CN105871482B - A kind of monitoring method of fm broadcast signal - Google Patents
A kind of monitoring method of fm broadcast signal Download PDFInfo
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- CN105871482B CN105871482B CN201610369831.5A CN201610369831A CN105871482B CN 105871482 B CN105871482 B CN 105871482B CN 201610369831 A CN201610369831 A CN 201610369831A CN 105871482 B CN105871482 B CN 105871482B
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04B—TRANSMISSION
- H04B17/00—Monitoring; Testing
- H04B17/30—Monitoring; Testing of propagation channels
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04H—BROADCAST COMMUNICATION
- H04H20/00—Arrangements for broadcast or for distribution combined with broadcast
- H04H20/12—Arrangements for observation, testing or troubleshooting
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04H—BROADCAST COMMUNICATION
- H04H60/00—Arrangements for broadcast applications with a direct linking to broadcast information or broadcast space-time; Broadcast-related systems
- H04H60/29—Arrangements for monitoring broadcast services or broadcast-related services
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- Electromagnetism (AREA)
- Computer Networks & Wireless Communication (AREA)
- Monitoring And Testing Of Transmission In General (AREA)
Abstract
A kind of monitoring method of fm broadcast signal aims to solve the problem that prior art the degree of automation is short of, the technical problems such as precision and inefficiency the present invention relates to radio monitoring field.The invention mainly comprises calculate mute template, the mute characteristic parameter of extraction and real-time judge.The present invention is often that recorded broadcast and the feature based on talking with, talk in real time, monitor frequency modulation broadcasting, rapid, batch finds " the black broadcast " in monitoring frequency range automatically by counting the degree of bias of the mute distribution of the proportion in playing process according to " black broadcast ".
Description
Technical field
The present invention relates to radio monitoring fields, and in particular to a kind of monitoring method of fm broadcast signal.
Background technology
In many areas in the whole nation, some criminals set up " black broadcast " using wireless device, and transmission content is vulgar, relates to
Yellow False advertisement, interference is caused to normal radio communication order, wherein is had when the case where interfering aviation frequency range
Occur.Meanwhile the life of the common people is caused to seriously affect, someone even has dust thrown into the eyes, very harmful.How sternly to hit " black
Broadcast ", the baneful influence for eliminating " black broadcast " become the urgent project of radio control person.
From Annual distribution, the broadcast time of " black broadcast " is simultaneously irregular, and some meetings continuously play several weeks, have
Diurnally or night broadcast；From spatial distribution, the signal coverage areas of a set of " black broadcast " is limited, specific range
Depending on local landform, the quality of weather and equipment；From frequency point distribution, " black broadcast " often neatly " insertion "
Each idle frequency sub-band of frequency range.
For these reasons, the complexity for judging " black broadcast " and investigating and prosecuting is increased on time, region, frequency domain.But
It is, at present to the judgement of " black broadcast " still based on manually monitoring.Different regions, different periods, different frequency range are required for consuming
Take a large amount of manpowers, since the sound of many frequency points is very ear-piercing, one can be caused for a long time to the hearing of radio regulator by monitoring
Fixed damage.Secondly it is audio analysis method, voice switchs to text, is then directed to key search.This method need to be to specific wide
The priori for broadcasting content needs certain artificial workload, and since content is changeable, wide variety increases the deposit of knowledge base
Difficulty；To the intensity of signal, the content of signal has required this method, reduces discrimination to a certain extent；Further, since
A frequency point can only be once scanned, and amount of audio data is larger, recognizer is complex, limits recognition efficiency.
Within a certain period of time, talk with different from the pause rule sung；Perdurabgility length of pausing every time is different；In broadcasting
Rong Shi, fluctuation situation also differ.For " black broadcast ", since main purpose is to promote the sale of products；And it is most of legal wide
It broadcasts, with service society, public amusement is purport.Dialogue that this two classes broadcasted content is included, song, background music proportion
There is very big difference.
To sum up, it after identifying mute plateau, can be carried out according to the difference of mute proportion distribution " black wide
Broadcast " and legal broadcast differentiation judge.
Effectively to identify " black broadcast ", manpower and time are saved, ensures that radio normal order, this patent propose one kind
Efficiently, identification " black broadcast " method accurately, intelligent.
Invention content
For the above-mentioned prior art, present invention aims at offer, aim to solve the problem that prior art the degree of automation is short of,
The technical problems such as precision and inefficiency.
