CN120064799B - Radio electromagnetic environment real-time monitoring system based on urban traffic - Google Patents
Radio electromagnetic environment real-time monitoring system based on urban trafficInfo
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- CN120064799B CN120064799B CN202510560102.7A CN202510560102A CN120064799B CN 120064799 B CN120064799 B CN 120064799B CN 202510560102 A CN202510560102 A CN 202510560102A CN 120064799 B CN120064799 B CN 120064799B
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R29/00—Arrangements for measuring or indicating electric quantities not covered by groups G01R19/00 - G01R27/00
- G01R29/08—Measuring electromagnetic field characteristics
- G01R29/0807—Measuring electromagnetic field characteristics characterised by the application
- G01R29/0814—Field measurements related to measuring influence on or from apparatus, components or humans, e.g. in ESD, EMI, EMC, EMP testing, measuring radiation leakage; detecting presence of micro- or radiowave emitters; dosimetry; testing shielding; measurements related to lightning
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R29/00—Arrangements for measuring or indicating electric quantities not covered by groups G01R19/00 - G01R27/00
- G01R29/08—Measuring electromagnetic field characteristics
- G01R29/0864—Measuring electromagnetic field characteristics characterised by constructional or functional features
- G01R29/0871—Complete apparatus or systems; circuits, e.g. receivers or amplifiers
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R29/00—Arrangements for measuring or indicating electric quantities not covered by groups G01R19/00 - G01R27/00
- G01R29/08—Measuring electromagnetic field characteristics
- G01R29/0864—Measuring electromagnetic field characteristics characterised by constructional or functional features
- G01R29/0892—Details related to signal analysis or treatment; presenting results, e.g. displays; measuring specific signal features other than field strength, e.g. polarisation, field modes, phase, envelope, maximum value
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
- G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
- G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
- G01S19/393—Trajectory determination or predictive tracking, e.g. Kalman filtering
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Abstract
The invention relates to the technical field of electromagnetic environment monitoring, in particular to a radio electromagnetic environment real-time monitoring system based on urban traffic. According to the invention, the signal acquisition frequency is dynamically adjusted, the data redundancy problem under a high-speed moving scene is optimized, the local signal capturing capacity is improved, a plane coordinate system is utilized to divide grids and combine normalization processing, the data storage pressure is reduced, the feature integrity is guaranteed, a threshold line is dynamically generated by adopting a sliding average algorithm, the signal-to-noise separation precision is improved, the misjudgment rate is reduced, the signal level value is corrected by combining the vehicle position and the grid center distance, the positioning error of a signal source is reduced, the geographic feature gradient and the building height parameter are fused to adjust the fitting weight, the data distortion and the electromagnetic situation map blind area are reduced, and the electromagnetic environment panoramic monitoring with high precision and low delay under the complex urban environment is realized.
Description
Technical Field
The invention relates to the technical field of electromagnetic environment monitoring, in particular to a radio electromagnetic environment real-time monitoring system based on urban traffic.
Background
The technical field of electromagnetic environment monitoring comprises a technical system for real-time acquisition, analysis and management of radio frequency spectrum resource distribution, electromagnetic field intensity, signal characteristics and interference sources. The core content of the field is that the frequency spectrum scanning, the signal measurement, the occupancy analysis, the interference investigation and the station checking of a target area are completed through equipment such as a fixed monitoring station, a mobile monitoring vehicle and a portable frequency spectrum analyzer, a plurality of links such as data acquisition terminal deployment, multi-source heterogeneous data fusion, signal characteristic extraction and classification and electromagnetic situation visualization are covered, and the current technical challenges are concentrated on the problems of limited coverage range of a fixed monitoring facility, insufficient dynamic monitoring capability of a high-density area, low real-time processing efficiency of mass data and insufficient signal-noise separation precision in a complex electromagnetic environment.
The radio electromagnetic environment real-time monitoring system based on urban traffic is a system for acquiring electromagnetic signals through public traffic carrier carried monitoring equipment and realizing signal extraction and positioning by combining meshed data compression and dynamic threshold algorithm, and specifically comprises a system for deploying a low-power monitoring receiver and an integrated antenna on a public traffic vehicle, automatically acquiring full-frequency-band signals along with the running of the vehicle and uploading a data center, dividing grids into Gaussian plane coordinates through longitude and latitude coordinate conversion, carrying out normalization combination on multi-frame data in the same grid, dividing a frequency spectrum according to a service frequency band, dynamically calculating a signal threshold based on adjacent peak value comparison, screening frequency bands exceeding the threshold, carrying out spatial correction on frequency band level values by adopting a weighted fitting mode aiming at signal positioning deviation, filling uncovered area data by utilizing a wavelet transformation superposition least square method, and generating an electromagnetic spectrum situation map by combining a free space propagation model.
In the traditional radio electromagnetic environment real-time monitoring technology, fixed monitoring facilities depend on fixed power supply and network conditions, special areas such as express ways, underground spaces and the like cannot be covered, so that a monitoring blind area is relatively high, multi-source heterogeneous data fusion lacks a normalization processing mechanism, redundant data quantity is greatly increased due to different equipment frequency bands and sampling rates, storage and transmission cost is increased, a static threshold algorithm adopts fixed threshold screening signals, the fluctuation of day and night signal intensity cannot be adapted, the misjudgment rate is high, signal positioning depends on a single propagation model, dynamic distance correction of uncombined vehicle positions and grid centers is carried out, positioning deviation is generally large, multipath reflection effects of building groups are ignored in a data filling process, fitting errors of uncombined areas are obvious, and thermodynamic diagram and actual electromagnetic distribution deviation are obvious.
