Method and system for identifying a stationary communication device based on a detection code

Abstract

The application provides a bearing stationary communication equipment identification method and system based on a detection code technology, comprising the following steps: S1, detecting communication equipment information, and giving bearing information according to the frame code equipment working state; S2, calculating a bearing distribution peak value measure of the communication equipment, and judging whether the bearing stationary setting is met; S3, calculating a bearing direction and distribution skewness measure of the communication equipment; and S4, correcting the bearing direction according to the bearing distribution of the communication equipment. The application considers multi-dimensional factors such as a time domain, a space domain and a data characteristic domain, uses the time characteristics and the bearing statistical analysis characteristics of the received communication equipment signals to analyze the bearing distribution of the communication equipment signals, and can more accurately identify the bearing stationary state of the communication equipment and help the monitoring personnel better understand the activity of the communication equipment.

Description

Technical Field

[0001] This invention relates to the field of code detection data analysis technology, and more specifically, to a system and method for identifying directional stationary communication devices based on code detection technology. Background Technology

[0002] A detection device is used to monitor and listen to communication devices. This type of device is commonly used in technologies that monitor and listen to radio communications, such as radio broadcasts, mobile phones, and satellite communications. By capturing and analyzing communication signals, detection devices can identify the location, identity, and activity of communication devices. However, traditional detection devices can only determine the range of the information source, such as a fan-shaped area with an angle of 60° and a radius of 5 kilometers, making it difficult to pinpoint the location of the communication device. To address this problem, this invention proposes a novel azimuth-based stationary communication device discrimination technology. This technology is based on a directional, follow-up detection device that can provide omnidirectional coverage of communication devices within the monitoring area and possesses higher azimuth positioning accuracy.

[0003] Patent document CN203279185U (application number: 201320349745.X) discloses an air-to-ground mobile phone communication and number identification and tracking system, including: an emergency command vehicle, a roof platform, an equipment cabinet, and a power supply; the equipment cabinet and the power supply are respectively installed in the compartment of the emergency command vehicle; a simulated base station, including an antenna and a base station body, the base station body is installed in the equipment cabinet, the antenna is installed on the roof platform and electrically connected to the base station body, and the base station body is electrically connected to the power supply; a code detection device, a positioning device, a listening device, a target ringing device, and a text message interception and reply device are respectively installed in the equipment cabinet and electrically connected to the base station body and the power supply; a server; and input / output devices. Summary of the Invention

[0004] To address the shortcomings of existing technologies, the purpose of this invention is to provide a method and system for identifying directional stationary communication devices based on code detection technology.

[0005] A method for identifying a stationary communication device based on code detection technology according to the present invention includes:

[0006] Step S1: Detect communication device information and assign azimuth information based on the frame code device's operating status;

[0007] Step S2: Calculate the peak value of the azimuth distribution of the communication equipment and determine whether the azimuth static setting is met;

[0008] Step S3: Calculate the orientation and distribution skewness measures of the communication equipment;

[0009] Step S4: Correct the orientation based on the location distribution of the communication equipment.

[0010] Preferably, in step S1:

[0011] The directional tracking detection device performs all-round monitoring and data collection of the deployment location monitoring area, assigns azimuth information to the collected communication device data, provides azimuth reference values ​​for each piece of communication device information, and identifies stationary communication devices and their azimuth direction based on the azimuth distribution characteristics of each communication device. Azimuth stationary means that the azimuth change range of the communication device or other target location is less than the main beam width of the detection device within a preset time; azimuth direction refers to the location of the communication device in a stationary state with the highest probability.

[0012] After the site is deployed, the directional tracking detection device can monitor the monitoring area in all directions. The detection device follows the set search and patrol route in a directional manner, detects communication devices during the search and patrol, collects information from the communication devices, and obtains the current orientation of the frame code device when it collects data from the communication devices. This information is then integrated with the data from the communication devices and sent back to the system database for storage.