In order to achieve the above objectives, the technical solution adopted by the present invention is as follows：
A kind of monitoring method of fm broadcast signal, step include
Step 1 carries out band scan to broadcast band, obtains its frequency spectrum data；
Step 2, according to frequency spectrum data, to the data frame of the signal of any appearance, find out that continuous to meet frequency point distribution special
The data frame that frequency point corresponds to the first threshold feature of level value is levied and met, candidate data frame set is formed；When not meeting
Stop that new data frame is added when features described above data frame, when what is again occurred continuous meet frequency point distribution characteristics and meet frequency point
When the data frame of the first threshold feature of corresponding level value, it is classified as new candidate data frame set；It repeats the above process, until obtaining
Obtain the mute template of all signals.To include that the most data frame set of frame number is denoted as the first number in these candidate data frame set
According to frame set, then find out the corresponding level value matrix of the first data frame set；
Step 3 finds out the corresponding average level value of level value matrix each column as mute template, wherein each average level
Value is used as mute point, and finds out its corresponding mute template to the signal of each appearance；
Step 4, according to mute template, calculate the slope of wherein straight line where the adjacent mute point of sequence, obtain mute mould
Plate slope characteristics；
Step 5, according to the corresponding mute template of each signal frequency point, the time quantum of set time length is set, to institute
There is signal frequency point to be matched and searched, find out while meeting slope characteristics and meets the second threshold of mute template average level value
Second data frame set of value tag, and the number of the second included object of data frame set is counted in current time unit,
That is the mute state data frame number through overmatching and judgement, is denoted as xij, then xijFor frequency point freiInclude in j-th of time quantum
Mute state data frame number, i=1,2 ... k, j=1,2 ... m, k are signal frequency point sum, and m is time quantum sum；
Mute shape obtained by step 6, each time quantum the second data frame set statistics by the condition described in step 5 that meets
State data frame number is denoted as Xi={ xi1,xi2,…,xij,…xim, degree of bias G is calculated as follows outi：
Wherein, XiThe mute state data frame number for including for j-th of time quantum mute state data frame set is xij
A time series, j=1,2 ... m, m be time quantum sum；GiFor frequency point freiThe degree of bias, E (X) be mathematic expectaion, var
(X) it is variance；
Step 7, default degree of bias threshold valueAccording to signal frequency point freiDegree of bias GiLess than or equal to degree of bias threshold valueJudge
Signal frequency point freiIt is black broadcast frequency point.
In the above method, the step 2, step includes,
Step 2.1, by 5 frequency points using centered on signal frequency point as a data frame, this 5 frequency points are corresponding
Feature vector of 5 sequence level values as the data frame；
Step 2.2, in a data frame will be in the corresponding level value size of opposite center frequency point and its in data frame
The corresponding level value size of its frequency point is compared, and finds out the data frame for meeting frequency point distribution characteristics, which is should
Level value in opposite center signal frequency point in data frame is maximum value；
Step 2.3, the data frame to meeting frequency point distribution characteristics described in step 2.2, will be respectively maximum in adjacent data frames
Level value and positioned at maximum level value or so level value it is corresponding respectively make difference and take absolute value, preset first threshold value, this is absolutely
The data frame that maximum value in value is less than first threshold constitutes the first data frame set, then finds out corresponding first data frame set
Level value.
In the above method, the step 3, the mute template of 5 mute point compositions, one signal specific, 5 mute points
From being calculated respectively by the corresponding average level value of level value matrix each column, it is mute that the maximum level value of mute template is located at third
Point position.
In the above method, the step 4, wherein
Mute template slope characteristics are the magnitude relationship and third slope and the 4th slope of first slope and the second slope
Magnitude relationship matches one of following four situation automatically according to the feature of signal frequency point：(>=, >=), (>=,<), (<,<), (<,
≥)。
In the above method, the step 5, wherein step include
Step 5.1, setting second threshold, it is characterized in that each data frame feature vector of current demand signal frequency point and mute mould
The maximum value that plate level value correspondence makees absolute value of the difference is less than the value；
Step 5.2 finds out the second data frame set for meeting step 5.1.