Disclosure of Invention
The invention aims to solve the defects in the prior art, and provides a radio electromagnetic environment real-time monitoring system based on urban traffic.
In order to achieve the purpose, the invention adopts the following technical scheme that the radio electromagnetic environment real-time monitoring system based on urban traffic comprises:
the signal acquisition module acquires vehicle running state information, extracts GPS coordinates and draws a vehicle running track in real time, and acquires a radio signal data set by identifying the running state of the vehicle, adjusting acquisition frequency and combining the position coordinates and a time stamp;
the grid compression module calls the radio signal data set, converts longitude and latitude data into a plane coordinate system, divides an area into a plurality of grids, distributes grid codes, maps radio signals into the grids, normalizes and combines data in the grids, and generates a grid code data set;
The signal processing module calls the grid coding data set, splits the monitoring data according to the service frequency bands, extracts the peak value of each sub-frequency band, calculates the difference value of adjacent peak values, and obtains a threshold line to denoise the signal by calculating the sliding average value of the signal peak value level to obtain a threshold signal characteristic set;
the signal positioning module calls the threshold signal feature set, calculates a distance attenuation factor by utilizing the distance between the vehicle position and the grid center according to the level value and the position code of the radio signal, adjusts the level value of the narrow-band high-power signal, fits a two-dimensional intensity distribution curved surface, extracts extreme points and generates a signal source coordinate set.
As a further scheme of the invention, the radio signal data set specifically includes a signal frequency parameter, a position coordinate and a time stamp, the grid coding data set includes a plane coordinate system parameter, a grid coding parameter and a normalized combining parameter, the threshold signal feature set specifically includes a service frequency band dividing parameter, a threshold line parameter and an effective signal frequency band list, and the signal source coordinate set includes a level value parameter, a two-dimensional intensity distribution curved surface and an extreme point identification record.
As a further aspect of the present invention, the signal acquisition module includes:
The state monitoring submodule acquires vehicle running state information, extracts vehicle engine start-stop signals and GPS sensor data, extracts longitude and latitude coordinates in real time, and acquires a real-time coordinate data set;
the track analysis submodule calls the real-time coordinate data set, draws track points according to the time stamp sequence, calculates the distance difference and the time difference of adjacent coordinate points, calculates the running speed of the vehicle in real time, identifies the motion state of the vehicle and generates a speed identification value;
The signal regulation and control submodule calculates the time difference of adjacent coordinate points by calling a time stamp sequence based on the speed identification value and combining real-time coordinate data, and adopts the formula:
;
Calculating to obtain a dynamic frequency adjustment coefficient, collecting radio signals in real time, and generating a radio signal data set by combining real-time coordinate data and a time stamp;
Wherein, the For the dynamic acquisition of the frequency adjustment coefficients,Is the vehicle speed identification value at time t,Is the abscissa of the plane coordinate system at the time t,Is the ordinate of the plane coordinate system at the time t,Is the abscissa of the plane coordinate system at the time t-1,Is the ordinate of the plane coordinate system at the time t-1,Is the time difference between adjacent coordinate points,And t is the sequence identifier of the current moment, and t-1 is the sequence identifier of the previous moment.
As a further aspect of the present invention, the mesh compression module includes:
The gridding conversion submodule acquires the radio signal data set, and converts longitude and latitude data into a plane coordinate system by Gaussian projection;
the grid code allocation submodule calls the plane coordinate system, divides the coordinate system into a plurality of grids, allocates grid codes and generates a code allocation result;
And the signal normalization combining submodule invokes the radio signal data based on the code allocation result, maps the radio signal into a grid, and performs normalization combining on the data in the grid to generate a grid coding data set.
As a further aspect of the present invention, the signal processing module includes:
The frequency band splitting submodule calls the grid coding data set, divides the monitoring data into a plurality of frequency sub-bands according to the service frequency band, and generates a frequency sub-band data set;
the peak value analysis submodule extracts the peak value level of each sub-frequency band signal based on the sub-frequency band data set, calculates the adjacent peak value level difference value and generates a peak value difference value data set;
the threshold generation submodule calls the peak value difference data set, calculates a sliding average value of signal peak value levels, combines adjacent peak value difference dynamic matching weight parameters, and adopts the formula:
;
Calculating to obtain dynamic threshold line parameters, denoising signals, extracting an effective signal frequency band list, and generating a threshold signal characteristic set;
Wherein, the As a parameter of the threshold line,For the peak level of the ith sub-band,As an arithmetic average of the peak levels of all sub-bands within the sliding window,The weight parameter matched with the difference value of the ith adjacent peak value, P is the frequency band interference suppression coefficient,And i is a reference value of a sliding average value of signal peak level, i is a sub-band index number, and n is the total number of sub-bands in the current sliding window.