[0013] Preferably, in step S2:

[0014] After acquiring communication equipment information data, the location of the communication equipment is statistically analyzed to determine its directional distribution. Kurtosis is used as the criterion for determining the directional static data. Based on the kurtosis measurement value, it is determined whether the directional distribution of the communication equipment is in a flat or peaked state. The kurtosis measurement formula is as follows:

[0015]

[0016] Where K is a measure of the azimuth distribution kurtosis, and n is the total number of detected communication device information data. Here, s is the azimuth mean, s is the azimuth standard deviation, and x is the azimuth i This represents the azimuth value of the data collected by each detected communication device;

[0017] Depending on the azimuth detection accuracy achievable by different detection devices, K can take different values ​​to measure whether the communication device is in a stationary azimuth state. When the calculated result of K is greater than the threshold K... th If the azimuth is constant, then it is stationary; otherwise, it is not stationary. th Configure according to project requirements.

[0018] Preferably, in step S3:

[0019] After determining that the communication equipment is a stationary communication device, the azimuth direction is calculated based on the data collected by the communication equipment; the mathematical expectation of the azimuth distribution is obtained as the azimuth direction (pnting) of the communication equipment. x The expression is:

[0020] pnting x =E(x)

[0021] The skewness coefficient is used as a measure of the asymmetry in the data distribution. The formula for calculating the skewness coefficient is:

[0022]

[0023] Where SK is the skewness coefficient, and n is the total number of detected communication device information data. denoted as mean, and s as standard deviation of azimuth;

[0024] SK<0 indicates that the data is left-biased and the orientation needs to be corrected to the right. SK=0 indicates that there is no bias and the orientation does not need to be corrected. SK>0 indicates that the data is right-biased and the orientation needs to be corrected to the left.

[0025] Preferably, in step S4:

[0026] When the absolute value of SK is less than the preset value, the data is unbiased and there is no need to correct the orientation.

[0027] When the absolute value of SK is greater than the set value, the azimuth direction of the left and right deviation data is corrected accordingly to the right and left, respectively, with the correction coefficient σ being...

[0028] σ=f(SK)

[0029] Where f(SK) is the calculation function of the correction coefficient σ, and the calculation function is selected as linear or nonlinear depending on the tolerance for data deviation.

[0030] A location-based stationary communication device identification system based on code detection technology, according to the present invention, includes:

[0031] Module M1: Detects communication equipment information and assigns azimuth information based on the frame code device's operating status;

[0032] Module M2: Calculates the peak value of the azimuth distribution of the communication equipment and determines whether the azimuth stationary setting is met;

[0033] Module M3: Calculates the orientation and distribution skewness measures of communication equipment;

[0034] Module M4: Corrects the orientation based on the location distribution of communication equipment.

[0035] Preferably, in module M1:

[0036] The directional tracking detection device performs all-round monitoring and data collection of the deployment location monitoring area, assigns azimuth information to the collected communication device data, provides azimuth reference values ​​for each piece of communication device information, and identifies stationary communication devices and their azimuth direction based on the azimuth distribution characteristics of each communication device. Azimuth stationary means that the azimuth change range of the communication device or other target location is less than the main beam width of the detection device within a preset time; azimuth direction refers to the location of the communication device in a stationary state with the highest probability.

[0037] After the site is deployed, the directional tracking detection device can monitor the monitoring area in all directions. The detection device follows the set search and patrol route in a directional manner, detects communication devices during the search and patrol, collects information from the communication devices, and obtains the current orientation of the frame code device when it collects data from the communication devices. This information is then integrated with the data from the communication devices and sent back to the system database for storage.

[0038] Preferably, in module M2:

[0039] After acquiring communication equipment information data, the location of the communication equipment is statistically analyzed to determine its directional distribution. Kurtosis is used as the criterion for determining the directional static data. Based on the kurtosis measurement value, it is determined whether the directional distribution of the communication equipment is in a flat or peaked state. The kurtosis measurement formula is as follows:

[0040]

[0041] Where K is a measure of the azimuth distribution kurtosis, and n is the total number of detected communication device information data. Here, s is the azimuth mean, s is the azimuth standard deviation, and x is the azimuth i This represents the azimuth value of the data collected by each detected communication device;

[0042] Depending on the azimuth detection accuracy achievable by different detection devices, K can take different values ​​to measure whether the communication device is in a stationary azimuth state. When the calculated result of K is greater than the threshold K... th If the azimuth is constant, then it is stationary; otherwise, it is not stationary. th Configure according to project requirements.