Step 5.3 is found out while being met step 5.1 and meets the second data frame set of step 5.2, packet in each set
The number of data frame containing mute state is xij。
Compared with prior art, beneficial effects of the present invention：
Ground is simultaneously created in novel ground, takes the lead in proposing to form quantitative mute template by frequency spectrum data itself, then will be mute
Template is matched with all frequency spectrum datas, then finds out the frequency spectrum data of nearly mute template, finally goes out black broadcast using threshold decision
A kind of frequency modulation broadcasting monitoring method；
Committed memory is few, and it is about 3.67MB to acquire some 1 minute audio data of signal frequency point, and is walked with 25K
For, a same frequency point, 1 minute data amount only 0.17MB in the band scan data of long acquisition；
Efficient, band scan data can obtain the scan data of all frequency points of the frequency range simultaneously, it is only necessary to 5 sampled points
It can identify that mute and intermediate frequency measurement data needs 1601, and can only once scan a frequency point；
It is adaptable, stability is high, due to need not as speech recognition must keyword in advance typing, not by wide
The limitation of content is broadcast, investigation range is largely improved；In addition, the algorithm is not area-limited, and can identify
" the black broadcast " that noise is larger, signal strength is weaker, improves the discrimination to " black broadcast "；
The present invention is adapted to different electromagnetic environments, can efficiently accomplish the Detection task on wide-band；By it is longer when
Between data counted, accurate more structurally sound data can be obtained；It is used for less empirical value, tool relative to other methods
Have higher intelligent.
Description of the drawings
Fig. 1 is that the present invention makes the difference in each frequency point level value correspondence of one signal specific frequency point adjacent data frames of spectrum scan data
Schematic diagram；
Fig. 2 is mute state data frame and sound status data frame schematic diagram of the present invention according to the identification of mute template
Fig. 3 is the mute distribution schematic diagram of the present invention legal broadcast 101.7MHz in somewhere 1 hour；
Fig. 4 is the mute distribution schematic diagram that the present invention " black broadcast " in somewhere 1 hour broadcasts 98.5MHz；
Fig. 5 is accuracy analysis curve graph of the different durations of the present invention to " black broadcast " broadcast identification.
Specific implementation mode
Embodiment 1
A kind of fm broadcast signal monitoring method, it is characterised in that：Its step are as follows：
I, data acquisition step：The frequency spectrum data that broadcast band super band scans is obtained from radio monitoring equipment；
II, each mute template step of frequency point is obtained：Find out all signal frequency points in the frequency spectrum data obtained in I step
fre1,fre2,…,frek, wherein k is signal frequency point sum.For any one signal frequency point, its generality is not lost, is denoted as
frei, remember freiAnd each two points in left and right are denoted as f successively1, f2, f3, f4, f5, level value size is followed successively by v1, v2, v3, v4, v5.Its
Middle f3It is center frequency point frei, f1, f2, it is two, center frequency point left side point, f4, f5It is two points on the right of center frequency point.
1. the data frame that pair all signals searched out by band scan screen 5 points for meeting following rule one by one is made
For the object for calculating mute：
A) level value maximum value and its signal center frequency position consistency, i.e. max (v1,v2,v3,v4,v5)=v3。
B) difference of the correspondence level value of each two points of its maximum level of eligible adjacent data frames a) and left and right is exhausted
Certain threshold value is less than to the maximum value of valueI.e. for same signal frequency point, remember that adjacent two data frame is f={ f1,f2,f3,f4,
f5And f '={ f1′,f2′,f3′,f4′,f5', remember that the corresponding level value size of this two frame is v=(v1,v2,v3,v4,v5) and v '
=(v1′,v2′,v3′,v4′,v5'), δi=| vi-vi' | indicate that this 5 points correspond to absolute value of the difference, as shown in Figure 1.It is eligible
A) adjacent data frames fluctuation range is less than predetermined threshold value Threshold value in this example
To Mr. Yu's signal frequency point within the unit time, the data matrix f that N frame data are constituted is acquired in real timeN×5It is as follows：
Level value corresponding to each position is denoted as vN×5, as follows：
To meeting condition 1 and the continuous longest segment of frame number is denoted as fn×5：
Level value corresponding to each frequency point is denoted as vn×5, as follows：
To vn×5It is averaged by row, obtains v1×5=(v1,v2,v3,v4,v5),
WhereinJ=1,2,3,4,5, v1×5Mute template as this period；One is updated at regular intervals
Secondary template is to adapt to current electromagnetic environment.