As a further aspect of the present invention, the signal positioning module includes:
the level adjustment submodule invokes the threshold signal feature set, extracts the level value and the position code of the radio signal, and adopts the formula according to the distance between the vehicle position and the center of the grid:
;
Calculating the influence of free space path loss on the signal level, and adjusting the level value of the narrow-band high-power signal to generate a level correction data set;
for the corrected signal power, d is the euclidean distance between the vehicle position and the grid center, f is the signal center frequency, c is the propagation speed of the electromagnetic wave in vacuum, For the original signal level reference value,Is the circumference ratio;
The intensity fitting submodule is used for calling position codes and correcting level values based on the level correction data set, fitting a two-dimensional signal intensity distribution curved surface and generating an intensity curved surface data set;
and the extremum extraction submodule calls the intensity curved surface data set, and identifies the signal source position by extracting the curved surface extremum point coordinates to generate a signal source coordinate set.
As a further aspect of the present invention, the system further includes:
The situation filling module uses the signal source coordinate set and the grid coding data set to call regional grid signal data and regional geographic features, calculates initial fitting values of uncovered grids, adjusts fitting level value correction parameters in combination with building heights, fits equipotential lines, calculates level intensity gradients and maps the level intensity gradients into a thermodynamic diagram, and generates an electromagnetic spectrum situation map;
the electromagnetic spectrum situation map is specifically a record drawn by uncovered grid fitting values, building height correction parameters and thermodynamic diagrams.
As a further aspect of the present invention, the situation filling module includes:
the grid fitting submodule calls the signal source coordinate set and the grid coding data set, extracts the regional grid signal intensity and the geographic characteristic parameters, and adopts the formula:
;
calculating initial fitting values of the uncovered grids, and generating an initial fitting data set;
Wherein, the For the initial fit value(s),For the kth grid signal strength,For the kth grid geographic feature gradient,For the center abscissa of the kth grid,Is the center ordinate of the kth grid,As the mean value of the abscissa of the reference region,For the mean value of the ordinate of the reference area, m is the total number of grids, k is the index number of the grid,Is a distance smoothing factor;
The parameter correction submodule adjusts a fitting level value correction parameter based on the initial fitting data set and combining building height data, corrects the initial fitting value and generates a corrected level parameter set;
And the thermodynamic mapping submodule invokes the corrected level parameter set, and maps the signal thermodynamic diagram of the target area by calculating the level intensity gradient to generate an electromagnetic spectrum situation map.
Compared with the prior art, the invention has the advantages and positive effects that:
According to the invention, the signal acquisition frequency is dynamically adjusted, the data redundancy problem under a high-speed moving scene is optimized, the local signal capturing capacity is improved, a plane coordinate system is utilized to divide grids and combine normalization processing, the data storage pressure is reduced, the feature integrity is guaranteed, a threshold line is dynamically generated by adopting a sliding average algorithm, the signal-to-noise separation precision is improved, the misjudgment rate is reduced, the signal level value is corrected by combining the vehicle position and the grid center distance, the positioning error of a signal source is reduced, the geographic feature gradient and the building height parameter are fused to adjust the fitting weight, the data distortion and the electromagnetic situation map blind area are reduced, and the electromagnetic environment panoramic monitoring with high precision and low delay under the complex urban environment is realized.
Drawings
FIG. 1 is a system flow diagram of the present invention;
FIG. 2 is a flow chart of a signal acquisition module according to the present invention;
FIG. 3 is a flow chart of a mesh compression module of the present invention;
FIG. 4 is a flow chart of a signal processing module according to the present invention;
FIG. 5 is a flow chart of a signal positioning module according to the present invention;
fig. 6 is a flow chart of a situation filling module of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present invention more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
In the description of the present invention, it should be understood that the terms "length," "width," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," and the like indicate orientations or positional relationships based on the orientation or positional relationships shown in the drawings, merely to facilitate describing the present invention and simplify the description, and do not indicate or imply that the devices or elements referred to must have a specific orientation, be configured and operated in a specific orientation, and therefore should not be construed as limiting the present invention. Furthermore, in the description of the present invention, the meaning of "a plurality" is two or more, unless explicitly defined otherwise.
Referring to fig. 1, a radio electromagnetic environment real-time monitoring system based on urban traffic includes:
the signal acquisition module acquires vehicle running state information, extracts GPS coordinates and draws a vehicle running track in real time, and acquires a radio signal data set by identifying the running state of the vehicle, adjusting acquisition frequency and combining the position coordinates and a time stamp;
the grid compression module calls a radio signal data set, converts longitude and latitude data into a plane coordinate system, divides an area into a plurality of grids, distributes grid codes, maps radio signals into the grids, normalizes and combines data in the grids, and generates a grid code data set;
The signal processing module calls a grid coding data set, splits monitoring data according to service frequency bands, extracts peak values of each sub-frequency band, calculates adjacent peak value difference values, and obtains a threshold line to denoise signals by calculating a sliding average value of signal peak value levels to obtain a threshold signal characteristic set;
the signal positioning module calls a threshold signal characteristic set, calculates a distance attenuation factor by utilizing the distance between the vehicle position and the grid center according to the level value and the position code of the radio signal, adjusts the level value of the narrow-band high-power signal, fits a two-dimensional intensity distribution curved surface, extracts extreme points and generates a signal source coordinate set;
The situation filling module uses a signal source coordinate set and a grid coding data set, invokes regional grid signal data and regional geographic features, calculates initial fitting values of uncovered grids, adjusts fitting level value correction parameters in combination with building heights, fits equipotential lines, calculates level intensity gradients, maps the level intensity gradients into a thermodynamic diagram, and generates an electromagnetic spectrum situation map.
