CN112929103A - Illegal broadcasting station detection method and system - Google Patents
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Abstract
The invention provides a method and a system for detecting an illegal broadcasting station, which are used for solving the problems of large workload and low positioning speed of searching illegal broadcasting signals in the prior art. The detection method comprises the steps of searching broadcast signals of an FM frequency band in a detection area through an intelligent frequency point search algorithm, determining a central frequency point of the broadcast signals, automatically and uninterruptedly monitoring 16-64 paths of broadcast signals through a multichannel analysis module under a 40MHz bandwidth with the central frequency point as a center, carrying out DDC analysis, identifying illegal broadcast signals in the searched broadcast signals, and finally carrying out direction finding and positioning on transmitting equipment of the identified illegal broadcast signals according to direction finding equipment and a positioning algorithm. The method and the device perform in-depth monitoring on the important frequency band from 88MHz to 108MHz, separate direction finding on a plurality of different incoming signals with same frequency aliasing, have quicker identification and more accurate positioning, and improve the detection efficiency of illegal broadcasting stations.
Description
Technical Field
The invention belongs to the field of radio safety, and particularly relates to an illegal broadcasting station detection method and system.
Background
An illegal broadcasting station is an illegal broadcasting station which is not approved by a broadcasting television management department and a radio management organization and is set to propagate to the society by using broadcasting frequency, and is commonly called black broadcasting. Because of no supervision, the research and development cost of radio transmitting equipment is reduced day by day, and illegal broadcasting stations are set privately by lawless persons in large quantities and are used for selling fake medicines and deceiving money and money, so that the social order is seriously disturbed, and the normal life of people is disturbed.
In the prior art, monitoring of illegal broadcasting stations is generally carried out by monitoring personnel by utilizing a fixed monitoring station to carry out full-band monitoring on broadcasting frequency bands, and whether a transmitted signal is illegal or not is confirmed by comparing a legal station library and verifying broadcasting contents. The positioning of the illegal broadcasting station is mainly realized by carrying out direction finding or positioning on the illegal broadcasting station through a plurality of fixed monitoring stations, locking a rough area, approaching and searching by utilizing a mobile monitoring vehicle, and finally determining the actual position of the illegal broadcasting transmitting equipment by monitoring personnel carrying portable equipment. As shown in fig. 1, currently, due to factors such as limited coverage of a monitoring station and multipath effect of signals, a radio monitoring person has a large error in positioning an illegal broadcasting station, which brings great difficulty to a search operation. Meanwhile, the full-band monitoring workload is large, and the monitoring accuracy is not improved.
Disclosure of Invention
In view of the above problems, embodiments of the present invention provide a method and a system for detecting an illegal broadcasting station, after searching for a broadcasting signal, the illegal broadcasting signal in the broadcasting signal is identified analytically based on a multi-channel of a central frequency point, and then the illegal broadcasting is located and law enforcement is performed through a direction finding and locating algorithm, so that the broadcasting frequency bandwidth is covered, intelligent search of the frequency point is realized, the identification is accurate, the precision is high, automatic discrimination and quick location are realized through adaptive multi-channel analysis, and the detection accuracy and the attack strength of the illegal broadcasting station are improved.
In order to achieve the above purpose, the embodiment of the present invention adopts the following technical solutions:
in a first aspect, an embodiment of the present invention provides an illegal broadcasting station detection method, where the method includes the following steps:
step S1, searching broadcast signals of FM frequency bands in the detection area through an intelligent frequency point search algorithm, and determining the center frequency point of the broadcast signals;
step S2, under the bandwidth of 40MHz taking the central frequency point as the center, the multi-channel analysis module automatically and uninterruptedly monitors the 16-64 channels of broadcast signals, and carries out DDC analysis to identify illegal broadcast signals in the searched broadcast signals;
and step S3, carrying out direction finding and positioning on the transmitting equipment of the identified illegal broadcast signals.
As a preferred embodiment of the present invention, the step S1 specifically includes:
step S11, dividing FM frequency bands in the detection area into 88-108 Mhz;
step S12, processing the continuous N-frame frequency spectrum into one frame in a multi-frame averaging mode in the FM frequency band to obtain the average frequency spectrum data of the full frequency band;
step S13, smoothing the average spectrum data;
step S14, segmenting the smoothed spectrum data, determining a threshold line, and determining a spectrum region larger than the threshold line as a signal region;
in step S15, the center frequency point of the signal is determined in the determined signal region.
As a preferred embodiment of the present invention, in the smoothing processing in step S13, a five-point three-pass smoothing filter algorithm with settable parameters is adopted, and small "glitches" are smoothed by setting relevant parameters, and the discrimination of signals close to each other is not affected; the algorithm formula (2) is as follows:
and n is not less than 2 (2);
in the formula (2), Y0、Y1、Y2、Y-1、Y-2Respectively representing original frequency spectrum signals received by a system, wherein the number of the signals is n, and the signals are from 0 th to n-1 th;
respectively representing new frequency spectrum data after five-point three-time smoothing filter algorithm operation shown by a formula.
