis: receive the absolute path of binary file after file writing, according to protocol agreement complete various message plaintext analysis.The application designs buffer logic with map+ fixed-length array, considers track loss, eliminates batch and the timing of each network data, avoids program crash caused by frequent opening of memory in network storm scenario, combines the advantages of map search and the convenience of array access, and considers buffer efficiency.

Description

Technical Field

[0001] This invention belongs to the field of radar situation display and analysis technology, and in particular relates to a method and system for managing multi-source massive radar data. Background Technology

[0002] Ground-based guidance radar is a multi-functional radar that uses microwave technology to search, track, and identify targets. It is mainly used for guiding surface-to-air missiles, air-to-air missiles, and anti-ship missiles. The interaction between the operator and the guidance radar is mainly bridged by display control software and situational awareness software, which enables the display of information such as target trajectory, identification results, and system status, as well as the scheduling and control of radar equipment and back-end processing.

[0003] With the rapid development of guidance technology, radar systems are becoming increasingly complex, and the sources and scale of radar data are growing daily. Information exchange with higher-level command systems often involves data filtering and stitching, making conventional data management methods insufficient to meet practical needs. Summary of the Invention

[0004] To address the above problems, this invention proposes a method for managing multi-source massive radar data, comprising the following steps:

[0005] Multi-source data caching: Receives various types of data and performs caching processing;

[0006] File writing: Receive various types of data and store them on the local hard drive in binary file format;

[0007] Data parsing: Receives the absolute path of the binary file after it has been written, and performs plaintext parsing of various messages according to the protocol.

[0008] Furthermore, multi-source data caching, file writing, and data parsing are implemented using multi-threading, with a locking mechanism added for thread synchronization.

[0009] Furthermore, the received data is based on the flight track. When the target flight track disappears, the corresponding batch number cache is cleared and the parsing and caching of the corresponding data packets are stopped.

[0010] Furthermore, the network data includes flight track data, identification results, and early warning information.

[0011] Furthermore, multi-source data caching specifically includes the following steps:

[0012] Step 1.1 Provide a data access interface and perform data retrieval based on data identifiers:

[0013] Step 1.2 If the target data exists, proceed to step 1.5;

[0014] Step 1.3 If the target data to be retrieved does not exist and the cache is full, clear the oldest historical data and proceed to step 1.5;

[0015] Step 1.4: If the target data to be retrieved does not exist and the cache is not full, proceed directly to Step 1.5;

[0016] Step 1.5: Update the map, which stores the position of the target data corresponding to the data identifier in the array. Proceed to Step 1.6.

[0017] Step 1.6: Based on the position of the target data in the array returned by the map, write the target data into the array in the buffer.

[0018] Furthermore, the data identifier is the target track batch identifier.

[0019] Furthermore, the file writing process specifically includes the following steps:

[0020] Receive network data;

[0021] Determine if the data buffer is full. If it is full, discard the data. If it is not full, record the thread, write the data to the binary file, and divide the binary file path based on the data source.

[0022] Furthermore, it supports controlling the start and end of data recording by checking boxes; the directory structure of the network data is three-level, with the first level being datarecord, the second level being recv and report, and the third level including EY and RaDadar. The three-level structure of the network data enables the writing of binary files to the hard disk.

[0023] Furthermore, the data parsing specifically includes the following steps:

[0024] Step 3.1: Determine if the binary file is corrupted. If the file is corrupted, proceed to step 3.2; if the file is not corrupted, proceed to step 3.3.

[0025] Step 3.2: Parsing failed, ending the data parsing process;

[0026] Step 3.3: Read the binary file to obtain the original network packets, get the packet identifier, and proceed to step 3.4;

[0027] Step 3.4: Determine if an adaptation script exists. If it exists, proceed to step 3.5. If it does not exist, output the log and return to step 3.3.

[0028] Step 3.5: Plaintext parsing. Determine if the binary file has been completely read. If yes, end the data parsing process. If not, return to step 3.3 and continue reading the binary file until all binary files have been read.

[0029] Furthermore, considering the need for flexible adaptation of parsing logic when network packets change, plaintext parsing of binary files is completed based on Lua scripts; scenarios of network packet changes include adding packet types and revising data item definitions.