The radio signal data set specifically comprises signal frequency parameters, position coordinates and time stamps, the grid coding data set comprises plane coordinate system parameters, grid coding and normalization combining parameters, the threshold signal characteristic set specifically comprises service frequency band dividing parameters, threshold line parameters and an effective signal frequency band list, the signal source coordinate set comprises level value parameters, a two-dimensional intensity distribution curved surface and extreme point identification records, and the electromagnetic spectrum situation map specifically comprises uncovered grid fitting values, building height correction parameters and thermodynamic diagram drawing records.
Referring to fig. 2, the signal acquisition module includes:
The state monitoring submodule acquires vehicle running state information, extracts vehicle engine start-stop signals and GPS sensor data, extracts longitude and latitude coordinates in real time, and acquires a real-time coordinate data set;
The engine start-stop signal is obtained through a vehicle-mounted OBD interface, the signal level value fluctuates within the range of 0-12V, when the level value is larger than 8V, the engine start state is judged, a GPS sensor adopts a U-bloxM N module, the sampling frequency is 1Hz, the precision is 2.5 m, longitude and latitude data under a WGS84 coordinate system are output in real time, the longitude range is 73-135 DEG, the latitude range is 18-53 DEG, the engine state is aligned with GPS data according to time stamps, a group of data is recorded every 100ms, and the formula is adopted:
;
an engine state value is calculated, wherein, As the value of the engine state value,As the value of the current level is,At the level of the minimum value of the electrical level,Is the maximum level value. Setting upThe voltage was set to be 10V,At a voltage of 0V,Substituting the set value into 12V for calculation:
;
The calculation result shows that the engine is in a starting state, and the engine state value, the longitude value, the latitude value and the time stamp are combined to generate a real-time coordinate data set.
The track analysis sub-module calls a real-time coordinate data set, draws track points according to the time stamp sequence, calculates the distance difference and the time difference of adjacent coordinate points, calculates the running speed of the vehicle in real time, identifies the motion state of the vehicle and generates a speed identification value;
In actual operation, the time difference between adjacent coordinate points is set to be 100ms, the distance between the adjacent coordinate points is calculated through HAVERSINE formula, when the vehicle is in a stationary state, the distance between the adjacent coordinate points is less than 0.1 meter, when the vehicle is in a driving state, the distance between the adjacent coordinate points is between 0.1 and 50 meters, and the formula is adopted:
;
calculating a velocity value, wherein v is the velocity value, d is the distance between adjacent coordinate points, Is the time difference. D is set to be 25 meters and is set to be 25 meters,Substituting the set value for 0.1 seconds to calculate:
;
The calculation result shows that the vehicle is in a normal running state, and the speed value is calculated every 100ms to generate the speed identification value.
The signal regulation and control submodule calculates the time difference of adjacent coordinate points by calling a time stamp sequence based on the speed identification value and combining real-time coordinate data, and adopts the formula:
;
Calculating to obtain a dynamic frequency adjustment coefficient, collecting radio signals in real time, and generating a radio signal data set by combining real-time coordinate data and a time stamp;
Wherein, the For the dynamic acquisition of the frequency adjustment coefficients,Is the vehicle speed identification value at time t,Is the abscissa of the plane coordinate system at the time t,Is the ordinate of the plane coordinate system at the time t,Is the abscissa of the plane coordinate system at the time t-1,Is the ordinate of the plane coordinate system at the time t-1,Is the time difference between adjacent coordinate points,The frequency band coverage density coefficient is obtained, t is the sequence identifier of the current moment, and t-1 is the sequence identifier of the previous moment;
calculating the time difference of adjacent coordinate points by using the speed identification value and the real-time coordinate data set through a time stamp sequence, and adopting the formula:
;
The dynamic frequency adjustment coefficient is obtained through operation, the radio signal is collected in real time, and the radio signal data set is generated by combining the real-time coordinate data and the time stamp. In actual operation, the WGS84 coordinate system is converted into a plane coordinate system, the x coordinate range is between 0 and 1000 meters, the y coordinate range is between 0 and 1000 meters, and the time difference between adjacent coordinate points is the same 100Ms frequency band coverage density coefficientAccording to the urban area type, the commercial area is 1.2, the residential area is 0.8, the industrial area is 1.0, and the setting is thatAbout 60km/h, about 16.67m/s,Is 500 meters in length and is suitable for the treatment of the common cold with the Chinese herbal medicines,Is the water content of the water-soluble fiber is 450 m,Is 500 meters in length and is suitable for the treatment of the common cold with the Chinese herbal medicines,Is the water content of the water-soluble fiber is 450 m,It is within a period of 0.1 seconds,Substituting the set value into 1.2 for calculation:
;
The calculation result shows that the dynamic frequency adjustment coefficient is 0.028, the acquisition frequency of the radio signal is adjusted according to the dynamic frequency adjustment coefficient, the local signal capturing capacity is enhanced, the signal acquisition frequency range is between 2 and 10Hz, the acquisition signal intensity range is between-120 dBm and 0dBm, and the real-time coordinate data and the time stamp are combined to generate the radio signal data set.