As a preferred embodiment of the present invention, the step S14 is to determine the threshold line, and the specific steps are as follows:
step S141, calculating frequency points corresponding to peaks and troughs of the preprocessed frequency spectrum, and calculating the average value of all trough levels;
step S142, determining a segmentation point, and segmenting the frequency spectrum according to the segmentation point; making a difference value between the peak and the trough of a certain point, comparing the absolute value of the difference value with the judgment experience value, and if the difference value of the point is smaller than the judgment experience value and the trough value of the point is smaller than the average value of the trough levels, the point is a segmented point;
step S143, let any section of frequency spectrum be M (n), n is the number of frequency points on this section; firstly, adding a moving value L to M (n) frequency spectrum data, wherein L is min [ M (n) ], and the moved data is S (n); the operation process is as formula (3):
S(n)＝M(n)+L (3)；
step S144, removing partial 'extra large' values in S (n) by using a K-means clustering algorithm, wherein the K-means clustering algorithm is used for clustering the S (n) into A, B classes, the initial clustering center point of the class A is the average value of the S (n), the initial clustering center point of the class B is the maximum value in the S (n), then the average value of the A, B classes clustered each time is used as a new clustering center, when the error between the new clustering center and the last clustering center is less than 0.01, the stopping is carried out, then the values in the class B are all replaced by the minimum value in the class B, and the data after clustering is made to be A (n);
step S145, performing K-means clustering again on A (n), taking the minimum value, the maximum value and the mean value of A (n) as clustering centers, clustering the A (n) into three types R, T and U, replacing the value smaller than the R type center value in A (n) with the R type center value, and replacing the value larger than the T type center value in A (n) with the T type center value to obtain new data X (n);
step S146, subtracting the previous moving amount L from the obtained X (n) to obtain P (n), wherein the operation process is as the formula (4):
P(n)＝X(n)-L (4)；
step S147, determining a noise threshold K, the determining method includes: firstly, calculating the variance Q of M (n) and N (n), and carrying out mean square error processing on the variance, wherein the formula is (5):
and adding P (n) to the obtained noise threshold K to be used as a finally determined self-adaptive dynamic threshold line F. In this step, in order to more accurately threshold the threshold line, the offset may be added appropriately;
the dynamic threshold line F is obtained according to the following formula (6):
F＝P(n)+K+offset (6)；
and step S148, splicing the self-adaptive dynamic threshold lines of each section to obtain the self-adaptive dynamic threshold line of the whole monitoring frequency band.
As a preferred embodiment of the present invention, the step S15 determines the center frequency point of the signal as follows:
step S151, preprocessing a plurality of continuous frames into a frame in sequence, and obtaining a plurality of preprocessed frequency spectrums in a statistical time interval;
step S152, finding out the frequency points which are judged as the central frequency on the preprocessed frequency spectrums, counting the frequency points, and taking the point which is judged as the central frequency as a signal area based on the dynamic threshold line which is obtained in the prior art and is larger than the threshold line;
step S153, determining a signal discrimination threshold T by equation (7):
T＝M×18％ (7)；
in the formula (7), T is a discrimination threshold, M is the total frame number of the frequency spectrum after preprocessing in statistical time, and 18% is an empirical value;
and step S154, comparing the statistic with T, taking the area larger than T as the most possible area of the central frequency of the signal, and taking the point corresponding to the maximum value in each area as the central frequency point of the signal.
As a preferred embodiment of the present invention, in step S3, when positioning the transmitting device, multiple signal direction finding is adopted, and multiple different direction finding signals with same frequency aliasing are separately direction finding.
In a second aspect, an embodiment of the present invention further provides an illegal broadcasting station detection system, where the system includes an intelligent frequency point search module, an illegal broadcasting signal identification module, and an illegal signal positioning module, which are in communication connection in sequence; wherein the content of the first and second substances,
the intelligent frequency point searching module is in communication connection with the illegal broadcast signal identification module and is used for searching broadcast signals of FM frequency bands in a detection area through an intelligent frequency point searching algorithm, determining a central frequency point of the broadcast signals and sending the determined central frequency point to the illegal broadcast signal identification module;
the illegal broadcast signal identification module is used for importing station database data, automatically and uninterruptedly monitoring 16-64 paths of broadcast signals through the multichannel analysis module under a preset bandwidth with the central frequency point as the center, carrying out DDC analysis and identifying illegal broadcast signals in the searched broadcast signals;
the illegal signal positioning module is used for monitoring the illegal broadcast signals identified by the identification module at any time and positioning the transmitting equipment of the identified illegal broadcast signals.