[0043] Preferably, in module M3:

[0044] After determining that the communication equipment is a stationary communication device, the azimuth direction is calculated based on the data collected by the communication equipment; the mathematical expectation of the azimuth distribution is obtained as the azimuth direction (pnting) of the communication equipment. x The expression is:

[0045] pnting x =E(x)

[0046] The skewness coefficient is used as a measure of the asymmetry in the data distribution. The formula for calculating the skewness coefficient is:

[0047]

[0048] Where SK is the skewness coefficient, and n is the total number of detected communication device information data. denoted as mean, and s as standard deviation of azimuth;

[0049] SK<0 indicates that the data is left-biased and the orientation needs to be corrected to the right. SK=0 indicates that there is no bias and the orientation does not need to be corrected. SK>0 indicates that the data is right-biased and the orientation needs to be corrected to the left.

[0050] Preferably, in module M4:

[0051] When the absolute value of SK is less than the preset value, the data is unbiased and there is no need to correct the orientation.

[0052] When the absolute value of SK is greater than the set value, the azimuth direction of the left and right deviation data is corrected accordingly to the right and left, respectively, with the correction coefficient σ being...

[0053] σ=f(SK)

[0054] Where f(SK) is the calculation function of the correction coefficient σ, and the calculation function is selected as linear or nonlinear depending on the tolerance for data deviation.

[0055] Compared with the prior art, the present invention has the following beneficial effects:

[0056] 1. This invention analyzes the directional distribution of communication equipment signals by considering multiple dimensions such as time domain, spatial domain, and data feature domain, and by utilizing the time characteristics and directional statistical analysis characteristics of the received communication equipment signals.

[0057] 2. This invention can more accurately identify the stationary state of communication equipment and help monitoring personnel better understand the activity of communication equipment.

[0058] 3. This invention has a wide range of applications, such as in the military and security fields, to achieve better monitoring and reconnaissance results;

[0059] 4. This invention uses statistical principles and data kurtosis and skewness to identify stationary directional codes and obtain directional pointing data with high reliability. Attached Figure Description

[0060] Other features, objects, and advantages of the present invention will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings:

[0061] Figure 1 This is a schematic diagram showing the azimuth distribution of stationary communication equipment.

[0062] Figure 2 Flowchart for identifying stationary communication devices;

[0063] Figure 3 A schematic diagram of the kurtosis of the azimuth distribution of communication equipment;

[0064] Figure 4 This is a schematic diagram showing the skewed distribution of communication equipment. Detailed Implementation

[0065] The present invention will now be described in detail with reference to specific embodiments. These embodiments will help those skilled in the art to further understand the present invention, but do not limit the invention in any way. It should be noted that those skilled in the art can make several changes and improvements without departing from the concept of the present invention. These all fall within the protection scope of the present invention.

[0066] Example 1:

[0067] This invention provides a system and method for identifying stationary communication devices based on code detection technology. Stationary location refers to a situation where the azimuth of a communication device or other target changes within a certain timeframe, with the main range of change being less than the main beamwidth of the code detection device. This invention is based on a directional, servo-controlled code detection device, which possesses omnidirectional monitoring capabilities with pan-tilt-zoom rotation and higher azimuth detection accuracy. It can monitor and listen to radio communications, including radio broadcasts, mobile phones, and satellite communications. When monitoring communication devices, the code detection device assigns azimuth information to the detected communication device signal data. In terms of data representation, the azimuth distribution of stationary serial codes exhibits significant convergence. This invention, through the azimuth distribution of communication device signals and utilizing mathematical statistics techniques, provides an effective system and method for identifying stationary communication devices and indicates the azimuth direction of the communication device. Identification of stationary communication devices can effectively classify the location of the communication device, and in cases where distance information is ambiguous, can further narrow down the range of the communication device's location, providing strong support for subsequent data processing.

