Multi-source mass radar data management method and system

Abstract

The invention discloses a multi-source mass radar data management method and system, and the method comprises the following steps: multi-source data caching: receiving various types of data, and carrying out the caching processing; file writing: storing data transmitted by the network transceiving thread in a local hard disk in a binary file form; and data analysis: receiving a binary file absolute path after file writing, and completing plaintext analysis of various messages according to protocol agreement. According to the method, cache logic is designed through map + fixed-length arrays, track loss, batch elimination and the time sequence of network data are considered, program crash caused by frequent development of a memory in a network storm scene is avoided, meanwhile, the map search advantage and the characteristic of convenient array access are combined, and the cache efficiency is considered.

Description

Technical Field

[0001] The present invention belongs to the technical field of radar situation display and analysis, and in particular relates to a multi-source massive radar data management method and system. Background Art

[0002] The ground guidance radar is a multifunctional radar that uses microwaves to search, track and identify targets. It is mainly used for the guidance of surface-to-air missiles, air-to-air missiles and anti-ship missiles. The interaction between the operator and the guidance radar is mainly through the display control software and situation software as a bridge to realize the display of target track, identification results, system status and other information, as well as the dispatching control of radar equipment and background processing.

[0003] With the rapid development of guidance technology, radar systems are becoming more complex, and the sources and scale of radar data are increasing. In the information exchange with the superior command system, data screening and splicing are often involved, and the conventional data management model can no longer meet the actual needs. Summary of the invention

[0004] In order to solve the above problems, the present invention proposes a multi-source massive radar data management method, comprising the following steps:

[0005] Multi-source data cache: receiving various types of data and performing cache processing;

[0006] File writing: Receive various data and store them in the form of binary files on the local hard disk;

[0007] Data parsing: Receive the absolute path of the binary file after the file is written, and complete the plain text parsing of various messages according to the protocol.

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

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

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

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

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

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

[0014] Step 1.3: If the target data does not exist and the cache is full, clear the longest historical data and go 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. The map stores the position of the target data corresponding to the data identifier in the array, and proceed to step 1.6;

[0017] Step 1.6: Based on the map, the position of the target data in the array is returned and the target data is written into the array in the buffer area.

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

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

[0020] Receive network data;

[0021] Determine whether the data buffer is full. If so, discard the data. If not, record the thread, write the data into a 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 in the form of a check box; 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 and Radadadar. The three-level structure of network data is used to realize writing of binary files to the hard disk.

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

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

[0025] Step 3.2: If the parsing fails, the data parsing process ends;

[0026] Step 3.3, read the binary file to obtain the original network message, obtain the message identifier, and proceed to step 3.4;

[0027] Step 3.4: Determine whether there is an adaptation script. If so, proceed to step 3.5. If not, output the log and return to step 3.3.

[0028] Step 3.5: Plain text parsing, determine whether the binary file has been read. If so, end the data parsing execution process. If not, return to step 3.3 to continue reading the binary file until all binary files have been read.

[0029] Furthermore, considering the flexible adaptation requirements of the parsing logic when the network message changes, the plain text parsing of binary files is completed based on the Lua script; the scenarios of network message changes include the addition of message types and the revision of data item definitions.

[0030] A multi-source massive radar data management system is also provided, including a multi-source data cache module, a file writing module, and a data parsing module. The multi-source data cache module, the file writing module, and the 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 the present invention are:

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

[0034] (2) The cache logic is designed with map + fixed-length array, taking into account the track loss, batch cancellation, and the timing of each network data. This avoids program crashes caused by frequent memory allocation in network storm scenarios, while combining the advantages of map search with the convenience of array access, taking into account 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 helps the operator to accurately control information such as data recording time and data source;

[0036] (4) The parsing function based on the Lua script can achieve perfect adaptation to multiple scenarios such as adding new message types and revising the definition of message data items without changing the parsing program, which greatly facilitates the parsing and management of plain text data. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 It is a flow chart of a method according to an embodiment of the present invention.

[0038] Figure 2 4 is a flow chart of radar data recording according to an embodiment of the present invention.

[0039] Figure 3 It is a flow chart of radar data plaintext parsing according to an embodiment of the present invention.

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

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

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

[0043] Figure 7 It is a screenshot of the analysis software of the embodiment of the present invention.