As a preferred embodiment of the present invention, the intelligent frequency point searching module includes a frequency band dividing sub-module, a multi-frame averaging sub-module, a spectrum data preprocessing sub-module, a signal region determining sub-module, and a central frequency point determining sub-module, which are sequentially connected in a communication manner; wherein the content of the first and second substances,
the frequency band division submodule is used for dividing the FM frequency band in the detection area into 88-108 Mhz; the multi-frame averaging submodule is used for processing the continuous N-frame frequency spectrum into one frame in an FM frequency band in a multi-frame averaging mode to obtain average frequency spectrum data of a full frequency band; the frequency spectrum data preprocessing submodule is used for carrying out smoothing processing on the average frequency spectrum data; the signal area judgment submodule is used for segmenting the frequency spectrum data after the smoothing processing, determining a threshold line and judging the frequency spectrum area larger than the threshold line as a signal area; and the central frequency point determining submodule is used for monitoring the peak value in the signal area and determining the central frequency point.
As a preferred embodiment of the present invention, the detection system further comprises: the system comprises a statistical analysis module, a data management module, a system management module and a geographic information display module; wherein the content of the first and second substances,
the statistical analysis module is in communication connection with the illegal broadcast signal identification module and the illegal signal positioning module, is connected with the geographic information display module, is used for counting the number of illegal broadcast signals according to days, months and years, sends the counting result to the geographic information display module, displays the counting result by using a preset graph and a preset chart, generates an illegal broadcast radio station development trend graph, is provided with an external application interface, and leads out a monitoring monthly report document; the system is also used for counting the illegal broadcast keywords, and the occurrence times are used as a vertical coordinate, the time is used as a horizontal coordinate, and the illegal broadcast keywords are displayed in a form of a histogram;
the geographic information display module is in communication connection with the statistical analysis module and is used for displaying the identification and positioning results of the illegal broadcast signals in real time and the statistical analysis results of the statistical analysis module;
the data management module is in communication connection with the illegal broadcast signal identification module and is used for managing and importing station data into a station database and storing the data, checking current station data information in real time, adding, deleting, modifying and checking the station data information and providing data support for identification of illegal broadcast signals; and for managing the identified illegal broadcast signals, comprising: checking the related information of the current illegal broadcast signal in real time, adding, deleting, modifying and checking the data information of the illegal broadcast signal, selecting one piece of illegal broadcast information, performing voice playing and checking voice recognition information; the system is also used for voice data management, all broadcast frequency point voice data are stored in real time, the voice data stored on a certain date of a certain device are checked in real time, voice records are selected for real-time playing, and voice data are added, deleted and checked;
the system management module is in communication connection with all other modules at the same time, and is used for managing login users and authorizing different users to access different modules to perform corresponding operations; the system is also used for monitoring station management, which comprises station management, equipment management, parameter management and log management.
The invention has the following beneficial effects:
according to the illegal broadcasting station detection method and system provided by the embodiment of the invention, stations which are built or are built in provinces and cities at present are used as infrastructure, deep monitoring is carried out on key frequency bands from 88MHz to 108MHz, the central frequency point of a broadcasting signal is accurately determined through an intelligent broadcasting signal search algorithm, the illegal broadcasting signal is identified based on a station database, and the positioning of the signal is realized through direction-finding equipment and a positioning algorithm, so that the detection efficiency of the illegal broadcasting station is improved, the identification is quicker, and the positioning is more accurate.
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In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
FIG. 1 is a flow chart of illegal broadcast detection in the prior art;
fig. 2 is a flowchart of an illegal broadcasting station detection method according to an embodiment of the present invention;
FIG. 3 is a flowchart illustrating signal searching in the illegal broadcasting station detection method according to the present invention;
FIG. 4 is a comparison of the spectrum signal before and after filtering in the illegal broadcasting station detection method according to the present invention;
FIG. 5 is a flow chart of signal identification in the illegal broadcasting station detection method according to the present invention;
FIG. 6 is a diagram illustrating an example of adaptive threshold lines in the illegal broadcast station detection method according to the present invention;
FIG. 7 is a block diagram of an illegal broadcasting station detection system according to the present invention.
Detailed Description
The technical problems, aspects and advantages of the invention will be apparent from the following detailed description, which proceeds with reference to the accompanying drawings, when taken in conjunction with the accompanying exemplary embodiments. The following exemplary embodiments are merely illustrative of the present invention and are not to be construed as limiting the invention. It will be understood by those skilled in the art that, unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. It will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the prior art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.
The embodiment of the invention provides an illegal broadcasting station detection method. As shown in fig. 2, the illegal broadcasting station detection method includes the following steps:
step S1, searching broadcast signals of FM frequency bands in the detection area through an intelligent frequency point search algorithm, and determining the center frequency point of the broadcast signals.
As shown in fig. 3, the present step specifically includes:
step S11, the FM frequency band in the detection area is divided into 88-108 Mhz.