[0068] According to the present invention, a method for identifying stationary communication devices based on code detection technology is provided, such as... Figures 1-4 As shown, it includes:

[0069] Step S1: Detect communication device information and assign azimuth information based on the frame code device's operating status;

[0070] Specifically, in step S1:

[0071] The directional tracking detection device performs all-round monitoring and data collection of the deployment location monitoring area, assigns azimuth information to the collected communication device data, provides azimuth reference values ​​for each piece of communication device information, and identifies stationary communication devices and their azimuth direction based on the azimuth distribution characteristics of each communication device. Azimuth stationary means that the azimuth change range of the communication device or other target location is less than the main beam width of the detection device within a preset time; azimuth direction refers to the location of the communication device in a stationary state with the highest probability.

[0072] After the site is deployed, the directional tracking detection device can monitor the monitoring area in all directions. The detection device follows the set search and patrol route in a directional manner, detects communication devices during the search and patrol, collects information from the communication devices, and obtains the current orientation of the frame code device when it collects data from the communication devices. This information is then integrated with the data from the communication devices and sent back to the system database for storage.

[0073] Step S2: Calculate the peak value of the azimuth distribution of the communication equipment and determine whether the azimuth static setting is met;

[0074] Specifically, in step S2:

[0075] After acquiring communication equipment information data, the location of the communication equipment is statistically analyzed to determine its directional distribution. Kurtosis is used as the criterion for determining the directional static data. Based on the kurtosis measurement value, it is determined whether the directional distribution of the communication equipment is in a flat or peaked state. The kurtosis measurement formula is as follows:

[0076]

[0077] Where K is a measure of the azimuth distribution kurtosis, and n is the total number of detected communication device information data. Here, s is the azimuth mean, s is the azimuth standard deviation, and x is the azimuth i This represents the azimuth value of the data collected by each detected communication device;

[0078] Depending on the azimuth detection accuracy achievable by different detection devices, K can take different values ​​to measure whether the communication device is in a stationary azimuth state. When the calculated result of K is greater than the threshold K... th If the azimuth is constant, then it is stationary; otherwise, it is not stationary. th Configure according to project requirements.

[0079] Step S3: Calculate the orientation and distribution skewness measures of the communication equipment;

[0080] Specifically, in step S3:

[0081] After determining that the communication equipment is a stationary communication device, the azimuth direction is calculated based on the data collected by the communication equipment; the mathematical expectation of the azimuth distribution is obtained as the azimuth direction (pnting) of the communication equipment. x The expression is:

[0082] pnting x =E(x)

[0083] The skewness coefficient is used as a measure of the asymmetry in the data distribution. The formula for calculating the skewness coefficient is:

[0084]

[0085] Where SK is the skewness coefficient, and n is the total number of detected communication device information data. denoted as mean, and s as standard deviation of azimuth;

[0086] SK<0 indicates that the data is left-biased and the orientation needs to be corrected to the right. SK=0 indicates that there is no bias and the orientation does not need to be corrected. SK>0 indicates that the data is right-biased and the orientation needs to be corrected to the left.

[0087] Step S4: Correct the orientation based on the location distribution of the communication equipment.

[0088] Specifically, in step S4:

[0089] When the absolute value of SK is less than the preset value, the data is unbiased and there is no need to correct the orientation.

[0090] When the absolute value of SK is greater than the set value, the azimuth direction of the left and right deviation data is corrected accordingly to the right and left, respectively, with the correction coefficient σ being...

[0091] σ=f(SK)

[0092] Where f(SK) is the calculation function of the correction coefficient σ, and the calculation function is selected as linear or nonlinear depending on the tolerance for data deviation.

[0093] Example 2:

[0094] Example 2 is a preferred example of Example 1, and is used to illustrate the present invention in more detail.

[0095] The present invention also provides a location-based stationary communication device identification system based on code detection technology. The location-based stationary communication device identification system based on code detection technology can be implemented by executing the process steps of the location-based stationary communication device identification method based on code detection technology. That is, those skilled in the art can understand the location-based stationary communication device identification method based on code detection technology as a preferred embodiment of the location-based stationary communication device identification system based on code detection technology.

