Real-time monitoring method for command and control of target equipment

Abstract

The invention discloses a method for real-time monitoring of command and control of target equipment. The method comprises the following steps: step 1, acquiring command and control communication voice data of the target equipment; step 2, identifying first practical key data and second practical key data in the command and control communication voice data in the step 1; 3, respectively establishing a first time sequence and a second time sequence on the time axis according to the first practical key data and the second practical key data in the step 2; and step 4, performing time warping on the first time sequence and the second time sequence so as to calculate the similarity between the two time sequences.

Description

Technical Field

[0001] This invention relates to the field of data analysis, and more specifically to a method for collecting and analyzing data specific to command and control communications. Background Technology

[0002] During the testing process, the data acquisition work itself can affect the progress of the test. At the same time, there are a lot of radio voice information from the test site that are not processed and analyzed. Therefore, the method provided by this invention, which analyzes and processes voice information to comprehensively analyze the equipment command and control capabilities in scenarios where test data cannot be directly obtained, is of great significance. Summary of the Invention

[0003] Therefore, in order to overcome the above-mentioned defects, the present invention provides a method for real-time monitoring of target equipment command and control, characterized by comprising the following steps: Step 1: Obtain the command and control communication voice data of the target equipment; Step 2: Identify the first and second practical key data in the command and control communication voice data from Step 1; Step 3: Establish a first time series and a second time series on the time axis based on the first practical key data and the second practical key data from Step 2, respectively; Step 4: Perform time normalization on the first and second time series in order to calculate the similarity between the two time series.

[0004] Preferably, the time warping refers to extending and shortening the first time series and the second time series.

[0005] Preferably, the first practical key data and the second practical key data respectively include radio voice data, training command voice, and tactical instructions.

[0006] Preferably, the calculation of the similarity includes the following steps: Step 4-1, using the first time series of length n The second time series of length m Establish matrix elements ,in This represents the distance calculation function; Step 4-2, search in matrix D from arrive The shortest path; Step 4-3, extract from matrix D... arrive The shortest path is used as the similarity between sequences Q and C, i.e. .

[0007] Preferably, the method further includes step 5, reading the voice display model data constructed in the database, and replaying the real-time situation of inter-equipment command and control communication in a graphical manner to analyze the inter-equipment communication quality, communication stability, accuracy of combat command transmission, transmission delay, and command and control communication capabilities.

[0008] Preferably, Determining the text content of radio voice data includes the following steps: S21. Determine the tactical instructions and training commands involved in the test; S22. Determine the radio voice data collected and recovered during the test; S23. Process the collected voice data according to the dynamic time warping algorithm and convert it into text information; S24. Based on the sorted text information and the personnel, equipment and vehicle allocation rules during the experiment, sort and organize the vehicle and personnel voices of each team according to the timeline to construct a voice display model.

[0009] Preferably, the voice display model data constructed after speech recognition is stored in a database. Attached Figure Description

[0010] Figure 1 A flowchart is shown illustrating a method for real-time monitoring of target equipment command and control according to a preferred embodiment of the present invention. Figure 2 The matrix search direction is briefly shown. Detailed Implementation

[0011] like Figure 1 As shown, it includes the following steps: S1. Collect radio voice data according to the test subjects; S2. Record tactical instructions and training commands based on the test subjects; S3. Extract audio text and other information from radio voice data; S4. Construct a model to store voice information; S5. Graphical playback of video feed; S6. Analyze the command and control capabilities of the equipment.

[0012] It is necessary to install radio voice equipment to collect command and control communication data.

[0013] We analyze equipment radio voice data by collecting a large amount of tactical command voice data and test training voice commands. Based on the audio information, we compare the data and use big data intelligent analysis methods to match and identify specific data frames and the corresponding text command information or daily training commands based on changes in these frames. We transform the voice recognition problem into a similarity measurement calculation between two time series. By extending and shortening time series of different lengths in the voice information and performing time normalization on the speech data, we calculate the similarity between the two time series. The specific implementation method is as follows: There are two time series, one for each of the collected radio voice data. and tactical instructions Given two strings, Q and C, with lengths n and m respectively, the similarity between Q and C is calculated as follows: 1) Build size is Matrix D, matrix elements ,in The distance calculation function is usually represented by Euclidean distance; 2) Search in matrix D from arrive The shortest path is typically found using dynamic programming search. The location and path search direction are generally as shown in Figure 2.

[0014] 3) Transfer the contents of matrix D from... arrive The shortest path is used as the similarity between sequences Q and C, i.e. .

[0015] 4. The method according to claim 3, characterized in that determining the text content of radio voice data includes the following steps: S31. Determine the tactical instructions and training commands involved in the test; S32. Determine the radio voice data collected and recovered during the test; S33. Process the collected voice data according to the dynamic time warping algorithm and convert it into text information; S34. Based on the sorted text information and the personnel, equipment and vehicle allocation rules during the experiment, sort and organize the vehicle and personnel voices of each team according to the timeline to construct a voice display model.