In the step, integer frequency is adopted for convenient algorithm calculation. In the actual detection, the real frequency band of 87.5-108 Mhz can be used according to the actual situation.
And step S12, processing the continuous N-frame frequency spectrum into one frame in a multi-frame averaging mode in the FM frequency band to obtain the average frequency spectrum data of the full frequency band.
Because the radio broadcast frequency spectrum does not change greatly in a short time, frequency point searching is not required to be carried out on each frame; meanwhile, each frame (each frame is 3200 points) obtained by the frequency spectrum data has slight changes of different degrees, and if a single frame is subjected to frequency point search, the error of the search result is large, so that the continuous N-frame frequency spectrum needs to be subjected to average processing, the continuous N-frame frequency spectrum is processed into one frame, and multi-frame maintenance is realized, so that the calculation amount of frequency point search can be reduced, and the error of the frequency point search result can also be greatly reduced. The value of N is given according to actual conditions or experience.
Wherein, the averaging of the continuous N frames of frequency spectrum is performed by adopting an equation (1):
Dav(K)＝(d1(k)+d2(k)+...+dm(k))/m (1)
in the formula (1), m is the number of frames to be averaged, dm(k) For each frame of input data, Dav(K) Averaging multiple frames to synthesize one frame.
Step S13, smoothing the average spectrum data.
In this step, small "burrs" may appear at some adjacent points of the average spectrum data obtained by multi-frame averaging, and the frequency spectrum smoothing is performed to avoid affecting the judgment of the frequency point peak value.
The frequency spectrum smoothing processing adopts a five-point three-time smoothing filtering algorithm with settable parameters, small 'burrs' can be smoothed by setting related parameters, and the judgment of signals with relatively close distances is not influenced. The algorithm formula (2) is as follows:
and n is not less than 2(2)
In the formula (2), Y0、Y1、Y2、Y3、Y4…YnThe original spectrum signals received by the system are represented respectively, the number of the signals is n, from the 0 th to the n-1 th, the original spectrum contains original data of each frequency, and the original data contains normal legal broadcast signals, illegal black broadcast signals, interference noise in the external environment, signal spurs generated by different receivers and false signals generated by external resonance. While
The new spectrum data obtained after the formula algorithm operation, namely the new spectrum data obtained after the five-point cubic smoothing filtering algorithm filtering, is represented, noise waves such as noise, stray waves, false signals and the like are completely filtered by the new spectrum, and the truest electromagnetic signals are restored, so that illegal signals can be quickly and effectively screened.
As shown in fig. 4, the filtered signals are compared before and after, and it can be seen that after the filtering process, the noise in the original data is filtered out, and the spectrum data becomes smooth.
In step S14, the smoothed spectrum data is segmented, a threshold line is determined, and a spectrum region larger than the threshold line is determined as a signal region.
In this step, the signal region is determined by the size of the spectrum data and the threshold line, and the spectrum region larger than the threshold line is the signal region, so that it can be known in advance which frequency points on the spectrum are determined as signal center frequency points.
And segmenting the smoothed frequency spectrum data, and segmenting the scanning frequency spectrum of a longer frequency band into a plurality of segments by adopting self-adaptive segmentation.
The method for determining the threshold line comprises the following specific steps:
step S141, calculating frequency points corresponding to peaks and troughs of the preprocessed spectrum, and calculating an average value of all trough levels.
And step S142, determining a segmentation point, and segmenting the frequency spectrum according to the segmentation point.
Specifically, the peak and the trough of a certain point are differentiated, the absolute value of the difference is compared with the discriminant empirical value, and if the difference of the point is smaller than the discriminant empirical value and the trough value of the point is smaller than the average value of the trough levels, the point is a segmentation point. The discriminant empirical value in this step is determined according to simulation. Preferably, the value of the discriminant experience value is 5. The segmentation point determined by the method can effectively avoid uniform segmentation to segment the same signal, avoid the noise step effect on a wider frequency band, and improve the reliability and accuracy of segmentation.
Step S143, let any section of frequency spectrum be M (n), n is the number of frequency points on this section; firstly, a shift value L is added to m (n) spectrum data, where L is min [ m (n) ], and the shifted data is s (n). The operation process is as formula (3):
S(n)＝M(n)+L (3)
step S144, removing partial 'extra large' values in S (n) by using a K-means clustering algorithm, wherein the K-means clustering algorithm is used for clustering the S (n) into A, B classes, the initial clustering center point of the class A is the average value of the S (n), the initial clustering center point of the class B is the maximum value in the S (n), then the average value of the A, B classes clustered each time is used as a new clustering center, when the error between the new clustering center and the last clustering center is less than 0.01, the new clustering center is stopped, then the values in the class B are all replaced by the minimum value in the class B, and the data after clustering is made to be A (n).