Referring to fig. 3, the mesh compression module includes:
The gridding conversion sub-module acquires a radio signal data set and converts longitude and latitude data into a plane coordinate system by using Gaussian projection;
The method comprises the steps of obtaining a radio signal data set, wherein the data set comprises information items such as a time stamp, longitude, latitude, signal intensity and the like, converting a geographic coordinate into a plane coordinate by utilizing a Gaussian projection method, firstly determining a Gaussian projection zoning used according to the geographic position of a signal acquisition point, for example, selecting a 6-degree zoning according to a city region, determining the longitude of a central meridian of the zoning, converting longitude and latitude coordinates into transverse and longitudinal coordinate values under a Gaussian plane rectangular coordinate system by taking the selected central meridian and equator as references, calculating the arc length distance of a coordinate point from the equator along the central meridian direction as an ordinate according to an earth ellipsoid model parameter, calculating the vertical distance of the coordinate point to the central meridian as an abscissa, adding a constant, for example, 500000 meters to the abscissa, performing conversion calculation on the longitude and latitude coordinates of each signal acquisition point recorded in the radio signal data set, and finally converting the geographic coordinates of all signal data points into corresponding plane coordinates to generate the plane coordinate data set.
The grid code allocation submodule calls a plane coordinate system, divides the coordinate system into a plurality of grids, allocates grid codes and generates a code allocation result;
A plane coordinate system is called, the coordinate system is divided into a plurality of grids, the grid size is set to be 100 meters multiplied by 100 meters, the row and column numbers of the grids to which the grid belongs are calculated according to coordinate points (4418500 meters on the ordinate and 446540 meters on the abscissa), and the formula is adopted:
;
;
The grid row and column numbers are calculated, wherein, In the form of a grid line number,Is grid column number, x is plane coordinate ordinate, y is plane coordinate abscissa,Is the side length of the grid (unit: meter),Represents downward rounding operation, x is 4418500 m, y is 446540 m,Substituting the set value into 100 meters for calculation:
;
;
the calculation result shows that the point belongs to 44185 th row and 4465 th column grids, the row and column numbers are combined to generate grid codes, unique codes are obtained by multiplying the row number by a base number (such as 100000) and adding the column number, the grid codes 4418504465 are obtained, and corresponding grid codes are distributed to all plane coordinate points in the area.
The signal normalization combining sub-module invokes radio signal data based on the code allocation result, maps the radio signal into a grid, performs normalization combining on the data in the grid, and generates a grid code data set;
Based on the grid coding data set, invoking signal intensity data in the radio signal data set, mapping the radio signal intensity value (-85 dB and milliwatt) of each timestamp into the corresponding grid coding (4418504465), carrying out normalization and combination processing on all the signal intensity data collected by the same grid within a set time window (1 minute), firstly normalizing the signal intensity, mapping the signal intensity to a section from 0 to 1, and adopting a formula:
;
A normalized signal strength is calculated, wherein, For normalized signal strength values, P is the original signal strength value,To set the minimum signal strength value recorded by the grid within the time window,For setting the maximum signal strength value recorded by the grid within the time window. Assuming the received signal strength of the grid 4418504465 within one minute is minus 85 db mw, minus 90 db mw, and minus 80 db mw, respectivelyIs minus 90 db milliwatts,For a signal strength P equal to minus 85 db mw, the set point is substituted for the calculation:
;
The calculation result shows that the normalized value of the signal intensity minus 85 dB and the signal intensity of 85 dB is 0.5, all the signal intensity values of the grid in the time window are subjected to the same normalization calculation, then the normalization values are processed according to a preset combination strategy, and the representative normalized signal intensity value obtained by the combination calculation and the corresponding grid codes are stored in a correlated manner to form a final output grid code data set.
Referring to fig. 4, the signal processing module includes:
The frequency band splitting sub-module invokes the grid coding data set, divides the monitoring data into a plurality of sub-frequency bands according to the service frequency band, and generates a sub-frequency band data set;
Invoking a grid-encoded signal set comprising representative signal strength information of each grid within a specific time window, which usually covers a wide frequency spectrum range, for example, recording an overall signal strength index of a certain grid within a frequency range of 80MHz to 2.5GHz within a time period of 10 days of 4 months of 2025, according to preset service frequency division parameters, which are determined according to national radio frequency division regulations and specific monitoring task requirements, for example, setting a frequency band to be focused including frequency modulation broadcasting (frequency range 88 to 108 MHz), terrestrial digital television (frequency range 470 to 798 MHz), mobile communication GSM900 downlink (frequency range 935 to 960 MHz), LTEBand downlink (frequency range 1805 to 1880 MHz) and the like, concentrating the original broadband monitoring data recorded by the grid-encoded signal, the method comprises the steps of screening and classifying according to frequency values, specifically, traversing each frequency point in monitoring data and corresponding signal intensity information thereof, judging whether the numerical value of the frequency point is within a preset starting and ending frequency range of any service frequency band, extracting the signal intensity information of the frequency point if the numerical value of the certain frequency point is within the frequency range of the certain service frequency band, classifying the signal intensity information of the frequency point into a data subset specially created for the service frequency band, performing the classifying operation on the signal data of all the frequency points recorded in a grid, finally forming a plurality of mutually independent data sets which respectively only contain the signal information of the specific service frequency band, for example, one data set contains frequency modulation broadcast signal data between 88MHz and 108MHz, the other data set contains GSM downlink signal data between 935MHz and 960MHz, a sub-band data set is generated.