[0030] A multi-source massive radar data management system is also provided, including a multi-source data caching module, a file writing module, and a data parsing module. The multi-source data caching module, file writing module, and data parsing module implement radar data management based on the above method.

[0031] Compared with the prior art, the present invention has the following advantages:

[0032] The beneficial effects of this invention are as follows:

[0033] (1) On the basis of the traditional network data management method of display and control software, a multi-source data aggregation and caching mechanism is added, which is conducive to the unified management of target information;

[0034] (2) The cache logic is designed with map + fixed-length array. Considering the loss of track, batch cancellation and the time sequence of each network data, the program crashes due to frequent memory allocation in network storm scenarios, while combining the advantages of map lookup with the convenience of array access, thus taking into account the cache efficiency.

[0035] (3) The data recording method designed for the operator's test review needs is in line with the actual combat situation and is conducive to the operator's accurate control of information such as data recording time and data source;

[0036] (4) The parsing function based on Lua scripts can perfectly adapt to multiple scenarios such as adding message types and revising message data item definitions without changing the parsing program, which greatly facilitates the parsing and management of plaintext data. Attached Figure Description

[0037] Figure 1 This is a flowchart of a method according to an embodiment of the present invention.

[0038] Figure 2 This is a flowchart of radar data recording according to an embodiment of the present invention.

[0039] Figure 3 This is a flowchart of the radar data plaintext parsing process according to an embodiment of the present invention.

[0040] Figure 4 This is a screenshot of the cache clearing button in the interactive software according to an embodiment of the present invention.

[0041] Figure 5 This is a screenshot of the interactive software data recording control button according to an embodiment of the present invention.

[0042] Figure 6 This is a hierarchical structure diagram of the data record directory according to an embodiment of the present invention.

[0043] Figure 7 This is a screenshot of the parsing software in an embodiment of the present invention.

[0044] Figure 8 This is a screenshot of the Lua parsing script in an embodiment of the present invention. Detailed Implementation

[0045] The purpose of this invention is to provide a method for managing multi-source, massive radar data. It designs a caching structure that can complete real-time management and recording of multi-source, massive radar data. It introduces Lua script programming, which eliminates the need to modify the relevant code of the compilation software. Plaintext parsing can be completed through script configuration, making it more suitable for the management of radar detection intelligence in complex data interaction scenarios.

[0046] To facilitate understanding of this application, a more complete description will be provided below with reference to the accompanying drawings, which illustrate embodiments of the present application. However, the present application can be implemented in many different forms and is not limited to the embodiments described herein. Rather, these embodiments are provided so that the disclosure of this application will be thorough and complete.

[0047] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application.

[0048] It is understood that the terms “first,” “second,” etc., used in this application may be used herein to describe various elements, but these elements are not limited by these terms. These terms are only used to distinguish one element from another.

[0049] Spatial relation terms such as “below,” “under,” “below,” “under,” “above,” “above,” etc., are used herein to describe the relationship between one element or feature shown in the figure and other elements or features. It should be understood that, in addition to the orientation shown in the figure, spatial relation terms also include different orientations of the device in use and operation. For example, if the device in the figure is flipped, the element or feature described as “below,” “under,” or “below” will be oriented “above” the other element or feature. Therefore, the exemplary terms “below” and “under” can include both above and below orientations. Furthermore, the device may also include other orientations (e.g., rotated 90 degrees or other orientations), and the spatial descriptive terms used herein will be interpreted accordingly.

[0050] It should be noted that when one element is considered to be "connected" to another element, it can be directly connected to the other element or connected to the other element through an intermediary element. Furthermore, in the following embodiments, "connection" should be understood as "electrical connection," "communication connection," etc., if there is transmission of electrical signals or data between the connected objects.

[0051] When used herein, the singular forms of “a,” “an,” and “the” may also include the plural forms unless the context clearly indicates otherwise. It should also be understood that the terms “comprising / including” or “having,” etc., specify the presence of the stated features, wholes, steps, operations, components, parts, or combinations thereof, but do not preclude the possibility of the presence or addition of one or more other features, wholes, steps, operations, components, parts, or combinations thereof. Meanwhile, the term “and / or” as used in this specification includes any and all combinations of the associated listed items.