Step S145, performing K-means clustering again on A (n), taking the minimum value, the maximum value and the mean value of A (n) as the clustering centers, clustering the A (n) into three types R, T and U, replacing the value smaller than the R type center value in A (n) with the R type center value, and replacing the value larger than the T type center value in A (n) with the T type center value to obtain new data X (n).
Step S146, subtracting the previous moving amount L from the obtained X (n) to obtain P (n), wherein the operation process is as the formula (4):
P(n)＝X(n)-L (4)
step S147, determining a noise threshold K, the determining method includes: firstly, calculating the variance Q of M (n) and N (n), and carrying out mean square error processing on the variance, wherein the formula is (5):
and adding P (n) to the obtained noise threshold K to be used as a finally determined self-adaptive dynamic threshold line F. In this step, an offset may be added as appropriate for more accurate threshold line. Preferably, the offset amount is set to 2.5< ═ offset < > 5.
The dynamic threshold line F is obtained according to the following formula (6):
F＝P(n)+K+offset (6)
as shown in fig. 5, the dynamic threshold line F fluctuates with noise fluctuations.
And step S148, splicing the self-adaptive dynamic threshold lines of each section to obtain the self-adaptive dynamic threshold line of the whole monitoring frequency band.
And step S15, determining the center frequency point of the signal.
On the basis of judging that the region larger than the threshold line is the signal region, the maximum value (peak value) of each region is calculated, and the frequency points on the frequency spectrum are estimated to be judged as signal center frequency points. In order to avoid frequency offset of FM broadcast and improve accuracy of signal search, the process of determining the center frequency point of a signal is as follows:
step S151, sequentially pre-process a plurality of continuous frames (five or ten frames) into one frame, and a plurality of pre-processed frequency spectrums are obtained within a statistical period.
Step S152, finding out the frequency points which are judged as the central frequency on the preprocessed frequency spectrums, counting the frequency points, and taking the point which is judged as the central frequency based on the dynamic threshold line obtained in the previous step and being larger than the threshold line as a signal area.
Step S153, a signal discrimination threshold T is determined.
In this step, a signal discrimination threshold T is determined by equation (7):
T＝M×18％ (7)
in the formula (7), T is a discrimination threshold, M is the total frame number of the spectrum after preprocessing in statistical time, and 18% is an empirical value (which can be determined by simulation).
And step S154, comparing the statistic with T, taking the area larger than T as the most possible area of the central frequency of the signal, and taking the point corresponding to the maximum value in each area as the central frequency point of the signal.
And step S2, under the bandwidth of 40MHz taking the central frequency point as the center, the multi-channel analysis module automatically and uninterruptedly monitors the 16-64 channels of broadcast signals, performs DDC analysis and identifies illegal broadcast signals in the searched broadcast signals.
As shown in fig. 6, in this step, on the basis of finding broadcast signals, measurement and monitoring are required for each broadcast signal, and in combination with a station database, separation between legitimate broadcast signals and illegitimate broadcast signals is achieved through various means such as signal characteristic (signal bandwidth, working time, etc.) comparison, spatial spectrum direction finding, TDOA positioning, and voice recognition. The medium frequency analysis (medium frequency measurement) function in the non-commission conventional monitoring function supports single frequency point measurement and monitoring and can be used for supporting and identifying illegal broadcasting. The medium frequency analysis (medium frequency measurement) function is limited to single frequency point measurement and monitoring, multi-channel broadcast frequency point simultaneous measurement and monitoring can not be carried out, the multi-channel analysis function in series products developed by the department supports multi-channel in-band DDC analysis under a 40MHz broadband under a central frequency point, 16-channel (maximally expandable to 64 channels) broadcast signals can be automatically and uninterruptedly monitored, the DDC analysis comprises ITU parameter measurement, spectrum analysis and demodulation output, and multi-channel narrow-band simultaneous direction finding is supported by selecting equipment supporting the direction finding function.
Step S3, locating the transmitting device of the identified illegal broadcast signal.
In this step, the positioning of the signal is realized by a special direction-finding device and a positioning algorithm. When the transmitting equipment is positioned, multi-signal direction finding is adopted, and a plurality of different direction-finding signals with same frequency aliasing are separated and subjected to direction finding, so that the positioning is more accurately realized, and the detection efficiency is improved.
The embodiment of the invention also provides an illegal broadcasting station detection system, which comprises an intelligent frequency point searching module, an illegal broadcasting signal identification module and an illegal signal positioning module which are sequentially in communication connection, as shown in fig. 7. The intelligent frequency point searching module is used for searching broadcast signals of FM frequency bands in the detection area through an intelligent frequency point searching algorithm, determining a central frequency point of the broadcast signals, and sending the determined central frequency point to the illegal broadcast signal identification module; the illegal broadcast signal identification module is used for importing station database data, automatically and uninterruptedly monitoring 16-64 paths of broadcast signals through the multichannel analysis module under the 40MHz bandwidth taking the central frequency point as the center, carrying out DDC analysis and identifying illegal broadcast signals in the searched broadcast signals; the illegal signal positioning module is used for monitoring the illegal broadcast signals identified by the identification module at any time and positioning the transmitting equipment of the identified illegal broadcast signals.