[0096] A location-based stationary communication device identification system based on code detection technology, according to the present invention, includes:

[0097] Module M1: Detects communication equipment information and assigns azimuth information based on the frame code device's operating status;

[0098] Specifically, in module M1:

[0099] The directional tracking detection device performs all-round monitoring and data collection of the deployment location monitoring area, assigns azimuth information to the collected communication device data, provides azimuth reference values ​​for each piece of communication device information, and identifies stationary communication devices and their azimuth direction based on the azimuth distribution characteristics of each communication device. Azimuth stationary means that the azimuth change range of the communication device or other target location is less than the main beam width of the detection device within a preset time; azimuth direction refers to the location of the communication device in a stationary state with the highest probability.

[0100] After the site is deployed, the directional tracking detection device can monitor the monitoring area in all directions. The detection device follows the set search and patrol route in a directional manner, detects communication devices during the search and patrol, collects information from the communication devices, and obtains the current orientation of the frame code device when it collects data from the communication devices. This information is then integrated with the data from the communication devices and sent back to the system database for storage.

[0101] Module M2: Calculates the peak value of the azimuth distribution of the communication equipment and determines whether the azimuth stationary setting is met;

[0102] Specifically, in module M2:

[0103] After acquiring communication equipment information data, the location of the communication equipment is statistically analyzed to determine its directional distribution. Kurtosis is used as the criterion for determining the directional static data. Based on the kurtosis measurement value, it is determined whether the directional distribution of the communication equipment is in a flat or peaked state. The kurtosis measurement formula is as follows:

[0104]

[0105] Where K is a measure of the azimuth distribution kurtosis, and n is the total number of detected communication device information data. Here, s is the azimuth mean, s is the azimuth standard deviation, and x is the azimuth i This represents the azimuth value of the data collected by each detected communication device;

[0106] Depending on the azimuth detection accuracy achievable by different detection devices, K can take different values ​​to measure whether the communication device is in a stationary azimuth state. When the calculated result of K is greater than the threshold K... th If the azimuth is constant, then it is stationary; otherwise, it is not stationary. th Configure according to project requirements.

[0107] Module M3: Calculates the orientation and distribution skewness measures of communication equipment;

[0108] Specifically, in module M3:

[0109] After determining that the communication equipment is a stationary communication device, the azimuth direction is calculated based on the data collected by the communication equipment; the mathematical expectation of the azimuth distribution is obtained as the azimuth direction (pnting) of the communication equipment. x The expression is:

[0110] pnting x =E(x)

[0111] The skewness coefficient is used as a measure of the asymmetry in the data distribution. The formula for calculating the skewness coefficient is:

[0112]

[0113] Where SK is the skewness coefficient, and n is the total number of detected communication device information data. denoted as mean, and s as standard deviation of azimuth;

[0114] SK<0 indicates that the data is left-biased and the orientation needs to be corrected to the right. SK=0 indicates that there is no bias and the orientation does not need to be corrected. SK>0 indicates that the data is right-biased and the orientation needs to be corrected to the left.

[0115] Module M4: Corrects the orientation based on the location distribution of communication equipment.

[0116] Specifically, in module M4:

[0117] When the absolute value of SK is less than the preset value, the data is unbiased and there is no need to correct the orientation.

[0118] When the absolute value of SK is greater than the set value, the azimuth direction of the left and right deviation data is corrected accordingly to the right and left, respectively, with the correction coefficient σ being...

[0119] σ=f(SK)

[0120] Where f(SK) is the calculation function of the correction coefficient σ, and the calculation function is selected as linear or nonlinear depending on the tolerance for data deviation.

[0121] Example 3:

[0122] Example 3 is a preferred example of Example 1, and is used to illustrate the present invention in more detail.

[0123] This invention can effectively identify communication devices in a stationary state through multiple dimensions including time domain, spatial domain, and data features, and can perform more detailed classification of the detected communication device data. The main task of this invention is to identify communication devices in a stationary state and provide the azimuth direction of the communication device. Here, "stationary azimuth" and "azimuth direction" are innovative concepts proposed in this invention, accurately describing the motion state of communication devices in the field of code detection technology data analysis. "Stationary azimuth" refers to a situation where the azimuth of a communication device or other target changes within a certain time period, and the main range of change is less than the main beamwidth of the code detection device. "Azimuth direction" refers to the location of a communication device in a stationary state with the highest probability. The data distribution of stationary communication devices is as follows: Figure 1 As shown.