[0052] like Figure 1 and Figure 2 As shown, this embodiment proposes a method for managing multi-source, massive radar data. By designing a cache structure and introducing script programming, it can flexibly realize the splicing, saving, and parsing of multi-source, massive radar data, providing basic support for rapidly acquiring radar intelligence. Figure 1 As shown, the specific steps include:

[0053] Step 1, Multi-source data caching (including various types of network data): Receive and parse track data (target RCS, one-dimensional image), recognition results, early warning information, etc., and perform caching processing; the above data is based on the track, and when the target track disappears (lost status or manual batch cancellation), the corresponding batch number cache is cleared and the parsing and caching of the corresponding data packets are stopped;

[0054] Based on map and array structures, considering the impact of array loops, target track loss, manual batch cancellation, etc., and taking into account the temporal order of track, identification information, and early warning information, the caching logic is designed and a data access interface is provided.

[0055] Based on Qt graphical interface technology, it supports manual online intervention in program caching and enables the clearing of historical caches during network storm scenarios;

[0056] Specifically, the following steps are included:

[0057] Step 1.1 Data Access: Provide an access interface and perform data retrieval based on the data identifier (target track batch identifier):

[0058] Step 1.2 If the target data exists, proceed to step 1.5;

[0059] Step 1.3 If the target data to be retrieved does not exist and the cache is full, clear the oldest historical data and proceed to step 1.5;

[0060] Step 1.4: If the target data to be retrieved does not exist and the cache is not full, proceed directly to Step 1.5;

[0061] Step 1.5: Update the map, which stores the position of the target data corresponding to the data identifier in the array. Proceed to Step 1.6.

[0062] Step 1.6: Based on the position of the target data in the array returned by the map, write the target data into the array in the buffer.

[0063] Step 2, Data Recording (File Writing): In response to the interface control, the data transmitted by the network sending and receiving thread is stored in the form of a binary file on the local hard drive.

[0064] The storage architecture is designed based on the needs of test review, allowing operators to accurately control information such as the start and end times of file records and data transmission and reception addresses; it also supports operators controlling the start and end of data records by checking boxes (e.g., ...). Figure 4 and Figure 5 As shown), and considering the need for post-experiment data analysis and review, the directory structure of the network data is three-level: the first level is datarecord, the second level is recv and report, and the third level includes EY, RaDadar, etc. This three-level structure of the network data enables the writing of binary data files to the hard drive, such as... Figure 6 As shown.

[0065] To address the need for multi-threaded data operations, a locking mechanism is added for thread synchronization to ensure software stability; for example... Figure 2 As shown, the specific steps include:

[0066] Step 2.1: Receive network data such as track data (target RCS, one-dimensional image), recognition results, and early warning information;

[0067] Step 2.2: Determine if the data buffer is full. If it is full, discard the data. If it is not full, record the thread, write the data to the binary file, and divide the binary file path based on the data source.

[0068] Step 3, Data Parsing: Receive the absolute path of the binary file from Step 2, and according to the protocol, parse the plaintext of various messages and write them to the file; for example... Figure 3 As shown, it includes the following steps:

[0069] Step 3.1 Determine if the binary file is corrupted. If the file is corrupted, proceed to step 3.2; if the file is not corrupted, proceed to step 3.3.

[0070] Step 3.2 failed to resolve, so the execution process of step 3 ends.

[0071] Step 3.3 Read the binary file to obtain the raw network packets, get the packet identifier, and proceed to step 3.4;

[0072] Step 3.4 Determine if an adaptation script exists. If it exists, proceed to step 3.5. If it does not exist, output the log and return to step 3.3.

[0073] Step 3.5 Plaintext parsing: Determine if the binary file has been completely read. If yes, end Step 3; otherwise, return to Step 3.3 and continue reading the binary file until all binary files have been read.

[0074] Considering the need for flexible adaptation of parsing logic in scenarios involving changes in network packets, such as the addition of new packet types or revisions to data item definitions, plaintext parsing of binary data files is implemented based on Lua scripts. Figure 7 Screenshots for analysis software. Figure 8 Screenshot of a Lua parsing script.

[0075] Considering the complex and ever-changing real-world scenarios, the parsing logic is separated from the C++ program and implemented through interaction between C++ and Lua scripts, thereby improving code flexibility and versatility.

[0076] This embodiment also provides a multi-source massive radar data management system, including a multi-source data caching module, a file writing module, and a data parsing module. The multi-source data caching module, file writing module, and data parsing module implement radar data management based on the above method.