The intelligent frequency point searching module comprises a frequency band dividing submodule, a multi-frame averaging submodule, a frequency spectrum data preprocessing submodule, a signal area judging submodule and a central frequency point determining submodule which are sequentially in communication connection. The frequency band division submodule is used for dividing the FM frequency band in the detection area into 88-108 Mhz; the multi-frame averaging submodule is used for processing the continuous N-frame frequency spectrum into one frame in an FM frequency band in a multi-frame averaging mode to obtain average frequency spectrum data of a full frequency band; the frequency spectrum data preprocessing submodule is used for carrying out smoothing processing on the average frequency spectrum data; the signal area judgment submodule is used for segmenting the frequency spectrum data after the smoothing processing, determining a threshold line and judging the frequency spectrum area larger than the threshold line as a signal area; and the central frequency point determining submodule is used for monitoring the peak value in the signal area and determining the central frequency point.
The illegal broadcasting station detection system further comprises: the system comprises a statistical analysis module, a data management module, a system management module and a geographic information display module.
The statistical analysis module is in communication connection with the illegal broadcast signal identification module and the illegal signal positioning module, is connected with the geographic information display module, is used for counting the number of illegal broadcast signals according to days, months and years, sends the counting result to the geographic information display module, displays the counting result by using a preset graph and a preset chart, generates an illegal broadcast radio station development trend graph, is provided with an external application interface, and leads out a monitoring monthly report document; and the method is also used for counting illegal broadcast keywords, and the occurrence times are used as a vertical coordinate, the time is used as a horizontal coordinate, and the illegal broadcast keywords are displayed in a form of a histogram.
The geographic information display module is in communication connection with the statistical analysis module and is used for displaying the identification and positioning results of the illegal broadcast signals in real time and the statistical analysis results of the statistical analysis module. When the positioning result is displayed, the conventional functions of the map, such as map selection, map marking, dragging, eagle eye, zooming, layered display, measurement, editing and the like, and map operation functions of backing, advancing, zooming in, zooming out, roaming, map full view, map centering and the like are included. When the illegal broadcast signal identification result is displayed, the current equipment monitoring broadcast frequency point information can be checked by operating a click site, and voice can be played in real time and spectrum information can be checked on line by clicking a certain broadcast frequency point.
The data management module is in communication connection with the illegal broadcast signal identification module and is used for managing and importing station data into a station database and storing the data, checking current station data information in real time, adding, deleting, modifying and checking the station data information and providing data support for identification of illegal broadcast signals; and for managing the identified illegal broadcast signals, comprising: checking the related information of the current illegal broadcast signal in real time, adding, deleting, modifying and checking the data information of the illegal broadcast signal, selecting one piece of illegal broadcast information, performing voice playing and checking voice recognition information; the method is also used for voice data management, all broadcast frequency point voice data are stored in real time, voice data stored on a certain date of a certain device are checked in real time, voice records are selected for real-time playing, and voice data are added, deleted and checked.
The system management module is in communication connection with all other modules at the same time, and is used for managing login users and authorizing different users to access different modules to perform corresponding operations. The users are classified into two categories: an administrator and an operator, both of which can be operating users. For example, an authorized administrator user adds a user, deletes a user, and modifies user information; the authorized operator can modify the password for logging in. The newly added function adds a piece of user information in time, wherein the user information comprises information such as a user name, authority, secrets, remarks and the like; the modification function is to select a user information double-click or click a modification button to modify the user information including modification authority, password and remark; the delete function is to delete a piece of user information.
The system management module is also used for monitoring station management, which comprises station management, equipment management, parameter management and log management, and is used for the system to configure and manage other modules, and comprises the following steps:
setting parameters of the control center: in the RMTP protocol, the state adopts uniform numbers and names for all levels of monitoring control centers, and the current monitoring center is arranged; the monitoring center is the existing illegal broadcasting station monitoring center; the log management includes querying records of various real-time operations, for example, after a start date and an end date are input, relevant log information can be displayed by clicking a query button, and the like. It should be noted that the illegal broadcasting station detection method provided by the embodiment of the present invention is related to the detection system, and the detection method is implemented by the detection system, so that the description and limitation of the method are also applicable to the detection system, the description of the system is also applicable to the detection method, and the overlapping technical features of the two are not repeatedly described.