[0044] Figure 8 It is a screenshot of the Lua parsing script of an embodiment of the present invention. DETAILED DESCRIPTION

[0045] The purpose of the present invention is to provide a multi-source, massive radar data management method, design a cache structure, and complete the real-time management and recording of multi-source and massive radar data; introduce Lua script programming, there is no need to modify the relevant code of the compilation software, and plain text parsing can be completed through script configuration, which is more suitable for the management of radar detection intelligence in complex data interaction scenarios.

[0046] In order to facilitate understanding of the present application, the present application will be described more fully below with reference to the relevant drawings. Embodiments of the present application are provided in the drawings. However, the present application can be implemented in many different forms and is not limited to the embodiments described herein. On the contrary, the purpose of providing these embodiments is to make the disclosure of the present application more thorough and comprehensive.

[0047] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which this application belongs. The terms used herein in the specification of this application are only for the purpose of describing specific embodiments and are not intended to limit this application.

[0048] It can be understood that the terms "first", "second", etc. used in the present application can be used in this article to describe various elements, but these elements are not limited by these terms. These terms are only used to distinguish the first element from another element.

[0049] Spatially relative terms such as "under," "beneath," "below," "under," "above," "above," and the like may be used herein to describe the relationship of an element or feature shown in the figures to other elements or features. It should be understood that, in addition to the orientations shown in the figures, spatially relative terms also include different orientations of the device in use and operation. For example, if the device in the accompanying drawings is flipped, an element or feature described as "under other elements" or "under it" or "under it" will be oriented as being "above" the other elements or features. Thus, the exemplary terms "under" and "under" may include both upper and lower orientations. In addition, the device may also include additional orientations (e.g., rotated 90 degrees or other orientations), and the spatial descriptors used herein are interpreted accordingly.

[0050] It should be noted that when an 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 intermediate element. In addition, the "connection" in the following embodiments 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 "a", "an", and "said / the" may also include plural forms, unless the context clearly indicates otherwise. It should also be understood that the terms "include / comprise" or "have" and the like specify the presence of stated features, wholes, steps, operations, components, parts, or combinations thereof, but do not exclude the possibility of the presence or addition of one or more other features, wholes, steps, operations, components, parts, or combinations thereof. At the same time, the term "and / or" used in this specification includes any and all combinations of the relevant listed items.

[0052] like Figure 1 and Figure 2 As shown, this embodiment proposes a multi-source, massive radar data management method. By designing a cache structure and introducing script programming, the splicing, storage, and analysis of multi-source, massive radar data can be flexibly realized, providing basic support for the rapid acquisition of radar intelligence. Figure 1 As shown, the specific steps include:

[0053] Step 1, multi-source data cache (including various network data): receive, analyze and cache track data (target RCS, one-dimensional image), recognition results, warning information and other data; the above data is based on the track. When the target track disappears (lost state or manual batch cancellation), clear the corresponding batch cache and stop parsing and caching the corresponding data packet;

[0054] Based on the map and array structure, the cache logic is designed considering the influence of array loop, target track loss, manual batch cancellation, etc., and the timing of track, identification information, and warning information is considered to provide a data access interface;

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

[0056] The specific steps include:

[0057] Step 1.1 Data access: Provide access interface and perform data retrieval based on data identification (target track batch number identification):

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

[0059] Step 1.3: If the target data does not exist and the cache is full, clear the longest historical data and go 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. The map stores the position of the target data corresponding to the data identifier in the array, and proceed to step 1.6;

[0062] Step 1.6: Based on the map, the position of the target data in the array is returned and the target data is written into the array in the buffer area.

[0063] Step 2, data recording (file writing): respond to the interface control and store the data transmitted by the network transceiver thread in the form of a binary file to the local hard disk.

[0064] The storage architecture is designed based on the test review requirements to facilitate operators to accurately control the file recording start time, end time, data sending and receiving address and other information; operators are supported to control the start and end of data recording in the form of checking (such as Figure 4 and Figure 5 As shown in the figure, considering the need for post-test 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, Radar, etc. The three-level structure of network data realizes the writing of binary data files to the hard disk, as shown in the figure. Figure 6 shown.

[0065] Considering the needs of multi-threaded data operations, a lock mechanism is added for thread synchronization to ensure software stability; Figure 2 As shown, the specific steps include:

[0066] Step 2.1, receiving network data such as track data (target RCS, one-dimensional image), recognition results, warning information, etc.;

[0067] Step 2.2, determine whether the data buffer is full. If it is full, discard the data. If it is not full, record the thread, write the data into a binary file, and divide the binary file path based on the data source.