[0077] Compared with the prior art, the present invention has the following advantages:

[0078] (1) On the basis of the traditional network data management method of display and control software, a multi-source data aggregation and caching mechanism is added, which is conducive to the unified management of target information;

[0079] (2) The cache logic is designed with map + fixed-length array. Considering the loss of track, batch cancellation and the time sequence of each network data, the program crashes due to frequent memory allocation in network storm scenarios, while combining the advantages of map lookup with the convenience of array access, thus taking into account the cache efficiency.

[0080] (3) The data recording method designed for the operator's test review needs is in line with the actual combat situation and is conducive to the operator's accurate control of information such as data recording time and data source;

[0081] (4) The parsing function based on Lua scripts can perfectly adapt to multiple scenarios such as adding message types and revising message data item definitions without changing the parsing program, which greatly facilitates the parsing and management of plaintext data.

[0082] The above description is only a preferred embodiment of the present invention and is 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 within the protection scope of the present invention.

Claims

1. A method for managing multi-source massive radar data, characterized in that, Includes the following steps: Multi-source data caching: Receives various types of data and performs caching processing; Multi-source data caching specifically includes the following steps: Step 1.1 Provide a data access interface and perform data retrieval based on data identifiers: Step 1.2 If the target data exists, proceed to step 1.5; Step 1.3 If the target data to be retrieved does not exist and the cache is full, clear the oldest historical data and proceed to step 1.5; Step 1.4: If the target data to be retrieved does not exist and the cache is not full, proceed directly to Step 1.5; Step 1.5: Update the map, which stores the position of the target data corresponding to the data identifier in the array. Proceed to Step 1.

6. Step 1.6: Based on the position of the target data in the array returned by the map, write the target data into the array in the buffer area; File writing: Receive various types of data and store them on the local hard drive in binary file format; Data parsing: Receive the absolute path of the binary file after the file is written, and complete the plaintext parsing of various messages according to the protocol. The data parsing specifically includes the following steps: Step 3.1: Determine if the binary file is corrupted. If the file is corrupted, proceed to step 3.2; if the file is not corrupted, proceed to step 3.

3. Step 3.2: Parsing failed, ending the data parsing process; Step 3.3: Read the binary file to obtain the original network packets, get the packet identifier, and proceed to step 3.4; Step 3.4: Determine if an adaptation script exists. If it exists, proceed to step 3.

5. If it does not exist, output the log and return to step 3.

3. Step 3.5: Plaintext parsing. Determine if the binary file has been completely read. If yes, end the data parsing process. If not, return to step 3.3 and continue reading the binary file until all binary files have been read.

2. The multi-source massive radar data management method according to claim 1, characterized in that, Multi-source data caching, file writing, and data parsing are implemented using multi-threading, with a locking mechanism added for thread synchronization.

3. The multi-source massive radar data management method according to claim 1, characterized in that, The received data is based on the flight track. When the target flight track disappears, the corresponding batch number cache is cleared and the parsing and caching of the corresponding data packets are stopped.

4. The multi-source massive radar data management method according to claim 1, characterized in that, The received data includes flight track data, identification results, and early warning information.

5. The multi-source massive radar data management method according to claim 1, characterized in that, The data identifier is the target track batch number identifier.

6. The multi-source massive radar data management method according to claim 1, characterized in that, The file writing process specifically includes the following steps: Receive network data; Determine if the data buffer is full. If it is full, discard the data. If it is not full, record the thread, write the data to the binary file, and divide the binary file path based on the data source.

7. The multi-source massive radar data management method according to claim 6, characterized in that, It supports controlling the start and end of data recording by checking boxes; the directory structure of the network data is three-level, with the first level being datarecord, the second level being recv and report, and the third level including EY and RaDadar. The three-level structure of the network data enables the writing of binary files to the hard disk.

8. The multi-source massive radar data management method according to claim 1, characterized in that, To address the need for flexible parsing logic to adapt to changes in network packets, plaintext parsing of binary files is performed using Lua scripts. Scenarios involving changes in network packets include adding new packet types and revising data item definitions.

9. A multi-source massive radar data management system, characterized in that, It includes a multi-source data caching module, a file writing module, and a data parsing module. The multi-source data caching module, the file writing module, and the data parsing module implement radar data management based on the method described in any one of claims 1-8.

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