The peak analysis submodule extracts the peak level of each sub-frequency band signal based on the sub-frequency band data set, calculates the adjacent peak level difference value and generates a peak difference value data set;
Extracting peak signal levels for signals in each sub-data set within a set analysis time window (for example, 1 minute) or frequency scanning range based on a sub-frequency band data set, for example, a frequency modulation broadcast sub-data set (including signal data in a range of 88 to 108 MHz), namely, finding the maximum value of signal intensity in the frequency band, detecting that the signal intensity at 98.5MHz is highest in the frequency modulation broadcast sub-data set of the grid 4418504465 as-72 dBm, performing peak extraction operation on all sub-frequency bands (for example, terrestrial digital televisions, GSM900 downlink and the like) to obtain a series of peak level data, and then calculating the difference value between the peak levels of adjacent service frequency bands (in frequency order), for example, if the frequency modulation broadcast peak is-72 dBm, the peak value of the adjacent terrestrial digital television frequency band is-85 dBm, using the formula:
;
Calculating a difference in adjacent peak levels, wherein, As peak level difference (unit: dB),For the peak level (in dBm) of the kth sub-band,Is the peak level (in dBm) of the kth-1 (adjacent in frequency) sub-band. Setting up(Terrestrial digital television) is-85 dBm,(Fm broadcast) was-72 dBm, and the calculation was performed by substituting the set value:
;
the calculation result shows that the peak level of the frequency modulation broadcast and the ground digital television frequency band differ by 13dB, the calculation is repeated for all adjacent sub-frequency band pairs, the difference information of the peak level of each frequency band and the adjacent frequency band is recorded, a data set containing frequency band identification, peak level, adjacent frequency band identification, peak difference value and other fields is formed, and a peak difference value data set is generated.
The threshold generation submodule calls a peak value difference data set, calculates a sliding average value of signal peak value levels, combines adjacent peak value difference dynamic matching weight parameters, and adopts the formula:
;
Calculating to obtain dynamic threshold line parameters, denoising signals, extracting an effective signal frequency band list, and generating a threshold signal characteristic set;
Wherein, the As a parameter of the threshold line,For the peak level of the ith sub-band,As an arithmetic average of the peak levels of all sub-bands within the sliding window,The weight parameter matched with the difference value of the ith adjacent peak value, P is the frequency band interference suppression coefficient,I is a sub-band index number, and n is the total number of sub-bands in the current sliding window;
invoking peak value difference data set and peak value level information in sub-frequency band data set, firstly calculating average value of signal peak value level in a sliding window ) The sliding window can be defined as n frequency-adjacent sub-bands, for example, n is set to 5, the current analysis frequency band and 2 frequency bands before and after the current analysis frequency band are selected, and the arithmetic average value of peak levels of the 5 frequency bands is calculated as a reference valueFor example, if the peak levels of 5 adjacent bands are-72, -85, -80, -88, -75dBm, respectivelyIs-80 dBm, and then, the weight parameters are dynamically matched by combining the adjacent peak difference values recorded in the peak difference value data setWeighting ofIs set to reflect the contribution of the peak difference to the effectiveness of the judgment signal, the smaller the difference is, the smaller the weight should be, the larger the difference is, the larger the weight should be, the larger the difference is, the smaller the difference is less than 5dB,0.2, When the difference is between 5 and 15dB,At 0.6, when the difference is greater than 15dB,1.0, 13DB difference, weightAnd introducing a frequency band interference suppression coefficient P of 0.6, wherein the coefficient is set according to the historical interference condition or the environmental complexity of the frequency band, the frequency band with more known interference is set to be 0.7, the frequency band with less interference is set to be 0.9, the frequency band with less interference is set to be 0.8, and the formula is adopted:
;
setting a sliding window n=3 including the peak levels of the frequency bands a, B, and C At a level of-75 dBm,At a level of-85 dBm,At a level of-80 dBm,=-80dBm。=-80dBm,The total number of the components is 0.6,The total number of the components is 0.6,The interference suppression coefficient p=0.8 is set to 0.6. Substituting the set value into the calculation:
;
;
;
;
the calculation result shows that the dynamic threshold line parameter is-79.32 dBm. By combining the sliding average value and the weighted peak value deviation, the threshold can be adaptively adjusted according to the fluctuation condition of the local frequency spectrum, the fluctuation of the real signal peak value and the background noise can be distinguished, the accuracy of signal detection is improved, the denoising operation is carried out on all the sub-frequency bands, the key characteristics of the denoised signals are extracted, and the threshold signal characteristic set is generated.
Referring to fig. 5, the signal positioning module includes:
The level adjustment submodule calls a threshold signal feature set, extracts a level value and a position code of a radio signal, and adopts the formula according to the distance between the vehicle position and the center of the grid:
;
Calculating the influence of free space path loss on the signal level, and adjusting the level value of the narrow-band high-power signal to generate a level correction data set;
for the corrected signal power, d is the euclidean distance between the vehicle position and the grid center, f is the signal center frequency, c is the propagation speed of the electromagnetic wave in vacuum, For the original signal level reference value,Is the circumference ratio;
The level adjustment submodule calls a threshold signal feature set which contains information such as effective signal frequency band identification, peak level, peak frequency and calculated dynamic threshold value after noise treatment, for example, for the effective signal frequency band A in the grid coding 4418504465, the feature set is characterized by that its central frequency is 98.5MHz, peak level is-75 dBm, firstly, the peak level value of each effective signal is extracted from the feature set ) And the grid code where the signal is positioned, reversely checking the central geographic coordinate of the grid through the grid code, simultaneously acquiring the real-time GPS coordinate of the vehicle when the signal is recorded, converting the real-time GPS coordinate into the coordinate under the same plane coordinate system, calculating the Euclidean distance between the position of the vehicle and the center of the grid, judging whether the signal belongs to a narrow-band high-power type, wherein the narrow-band signal can be defined as a signal bandwidth smaller than 200kHz, the high-power signal can be defined as a peak value level larger than a preset power threshold value, and if the signal meets the condition, carrying out level adjustment;
Setting up ,,,Substituting the formula:
;
The result shows that the corrected signal power is And taking the distance, frequency and signal strength references into consideration, quantifying the deviation effect generated during short-distance measurement, and storing the adjusted level values of all effective signals in all grids in association with the position codes (grid codes) thereof to generate a level correction data set.