[0016] The voice display model data constructed after speech recognition is stored in the database.

[0017] The system reads voice display model data built in the database and replays the real-time situation of command and control communication between equipment in a graphical way, analyzing the command and control communication capabilities such as communication quality, communication stability, accuracy of combat command transmission, and transmission latency between equipment.

[0018] The aforementioned data collection and analysis method for command and control communications involves installing radio voice acquisition equipment on command and control equipment to collect a large amount of command and control communication voice data. This data is then analyzed using big data mining techniques. Combined with troop combat instructions and test training commands, the analysis reveals the command and control communication and information transmission process during the test. By constructing a voice data display model, the flow of data information is graphically displayed, providing support for the analysis of equipment command and control capabilities.

[0019] Based on the above embodiments, a method for real-time monitoring of target equipment command and control can be further summarized, characterized by comprising the following steps: Step 1: Obtain the command and control communication voice data of the target equipment; Step 2: Identify the first and second practical key data in the command and control communication voice data from Step 1; Step 3: Establish a first time series and a second time series on the time axis based on the first practical key data and the second practical key data from Step 2, respectively; Step 4: Perform time normalization on the first and second time series in order to calculate the similarity between the two time series.

[0020] Preferably, the time warping refers to extending and shortening the first time series and the second time series.

[0021] Preferably, the first practical key data and the second practical key data respectively include radio voice data, training command voice, and tactical instructions.

[0022] Preferably, the calculation of the similarity includes the following steps: Step 4-1, using the first time series of length n and the second time series of length m Establish matrix elements ,in This represents the distance calculation function; Step 4-2, search in matrix D from arrive The shortest path; Step 4-3, extract from matrix D... arrive The shortest path is used as the similarity between sequences Q and C, i.e. .

[0023] Preferably, the method further includes step 5, reading the voice display model data constructed in the database, and replaying the real-time situation of inter-equipment command and control communication in a graphical manner to analyze the inter-equipment communication quality, communication stability, accuracy of combat command transmission, transmission delay, and command and control communication capabilities.

[0024] Preferably, Determining the text content of radio voice data includes the following steps: S21. Determine the tactical instructions and training commands involved in the test; S22. Determine the radio voice data collected and recovered during the test; S23. Process the collected voice data according to the dynamic time warping algorithm and convert it into text information; S24. Based on the sorted text information and the personnel, equipment and vehicle allocation rules during the experiment, sort and organize the vehicle and personnel voices of each team according to the timeline to construct a voice display model.

[0025] Preferably, the voice display model data constructed after speech recognition is stored in a database.

[0026] The preferred embodiments of this application have been exemplified above with the aid of the accompanying drawings. However, those skilled in the art should understand that, without exceeding the scope of protection of the appended claims, they can form new technical solutions by adding features, combining features, etc.

Claims

1. A method for target equipment command control real-time monitoring, characterized in that, The method comprises the following steps: Step 1, obtaining the command control communication voice data of the target equipment; Step 2, identifying the first and second key data in the command control communication voice data in step 1; Step 3, establishing a first time sequence and a second time sequence according to the first and second key data in step 2 on a time axis respectively; Step 4, time normalization of the first and second time sequences to calculate the similarity between the two time sequences.

2. The method for target equipment command control real-time monitoring according to claim 1, characterized in that, The time normalization refers to the extension and shortening of the first and second time sequences.

3. The method for target equipment command control real-time monitoring according to claim 2, characterized in that, The first and second key data respectively include one of radio voice data, training password voice and tactical command.

4. The method for target equipment command control real-time monitoring according to claim 3, characterized in that, The calculation of the similarity comprises the following steps: Step 4-1, by said first time series of length n and said second time series of length m establishing matrix elements wherein denotes a distance computation function; Step 4-2, search for the shortest path from to in matrix D; Step 4-3, the shortest path in matrix D from to is taken as the similarity of Q and C sequences, i.e. 。 5. The method for target equipment command control real-time monitoring according to claim 4, characterized in that, Further comprising step 5, reading the constructed voice display model data in the database, playing back the real-time situation of the inter-equipment command control communication in a graphical manner, and analyzing the inter-equipment communication quality, communication stability, combat command transmission accuracy, transmission time delay and command control communication capability.

6. The method for real-time monitoring of target equipment command control according to claim 5, wherein The judgment of the radio voice data text content comprises the following steps: S31, determining the tactical command and training password content involved in the test process; S32, determining the radio voice data collected and recovered in the test process; S33, processing the collected and recovered voice data according to the dynamic time normalization algorithm and converting it into text information; S34, according to the sorted text information, combining the personnel and equipment vehicle allocation rules in the test process, sorting and arranging the vehicle and personnel voice of each team according to the time axis, and constructing a voice display model.

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