According to the technical scheme, the illegal broadcasting station detection method and the illegal broadcasting station detection system provided by the embodiment of the invention utilize the station which is built or is built in each province and city as infrastructure, and specially aim at the heavy point frequency band from 88MHz to 108MHz and the like to carry out deep monitoring, so that the detection efficiency of the illegal broadcasting station is improved, the identification is faster, and the positioning is more accurate.
While the foregoing is directed to the preferred embodiment of the present invention, it is understood that the invention is not limited to the exemplary embodiments disclosed, but is made merely for the purpose of providing those skilled in the relevant art with a comprehensive understanding of the specific details of the invention. It will be apparent to those skilled in the art that various modifications and adaptations of the present invention can be made without departing from the principles of the invention and the scope of the invention is to be determined by the claims.
Claims (9)
1. A method for detecting an illegal broadcast station, the method comprising the steps of:
step S1, searching broadcast signals of FM frequency bands in the detection area through an intelligent frequency point search algorithm, and determining the center frequency point of the broadcast signals;
step S2, under the bandwidth of 40MHz taking the central frequency point as the center, the multi-channel analysis module automatically and uninterruptedly monitors the 16-64 channels of broadcast signals, and carries out DDC analysis to identify illegal broadcast signals in the searched broadcast signals;
and step S3, carrying out direction finding and positioning on the transmitting equipment of the identified illegal broadcast signals.
2. The method of claim 1, wherein the step S1 includes:
step S11, dividing FM frequency bands in the detection area into 88-108 Mhz;
step S12, processing the continuous N-frame frequency spectrum into one frame in a multi-frame averaging mode in the FM frequency band to obtain the average frequency spectrum data of the full frequency band;
step S13, smoothing the average spectrum data;
step S14, segmenting the smoothed spectrum data, determining a threshold line, and determining a spectrum region larger than the threshold line as a signal region;
in step S15, the center frequency point of the signal is determined in the determined signal region.
3. The illegal broadcasting station detection method according to claim 2, wherein the smoothing processing of step S13 adopts a five-point three-times smoothing filter algorithm with settable parameters, and smoothes out small "glitches" by setting relevant parameters, and does not affect the discrimination of signals with close distance; the algorithm formula (2) is as follows:
and n is not less than 2 (2);
in the formula (2), Y0、Y1、Y2、Y-1、Y-2Respectively representing original frequency spectrum signals received by a system, wherein the number of the signals is n, and the signals are from 0 th to n-1 th;
respectively representing new frequency spectrum data after five-point three-time smoothing filter algorithm operation shown by a formula.
4. The method as claimed in claim 3, wherein the step S14 of determining the threshold line comprises the following steps:
step S141, calculating frequency points corresponding to peaks and troughs of the preprocessed frequency spectrum, and calculating the average value of all trough levels;
step S142, determining a segmentation point, and segmenting the frequency spectrum according to the segmentation point; making a difference value between the peak and the trough of a certain point, comparing the absolute value of the difference value with the judgment experience value, and if the difference value of the point is smaller than the judgment experience value and the trough value of the point is smaller than the average value of the trough levels, the point is a segmented point;
step S143, let any section of frequency spectrum be M (n), n is the number of frequency points on this section; firstly, adding a moving value L to M (n) frequency spectrum data, wherein L is min [ M (n) ], and the moved data is S (n); the operation process is as formula (3):
S(n)＝M(n)+L (3)；
step S144, removing partial 'extra large' values in S (n) by using a K-means clustering algorithm, wherein the K-means clustering algorithm is used for clustering the S (n) into A, B classes, the initial clustering center point of the class A is the average value of the S (n), the initial clustering center point of the class B is the maximum value in the S (n), then the average value of the A, B classes clustered each time is used as a new clustering center, when the error between the new clustering center and the last clustering center is less than 0.01, the stopping is carried out, then the values in the class B are all replaced by the minimum value in the class B, and the data after clustering is made to be A (n);
step S145, performing K-means clustering again on A (n), taking the minimum value, the maximum value and the mean value of A (n) as clustering centers, clustering the A (n) into three types R, T and U, replacing the value smaller than the R type center value in A (n) with the R type center value, and replacing the value larger than the T type center value in A (n) with the T type center value to obtain new data X (n);
step S146, subtracting the previous moving amount L from the obtained X (n) to obtain P (n), wherein the operation process is as the formula (4):
P(n)＝X(n)-L (4)；
step S147, determining a noise threshold K, the determining method includes: firstly, calculating the variance Q of M (n) and N (n), and carrying out mean square error processing on the variance, wherein the formula is (5):
adding P (n) to the obtained noise threshold K to be used as a finally determined self-adaptive dynamic threshold line F;
the dynamic threshold line F is obtained according to the following formula (6):
F＝P(n)+K+offset (6)；
and step S148, splicing the self-adaptive dynamic threshold lines of each section to obtain the self-adaptive dynamic threshold line of the whole monitoring frequency band.