The intensity fitting submodule is used for calling position codes and correcting level values based on the level correction data set, fitting a two-dimensional signal intensity distribution curved surface and generating an intensity curved surface data set;
Based on the level correction dataset, the dataset comprises each grid code and a representative level value corrected by each effective frequency band in the grid, for example, the correction level of the frequency band A corresponding to the grid 4418504465 is-55.06 dBm, the position codes (corresponding center coordinates) of a plurality of adjacent grids and the correction level value of the same frequency band (or concerned frequency band) in the grids are called, a continuous two-dimensional signal intensity distribution curved surface is constructed by utilizing the discrete intensity data points through a spatial interpolation or function fitting method, a monitored geographic area is covered, and bilinear interpolation is utilized for any point in the area Its signal strengthThe coordinates of four corner points (namely the centers of four adjacent grids) of the rectangular grid where the coordinates are locatedCorresponding corrected level valueThe calculation results, using the formula:
;
a bilinear interpolation calculation is performed, wherein, Is taken as a pointFitting signal strength (unit: dBm) at,For the plane coordinates of the point to be interpolated,As a surrounding pointIs defined by the four grid center coordinates of (c),The correction level values corresponding to the centers of the four grids are respectively,Is the area of the rectangular grid. Setting the grid side length as 100m and four corner coordinates asM, corresponding correction level valuedBm,dBm,dBm,DBm, calculation pointThe strength at m is set to be equal to the strength at m,,,,. Then,,,Area of. Substituting the set value into the calculation:
;
;
The calculation shows that the signal strength of the fit at point (4418580,446580) is about-57.31 dBm. And (3) carrying out interpolation calculation on all positions in the monitoring area to obtain a mathematical model or a data set for continuously describing the spatial distribution of the signal intensity, wherein the model reflects the variation trend and the distribution form of the signal intensity on a two-dimensional plane, and an intensity curved surface data set is generated.
The extremum extraction submodule calls an intensity curved surface data set, and recognizes the position of a signal source by extracting the coordinates of the extremum points of the curved surface, so as to generate a signal source coordinate set;
invoking an intensity surface dataset representing the distribution of signal intensities in a planar region, in order to identify potential signal emission source locations, finding local extremum points of signal intensities on this intensity distribution surface, which points generally correspond to the central region of the signal source or the region of strongest signal, finding extremum points being possible by analyzing the first and second partial derivatives of the surface function, for a continuously differentiable surface function the local maximum points must satisfy the condition that the first partial derivative at this point (i.e. the rate of change of the function in x-direction and y-direction) is equal to zero, while the second partial derivative at this point (i.e. the curvature of the function in x-direction and y-direction) satisfies certain conditions, in particular the determinant of the hessian matrix (matrix of second partial derivatives) of the function at this point must be greater than zero, and the second partial derivative of the function in x-direction must be less than zero. Together, these conditions ensure that the point is a local maximum point, rather than a minimum point or saddle point, and in actual operation, if the intensity curved surface exists in the form of discrete lattice point data, the local peak value can be found by comparing the intensity values of each lattice point with the intensity values of eight adjacent lattice points around the lattice point, i.e. if the intensity value of a certain point is greater than the intensity values of all adjacent points, the point is identified as a local maximum point, the plane coordinates of all found local maximum points are extracted, the signal source position is identified, and a signal source coordinate set is generated.