[0124] This invention relies on a directional tracking detection device that can perform omnidirectional monitoring and data collection of the deployment location monitoring area. It can assign directional information to the collected communication device data, provide directional reference values ​​for each piece of communication device information, and ultimately identify stationary communication devices and their directional orientation based on the directional distribution characteristics of each communication device. The system workflow diagram is as follows. Figure 2 As shown.

[0125] Specifically, after the site is deployed, the directional tracking detection device begins to monitor the monitoring area in all directions. The detection device can perform directional tracking according to the set search and patrol route. During the search and patrol, it continuously detects communication devices, collects information from the communication devices, and obtains the current orientation of the frame code device when it collects data from the communication devices. This information is then integrated with the data from the communication devices and sent back to the system database for storage.

[0126] Specifically, after acquiring communication device information data, the location of the communication device is statistically analyzed to determine its directional distribution. This invention uses kurtosis as the criterion for determining directional static data. Based on the kurtosis measurement value, it is determined whether the directional distribution of the communication device is in a flat or peaked state, with different kurtosis manifestations as follows: Figure 3 As shown. The formula for kurtosis state measurement is:

[0127]

[0128] Where K is a measure of the azimuth distribution kurtosis, and n is the total number of detected communication device information data. σ is the azimuth mean, and s is the azimuth standard deviation. i K represents the azimuth value of each detected data point collected by the communication device. Depending on the azimuth detection accuracy achievable by different detection devices, K can take different values ​​to measure whether the communication device is in a stationary azimuth state. K is a measure of kurtosis; it is assumed that the calculated K is greater than the threshold K0. th If it is oriented at a certain value, it is considered to be stationary; otherwise, it is considered not to be stationary at a certain value. th It can be used flexibly according to project requirements.

[0129] The flexible use of the K value allows for adaptation to different devices and working environments, enabling the invention to be applied to various practical scenarios.

[0130] Specifically, after determining that the communication device is a stationary communication device, this invention can calculate its azimuth direction based on the data collected by the communication device. The expected value of the azimuth distribution can be obtained as the azimuth direction of the communication device, and its expression is:

[0131] pnting x =E(x)

[0132] Because the parameters of the detection equipment are stable during operation and there is no violent fluctuation, the azimuth distribution of the stationary communication equipment is approximately normal under ideal conditions. However, in actual application scenarios, there are external factors such as obstruction, electromagnetic interference, slight movement of the stationary target, and being within the detection boundary of the detection equipment. These factors cause a deviation between the mathematical expectation of the azimuth distribution and the actual azimuth direction. Therefore, the final determination of the azimuth direction needs to take into account the skewness of the azimuth distribution in order to correct the azimuth direction.

[0133] Specifically, skewness refers to the asymmetry of data distribution. Schematic diagrams illustrating left-skewed, unskewed, and right-skewed data are shown below. Figure 4 As shown, this invention uses the skewness coefficient as a measure of data distribution asymmetry. The formula for calculating the skewness coefficient is as follows:

[0134]

[0135] Where SK is the skewness coefficient, and n is the total number of detected communication device information data. SK represents the azimuth mean, and s represents the azimuth standard deviation. SK < 0 indicates that the data is left-skewed and the azimuth needs to be corrected to the right; SK = 0 indicates that the data is unskewed and the azimuth does not need to be corrected; SK > 0 indicates that the data is right-skewed and the azimuth needs to be corrected to the left.

[0136] Specifically, in practical applications, due to unavoidable system errors and environmental interference, when the absolute value of SK is less than a certain value, the data can be considered unbiased and no correction for the azimuth direction is needed. When the absolute value of SK is greater than the set value, the azimuth direction of the left-biased and right-biased data needs to be corrected accordingly to the right and left, with a correction coefficient of [value missing].