5. The method for detecting the illegal broadcasting station according to claim 4, wherein the step S15 is performed by determining the center frequency point of the signal as follows:
step S151, preprocessing a plurality of continuous frames into a frame in sequence, and obtaining a plurality of preprocessed frequency spectrums in a statistical time interval;
step S152, finding out the frequency points which are judged as the central frequency on the preprocessed frequency spectrums, counting the frequency points, and taking the point which is judged as the central frequency as a signal area based on the dynamic threshold line which is obtained in the prior art and is larger than the threshold line;
step S153, determining a signal discrimination threshold T by equation (7):
T＝M×18％ (7)；
in the formula (7), T is a discrimination threshold, M is the total frame number of the frequency spectrum after preprocessing in statistical time, and 18% is an empirical value;
and step S154, comparing the statistic with T, taking the area larger than T as the most possible area of the central frequency of the signal, and taking the point corresponding to the maximum value in each area as the central frequency point of the signal.
6. The method as claimed in any one of claims 1 to 5, wherein in step S3, when positioning the transmitter, multi-signal direction finding is adopted to separate direction finding signals of different directions with aliasing.
7. An illegal broadcasting station detection system comprises an illegal broadcasting signal identification module and an illegal signal positioning module which are in communication connection; the system is characterized by also comprising an intelligent frequency point searching module;
the intelligent frequency point searching module is in communication connection with the illegal broadcast signal identification module and is used for searching broadcast signals of FM frequency bands in a detection area through an intelligent frequency point searching algorithm, determining a central frequency point of the broadcast signals and sending the determined central frequency point to the illegal broadcast signal identification module;
the illegal broadcast signal identification module is used for importing station database data, automatically and uninterruptedly monitoring 16-64 paths of broadcast signals through the multichannel analysis module under a preset bandwidth with the central frequency point as the center, carrying out DDC analysis and identifying illegal broadcast signals in the searched broadcast signals;
the illegal signal positioning module is used for monitoring the illegal broadcast signals identified by the identification module at any time and positioning the transmitting equipment of the identified illegal broadcast signals.
8. The illegal broadcasting station detection system according to claim 7, wherein the intelligent frequency point search module comprises a frequency division submodule, a multi-frame averaging submodule, a spectrum data preprocessing submodule, a signal area determination submodule and a central frequency point determination submodule which are in communication connection in sequence; wherein the content of the first and second substances,
the frequency band division submodule is used for dividing the FM frequency band in the detection area into 88-108 Mhz; the multi-frame averaging submodule is used for processing the continuous N-frame frequency spectrum into one frame in an FM frequency band in a multi-frame averaging mode to obtain average frequency spectrum data of a full frequency band; the frequency spectrum data preprocessing submodule is used for carrying out smoothing processing on the average frequency spectrum data; the signal area judgment submodule is used for segmenting the frequency spectrum data after the smoothing processing, determining a threshold line and judging the frequency spectrum area larger than the threshold line as a signal area; and the central frequency point determining submodule is used for monitoring the peak value in the signal area and determining the central frequency point.
9. The illegal broadcasting station detection system according to claim 8, further comprising: the system comprises a statistical analysis module, a data management module, a system management module and a geographic information display module; wherein the content of the first and second substances,
the statistical analysis module is in communication connection with the illegal broadcast signal identification module and the illegal signal positioning module, is connected with the geographic information display module, is used for counting the number of illegal broadcast signals according to days, months and years, sends the counting result to the geographic information display module, displays the counting result by using a preset graph and a preset chart, generates an illegal broadcast radio station development trend graph, is provided with an external application interface, and leads out a monitoring monthly report document; the system is also used for counting the illegal broadcast keywords, and the occurrence times are used as a vertical coordinate, the time is used as a horizontal coordinate, and the illegal broadcast keywords are displayed in a form of a histogram;
the geographic information display module is in communication connection with the statistical analysis module and is used for displaying the identification and positioning results of the illegal broadcast signals in real time and the statistical analysis results of the statistical analysis module;
the data management module is in communication connection with the illegal broadcast signal identification module and is used for managing and importing station data into a station database and storing the data, checking current station data information in real time, adding, deleting, modifying and checking the station data information and providing data support for identification of illegal broadcast signals; and for managing the identified illegal broadcast signals, comprising: checking the related information of the current illegal broadcast signal in real time, adding, deleting, modifying and checking the data information of the illegal broadcast signal, selecting one piece of illegal broadcast information, performing voice playing and checking voice recognition information; the system is also used for voice data management, all broadcast frequency point voice data are stored in real time, the voice data stored on a certain date of a certain device are checked in real time, voice records are selected for real-time playing, and voice data are added, deleted and checked;
the system management module is in communication connection with all other modules at the same time, and is used for managing login users and authorizing different users to access different modules to perform corresponding operations; the system is also used for monitoring station management, which comprises station management, equipment management, parameter management and log management.
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