Referring to fig. 6, the situation filling module includes:
the grid fitting submodule calls a signal source coordinate set and a grid coding data set, extracts regional grid signal intensity and geographic characteristic parameters, and adopts the formula:
;
calculating initial fitting values of the uncovered grids, and generating an initial fitting data set;
Wherein, the For the initial fit value(s),For the kth grid signal strength,For the kth grid geographic feature gradient,For the center abscissa of the kth grid,Is the center ordinate of the kth grid,As the mean value of the abscissa of the reference region,For the mean value of the ordinate of the reference area, m is the total number of grids, k is the index number of the grid,Is a distance smoothing factor;
The grid fitting submodule calls a signal source coordinate set and a grid coding data set, wherein the data set comprises codes, center coordinates and signal intensity information of each grid in a region, for example, the center coordinates of the grids 4418504465 are (4418550,446550) m, the signal intensity is-55 dBm, the signal intensity and geographic characteristic parameters of the grids in the region are extracted, the geographic characteristic parameters comprise terrain elevation, building density, vegetation coverage and the like, the parameters are obtained through remote sensing data or a geographic information system, for example, the building density of a certain grid is 0.6, the vegetation coverage is 0.3, the terrain elevation is 50m, a wavelet transformation superposition least square method is adopted, and the signal intensity fitting is carried out on uncovered grids (namely, grids without direct measurement data) by adopting the following formula:
;
An initial fit value of the uncovered grid is calculated, wherein, For the initial fitting value (unit: dBm),For the kth grid signal strength (unit: dBm),For the kth grid geographic feature gradient (dimensionless, calculated from geographic feature parameters, such as building density gradient, terrain gradient, etc.),Is the kth grid center abscissa (unit: m),Is the center ordinate (unit: m) of the kth grid,Is the mean value of the abscissa (unit: m) of the reference area,Is the mean value of the ordinate of the reference area (unit: m), m is the total number of grids involved in calculation, k is the grid index number,As distance smoothing factor (unit: m, typically 1% of the grid side length, for example 100m,). The set reference area comprises 5 grids, the central coordinates of which are (4418550,446550), (4418650,446550), (4418550,446650), (4418650,446650), (4418750,446750) m respectively, and the corresponding signal intensities-55, -60, -58, -62, -65DBm, respectively, of geographic feature gradient0.8,0.6,0.7,0.5,0.4, Calculating a reference region coordinate mean value:
, Setting up Calculating initial fitting values of the uncovered grid (4418800,446800), substituting the set values into the calculated values:
;
;
;
;
;
;
The calculation shows that the initial fit signal strength of the uncovered grid (4418800,446800) is about-2.516 dBm. By combining the signal intensity, the geographic feature gradient and the spatial distance, the signal intensity distribution of the uncovered area is accurately estimated, and the influence of the geographic environment on signal propagation is considered. This calculation is performed on all uncovered meshes, generating an initial fit dataset.
The parameter correction sub-module is used for adjusting correction parameters of the fitting level value based on the initial fitting data set and combining building height data, correcting the initial fitting value and generating a corrected level parameter set;
The parameter correction sub-module is based on an initial fit dataset comprising initial fit signal strength values for uncovered grid, e.g. grid (4418800,446800) initial fit values of-2.516 dBm, combined with building height data obtained by laser radar (LiDAR) or stereo photogrammetry, e.g. average building height of a grid of 30m, maximum building height of 100m, standard deviation of building height distribution of 15m, adjusting fit level value correction parameters to correct the initial fit values, the correction taking into account occlusion and reflection effects of the building on the signal, high-rise building resulting in signal attenuation while generating multipath effects, the correction parameters comprising building height coefficients, building density coefficients, building distribution uniformity coefficients etc., e.g. setting building height coefficients With average building heightThe relation of (2) is thatBuilding density coefficientThe relation with the building coverage rate d is thatBuilding distribution uniformity coefficientStandard deviation from heightThe relation of (2) is thatCorrected signal strengthCan be expressed as:
;
Wherein, the For the corrected signal strength (unit: dBm),For the initial fitting value (unit: dBm),、、Is a correction coefficient (dimensionless). Setting initial fitting values of a grid (4418800,446800)Average building heightBuilding coverage d=0.6, height standard deviationCalculating a correction coefficient:
;
;
;
substituting the set value into the calculation:
;
;
;
The calculation shows that the corrected signal strength is about-4.216 dBm, which is about 1.7dB lower than the initial fit value, taking into account the building effects. And executing correction calculation on the initial fitting values of all uncovered grids, and storing the corrected signal strength values, corresponding grid codes and coordinate information in a correlated manner to generate a corrected level parameter set.
The thermodynamic mapping submodule invokes the corrected level parameter set, and maps the signal thermodynamic diagram of the target area by calculating the level intensity gradient to generate an electromagnetic spectrum situation map;
The thermal mapping submodule invokes a modified level parameter set containing signal strength information for all grids within the region (including the measured grid and the fitted modified grid), e.g., grid 4418504465 has a signal strength of-55 dBm, grid (4418800,446800) has a modified signal strength of-4.216 dBm, maps the signal thermodynamic diagram of the target region by calculating a level strength gradient, the gradient calculation uses a central difference method for the grid Gradient component thereof in x-direction and y-directionAndCan be expressed as:
;
;
Wherein, the 、As gradient components (units: dB/m),Is a gridSignal strength (unit: dBm),,Is the grid spacing (unit: m, in general)). The grid spacing is set to be 100m, the signal intensity value (unit: dBm) of a certain 3×3 grid area is-55 (1, 1), -58 (1, 2), -60 (1, 3), -53 (2, 1), -52 (2, 2), -57 (2, 3), -54 (3, 1), -56 (3, 2), -59 (3, 3), the gradient of the central grid (2, 2) is calculated, and the set value is substituted for calculation:
;
;
the calculation results show that the signal strength at the center grid (2, 2) decreases at a rate of 0.02dB/m in the x-direction and increases at a rate of 0.01dB/m in the y-direction. The magnitude and direction of the gradient reflect the change trend of the signal intensity, the region with larger gradient usually corresponds to the position of the signal source or an obstacle on the signal propagation path, the signal intensity is visualized by using color mapping in combination with the corrected signal intensity value according to the calculated gradient information, and a gradient color level from red (high signal intensity) to blue (low signal intensity) is usually adopted to generate an electromagnetic spectrum situation map, so that the intensity distribution and the change trend of the electromagnetic signals in the region are intuitively displayed.
The present invention is not limited to the above embodiments, and any equivalent embodiments which can be changed or modified by the technical disclosure described above can be applied to other fields, but any simple modification, equivalent changes and modification made to the above embodiments according to the technical matter of the present invention will still fall within the scope of the technical disclosure.
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