[0137] σ=f(SK)

[0138] Where f(SK) is the specific calculation function of the correction coefficient σ. In practical applications, the calculation function can be selected as linear or nonlinear depending on the tolerance for data deviation.

[0139] This invention provides a system and method for identifying stationary communication devices based on code detection technology, and analyzes and explains it from the spatial domain, temporal domain, and data feature domain. The temporal domain refers to the limitation of data acquisition time. The spatial domain refers to the distribution location of the communication devices. The data domain refers to the kurtosis and skewness statistical results.

[0140] The specific methods mentioned in this invention are merely one effective implementation of the invention and do not represent all the contents covered by the invention. For example, there are many basic methods for determining azimuth at rest, including specific measurement methods for different kurtosis and skewness, variance, range, coefficient of variation, and other related metrics. This paper only selects one specific implementation for illustration. f(SK) can be modified according to the actual application by choosing an appropriate function expression to correct the azimuth direction. Therefore, any related variations are within the protection scope of this invention.

[0141] Those skilled in the art will understand that, in addition to implementing the system, apparatus, and their modules provided by this invention in purely computer-readable program code, the same program can be implemented in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers by logically programming the method steps. Therefore, the system, apparatus, and their modules provided by this invention can be considered a hardware component, and the modules included therein for implementing various programs can also be considered structures within the hardware component; alternatively, modules for implementing various functions can be considered both software programs implementing the method and structures within the hardware component.

[0142] Specific embodiments of the present invention have been described above. It should be understood that the present invention is not limited to the specific embodiments described above, and those skilled in the art can make various changes or modifications within the scope of the claims, which do not affect the essence of the present invention. Unless otherwise specified, the embodiments and features described in this application can be arbitrarily combined with each other.

Claims

1. A method for identifying a stationary communication device based on a signature technology, characterized by, include: Step S1: Detect communication device information and assign azimuth information based on the frame code device's operating status; Step S2: Calculate the peak value of the azimuth distribution of the communication equipment and determine whether the azimuth static setting is met; Step S3: Calculate the orientation and distribution skewness measures of the communication equipment; Step S4: Correct the orientation based on the location distribution of communication equipment; In step S2: After acquiring communication equipment information data, the location of the communication equipment is statistically analyzed to determine its location distribution. Kurtosis is used as the criterion for determining azimuth stationary data. Based on the kurtosis measurement value, it is determined whether the azimuth distribution of the communication equipment is in a flat or peaked state. The formula for kurtosis measurement is: in, This is a measure of the kurtosis of the azimuth distribution. The total amount of information data from detected communication devices. This is the average value of the azimuth. This represents the standard deviation of azimuth. This represents the azimuth value of the data collected by each detected communication device; The directional detection accuracy can be achieved by different code detection devices. It can take different corresponding values ​​to measure whether the communication device is in a stationary state. When the calculated result of K is greater than the threshold... If it is true, then it is stationary in orientation; otherwise, it is not stationary in orientation. Configure according to project requirements; In step S3: After determining that the communication equipment is a stationary communication device, the azimuth direction is calculated based on the data collected by the communication equipment; the expected value of the azimuth distribution is then used as the azimuth direction of the communication equipment. The expression is: The skewness coefficient is used as a measure of the asymmetry in the data distribution. The formula for calculating the skewness coefficient is: in, The skewness coefficient, The total amount of information data from detected communication devices. This is the average value of the azimuth. This represents the standard deviation of azimuth. The data indicates a leftward skew; the orientation needs to be corrected to the right. It represents impartiality, and the orientation does not require correction. The data indicates a rightward bias, and the orientation needs to be corrected to the left.

2. The method for identifying a stationary communication device based on code detection technology according to claim 1, characterized in that, In step S1: The directional tracking detection device can perform all-round monitoring and data collection of the deployment location monitoring area, assign directional information to the collected communication device data, provide directional reference values ​​for each communication device information, and identify stationary communication devices and their directional directions based on the directional distribution characteristics of each communication device. Stationary directional means that when the directional change range of the location of the communication device or other target is less than the main beam width of the detection device within a preset time. Directional orientation refers to the direction in which a communication device in a stationary position is most likely to be located. After the site is deployed, the directional tracking detection device can monitor the monitoring area in all directions. The detection device follows the set search and patrol route in a directional manner, detects communication devices during the search and patrol, collects information from the communication devices, and obtains the current orientation of the frame code device when it collects data from the communication devices. This information is then integrated with the data from the communication devices and sent back to the system database for storage.