III, mute characteristic parameter step is extracted：
1. calculating 4 slope ks of four line segments of mute template connection1,k2,k3,k4, wherein ki=vi+1-vi, i=1,2,
3,4, k1For f1,f2The slope of composition；k2For f2,f3The slope of composition；k3For f3,f4The slope of composition；k4For f4,f5What is constituted is oblique
Rate；Next judge k1With k2Magnitude relationship (" being more than ", " being equal to ", " being less than "), k3With k4Magnitude relationship (" being more than ",
" being equal to ", " being less than "), it for the comparison result of two groups of slopes, " will be more than ", and be labeled as " 0 " the case where " being equal to ", " will be less than "
The case where be labeled as " 1 ", for the record of both sides slope size relationship, generate in total 4 kinds of results (1,1) (1,0) (0,1) (0,
0), the slope characteristics of mute template are wherein one of result.
2. setting threshold value a δ ', all data frame fi={ fi1,fi2,fi3,fi4,fi5, i=1,2 ... N level values vi=
(vi1,vi2,vi3,vi4,vi5), the level value v of i=1,2 ... N and mute template1×5=(v1,v2,v3,v4,v5) make difference after take absolutely
To value, it is denoted as δi=(δi1,δi2,δi3,δi4,δi5), δij=| vij-vj|, wherein i=1,2 ..., N；J=1,2,3,4,5 and
Meet δ ' ＞ max (δi), δ '=5 in this example, the mute state data frame and sound status identified in sometime unit
Data frame, as shown in Figure 2.
IV, real-time judge step：
1. being arranged according to mute template slope characteristics in step III and threshold value, mute characteristic parameter is met to entire frequency range
Each frequency point of new data counted successively according to time quantum, be denoted as xij, wherein i=1,2 ... k, k are signal sum；J=
1,2 ... m, m are time quantum sum, indicate i-th of frequency point freiX is shared in j-th of time quantumijFrame mute state number
According to.
2. a series of mute numbers of each time quantum statistics on each frequency point are denoted as：Xi={ xi1,xi2,…,
xij,…xim, calculate the degree of bias according to following formula：
Wherein：I=1,2 ... k, j=1,2 ... m, GiFor the degree of bias of signal frequency point i, E (X) is mathematic expectaion, var (X)
For variance.
Certain threshold value is set to the degree of biasIfThen judge signal frequency point freiFor " black broadcast ", otherwise frei
For " legal broadcast ", in this exampleIn 1 hour, the primary mute content of 10 seconds every (500 frame) statistics, frequency
Statistical chart is as shown in Figure 3 and Figure 4, wherein frequency point 98.5MHz is apparent left avertence, and the degree of bias is negative, is judged as less than 0.55
" black broadcast ", frequency point 101.7MHz, the degree of bias 3.6 are judged as legal broadcast more than 0.55.
Effect analysis：
Acquire the frequency spectrum data for the spectrum scan that somewhere frequency range is 87.5MHz-108MHz 3 hours.46 frequency points are shared,
Wherein include 15 " black broadcast ", 31 legal broadcast.It by this algorithm, identifies 14 " black broadcast ", erroneous judgement one is legal
Broadcast, fails to judge one " black broadcast ", by confusion matrix, calculates discrimination, sensitivity, precision is：95.7%, 93.3%,
93.3%.Calculation formula is as follows：
Discrimination：
Sensitivity：
Precision：
In formula：
Y:The number of " black broadcast " is correctly identified in classification results；
N0:Total number of samples；
N1:Normal broadcast total number is correctly identified in classification results；
N2:" black broadcast " number in data acquisition；
N3:The number of wrong identification normal broadcast in classification results.
Different durations (1-10 hours) is tested, accuracy analysis such as Fig. 5 has absolutely proved the effective of this method
Property.
The above description is merely a specific embodiment, but scope of protection of the present invention is not limited thereto, any
Belong to those skilled in the art in the technical scope disclosed by the present invention, the change or replacement that can be readily occurred in all are answered
It is included within the scope of the present invention.