[0068] Step 3, data analysis: Receive the absolute path of the binary file in step 2, complete the plain text analysis of various messages according to the protocol agreement and write them into the file; Figure 3 As shown, the following steps are included:

[0069] Step 3.1 determines whether the binary file is damaged. If the file is damaged, proceed to step 3.2. If the file is not damaged, proceed to step 3.3.

[0070] Step 3.2 parsing fails, and the execution process of step 3 ends;

[0071] Step 3.3: Read the binary file to obtain the original network message, obtain the message identifier, and proceed to step 3.4;

[0072] Step 3.4 determines whether there is an adaptation script. If so, proceed to step 3.5. If not, output the log and return to step 3.3.

[0073] Step 3.5: Plain text parsing to determine whether the binary file has been read. If so, end step 3. If not, return to step 3.3 to continue reading the binary file until all binary files have been read.

[0074] Considering the changes in network messages, such as the addition of new message types and the revision of data item definitions, the parsing logic is flexibly adapted to meet the needs, and the plain text parsing of binary data files is completed based on Lua scripts. Figure 7 To analyze the software screenshots, Figure 8 Take a screenshot of the Lua parsing script.

[0075] Taking into account the complex and changeable actual scenarios of the protocol, the parsing logic is separated from the C++ program, and the parsing function is implemented through the interaction between C++ and Lua scripts to improve the flexibility and universality of the code.

[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, the file writing module, and the 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) Based on the traditional display and control software network data management method, a multi-source data aggregation and caching mechanism is added to facilitate the unified management of target information;

[0079] (2) The cache logic is designed with map + fixed-length array, taking into account the track loss, batch cancellation, and the timing of each network data. This avoids program crashes caused by frequent memory allocation in network storm scenarios, while combining the advantages of map search with the convenience of array access, taking into account 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 helps the operator to accurately control information such as data recording time and data source;

[0081] (4) The parsing function based on the Lua script can achieve perfect adaptation to multiple scenarios such as adding new message types and revising the definition of message data items without changing the parsing program, which greatly facilitates the parsing and management of plain text 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 principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A multi-source massive radar data management method, characterized in that: The following steps are involved: Multi-source data cache: receiving various types of data and performing cache processing; File writing: Receive various types of data and store them in the form of binary files on the local hard disk; Data parsing: Receive the absolute path of the binary file after the file is written, and complete the plain text parsing of various messages according to the protocol.

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 through multi-threading, and a lock mechanism is 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 track. When the target track disappears, the corresponding batch number cache is cleared and the parsing and caching of the corresponding data packet is stopped.

4. The multi-source massive radar data management method according to claim 1, characterized in that: The various types of data received include track data, identification results, and warning information.

5. The multi-source massive radar data management method according to claim 1, characterized in that: Multi-source data caching specifically includes the following steps: Step 1.1 Provide data access interface and perform data retrieval based on data identification: Step 1.2 If the retrieved target data exists, proceed to step 1.5; Step 1.3: If the target data does not exist and the cache is full, clear the longest historical data and go 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. The map stores the position of the target data corresponding to the data identifier in the array, and proceed to step 1.6; Step 1.6: Based on the map, the position of the target data in the array is returned and the target data is written into the array in the buffer area.

6. 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.

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

8. The multi-source massive radar data management method according to claim 7, characterized in that: It supports controlling the start and end of data recording in the form of checking; 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 and Radadadar. The three-level structure of network data is used to realize writing of binary files to the hard disk.

9. The multi-source massive radar data management method according to claim 1, characterized in that: The data analysis specifically includes the following steps: Step 3.1: Determine whether the binary file is damaged. If the file is damaged, proceed to step 3.2; if the file is not damaged, proceed to step 3.

3. Step 3.2: If the parsing fails, the data parsing process ends; Step 3.3, read the binary file to obtain the original network message, obtain the message identifier, and proceed to step 3.4; Step 3.4: Determine whether there is an adaptation script. If so, proceed to step 3.

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

3. Step 3.5: Plain text parsing, determine whether the binary file has been read. If so, end the data parsing execution process. If not, return to step 3.3 to continue reading the binary file until all binary files have been read.

10. The multi-source massive radar data management method according to claim 1, characterized in that: Considering the flexible adaptation requirements of the parsing logic when network messages change, the plain text parsing of binary files is completed based on Lua scripts; the scenarios of network message changes include the addition of new message types and the revision of data item definitions.

11. A multi-source massive radar data management system, characterized in that: It includes a multi-source data cache module, a file writing module, and a data parsing module. The multi-source data cache module, the file writing module, and the data parsing module realize radar data management based on the method described in any one of claims 1 to 10.

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