3. The method for identifying stationary communication devices based on code detection technology according to claim 1, characterized in that, In step S4: when When the absolute value is less than the preset value, the data is unbiased and there is no need to correct the orientation. when When the absolute value is greater than the set value, the azimuth direction of the left and right deviation data is corrected accordingly to the right and left, respectively, with the correction coefficient being [missing value]. for in, Correction coefficient The calculation function is selected as either linear or nonlinear, depending on the tolerance for data deviation.

4. A location-based stationary communication device identification system based on code detection technology, characterized in that, include: Module M1: Detects communication equipment information and assigns azimuth information based on the frame code device's operating status; Module M2: Calculates the peak value of the azimuth distribution of the communication equipment and determines whether the azimuth stationary setting is met; Module M3: Calculates the orientation and distribution skewness measures of communication equipment; Module M4: Corrects orientation based on the location distribution of communication equipment; In module M2: After acquiring communication equipment information data, the location of the communication equipment is statistically analyzed to determine its location distribution. Kurtosis is used as the criterion for determining azimuth stationary data. Based on the kurtosis measurement value, it is determined whether the azimuth distribution of the communication equipment is in a flat or peaked state. The formula for kurtosis measurement is: in, This is a measure of the kurtosis of the azimuth distribution. The total amount of information data from detected communication devices. This is the average value of the azimuth. This represents the standard deviation of azimuth. This represents the azimuth value of the data collected by each detected communication device; The directional detection accuracy can be achieved by different code detection devices. It can take different corresponding values ​​to measure whether the communication device is in a stationary state. When the calculated result of K is greater than the threshold... If it is true, then it is stationary in orientation; otherwise, it is not stationary in orientation. Configure according to project requirements; In module M3: After determining that the communication equipment is a stationary communication device, the azimuth direction is calculated based on the data collected by the communication equipment; the expected value of the azimuth distribution is then used as the azimuth direction of the communication equipment. The expression is: The skewness coefficient is used as a measure of the asymmetry in the data distribution. The formula for calculating the skewness coefficient is: in, The skewness coefficient, The total amount of information data from detected communication devices. This is the average value of the azimuth. This represents the standard deviation of azimuth. The data indicates a leftward skew; the orientation needs to be corrected to the right. It represents impartiality, and the orientation does not require correction. The data indicates a rightward bias, and the orientation needs to be corrected to the left.

5. The location-based stationary communication device identification system based on code detection technology according to claim 4, characterized in that, In module M1: The directional tracking detection device can perform all-round monitoring and data collection of the deployment location monitoring area, assign directional information to the collected communication device data, provide directional reference values ​​for each communication device information, and identify stationary communication devices and their directional directions based on the directional distribution characteristics of each communication device. Stationary directional means that when the directional change range of the location of the communication device or other target is less than the main beam width of the detection device within a preset time. Directional orientation refers to the direction in which a communication device in a stationary position is most likely to be located. After the site is deployed, the directional tracking detection device can monitor the monitoring area in all directions. The detection device follows the set search and patrol route in a directional manner, detects communication devices during the search and patrol, collects information from the communication devices, and obtains the current orientation of the frame code device when it collects data from the communication devices. This information is then integrated with the data from the communication devices and sent back to the system database for storage.

6. The location-based stationary communication device identification system based on code detection technology according to claim 4, characterized in that, In module M4: when When the absolute value is less than the preset value, the data is unbiased and there is no need to correct the orientation. when When the absolute value is greater than the set value, the azimuth direction of the left and right deviation data is corrected accordingly to the right and left, respectively, with the correction coefficient being [missing value]. for in, Correction coefficient The calculation function is selected as either linear or nonlinear, depending on the tolerance for data deviation.

Images