Claims (6)
1. a kind of monitoring method of fm broadcast signal, which is characterized in that step includes
Step 1 carries out band scan to broadcast band, obtains its frequency spectrum data；
Step 2, according to frequency spectrum data, there is the data frame of signal to each, find out and continuously meet frequency point distribution characteristics and accord with
Sum of fundamental frequencies point corresponds to the data frame of the first threshold feature of level value, forms candidate data frame set, will be in candidate data frame set
Including the most data frame set of frame number is denoted as the first data frame set, then find out the corresponding level value square of the first data frame set
Battle array；
Step 3 finds out the corresponding average level value of level value matrix each column as mute template, wherein each average level value is made
For mute point, and its corresponding mute template is found out to the signal of each appearance；
Step 4, according to mute template, calculate the slope of wherein straight line where the adjacent mute point of sequence, it is oblique to obtain mute template
Rate feature；
Step 5, according to the corresponding mute template of each signal frequency point, the time quantum of set time length is set, to all letters
Number frequency point is matched and is searched, find out while meeting slope characteristics and meet mute template average level value second threshold it is special
Second data frame set of sign, and count in current time unit the number of the second included object of data frame set, that is, it passes through
The mute state data frame number of overmatching and judgement, is denoted as xij, then xijFor frequency point freiJ-th of time quantum include it is quiet
Sound-like state data frame number, i=1,2 ... k, j=1,2 ... m, k are signal frequency point sum, and m is time quantum sum；
Step 6, will meet all of condition described in step 5 or each time quantum the second data frame set statistics gained it is quiet
Sound-like state data frame number is denoted asOr Xj={ x1j,x2j,…,xkj, wherein Xi={ xi1,
xi2,…,xijWhen include in j time quantum mute state data frame set for i-th of frequency point mute state data frame
Number is xijA time series, degree of bias G is calculated as follows outi：
Wherein, XiThe mute state data frame number for including in j time quantum mute state data frame set for i-th of frequency point
For xijA time series；GiFor frequency point freiThe degree of bias, E (X) be mathematic expectaion, var (X) be variance；
Step 7, default degree of bias threshold valueAccording to signal frequency point freiDegree of bias GiLess than or equal to degree of bias threshold value G, signal frequency is judged
Point freiIt is black broadcast frequency point.
2. a kind of monitoring method of fm broadcast signal according to claim 1, which is characterized in that the step 2, step
Suddenly include,
Step 2.1, by 5 frequency points using centered on signal frequency point as a data frame, this 5 frequency points are 5 corresponding
Feature vector of the sequence level value as the data frame；
Step 2.2, in a data frame will be in the corresponding level value size of opposite center frequency point and other frequencies in data frame
The corresponding level value size of point is compared, and finds out the data frame for meeting frequency point distribution characteristics, which is the data
Level value in opposite center signal frequency point in frame is maximum value；
Step 2.3, the data frame to meeting frequency point distribution characteristics described in step 2.2, by respective maximum level in adjacent data frames
Value and positioned at maximum level value or so level value it is corresponding respectively make difference and take absolute value, preset first threshold value, in the absolute value
Maximum value be less than the data frame of first threshold and constitute the first data frame set, then find out the level of corresponding first data frame set
Value.
3. a kind of monitoring method of fm broadcast signal according to claim 2, which is characterized in that the step 2.3,
In further include,
Stop new data frame candidate data frame set is added when the data frame for occurring not meeting step 2, when again occurring
It is continuous when meeting frequency point distribution characteristics and meeting frequency point and correspond to the data frame of first threshold feature of level value, be grouped into time again
Select data frame set；
To include that the most data frame set of frame number is denoted as the first data frame collection in all candidate data frame set of each signal
It closes, then finds out the corresponding level value matrix of the first data frame set；
It repeats the above process, until obtaining the mute template of all signals.
4. a kind of monitoring method of fm broadcast signal according to claim 1, which is characterized in that the step 3,5
The mute template of one signal specific of mute point composition, 5 mute points are respectively by the corresponding average level of level value matrix each column
Value calculates, and the maximum level value of mute template is located at mute position of third.
5. a kind of monitoring method of fm broadcast signal according to claim 1, which is characterized in that the step 4, it is mute
Template slope characteristics are that first slope and the magnitude relationship and third slope and the magnitude relationship of the 4th slope of the second slope are automatic
One of following four situation is matched according to the feature of signal frequency point：(>=, >=), (>=,<), (<,<), (<, >=), i.e., (first
The slope of slope >=second, the slope of third slope >=the 4th), (slope of first slope >=second, third slope<4th slope), (the
One slope<Second slope, third slope<4th slope), (first slope<Second slope, the slope of third slope >=the 4th).
6. a kind of monitoring method of fm broadcast signal according to claim 1, which is characterized in that the step 5, step
Suddenly include,
Step 5.1, setting second threshold, it is characterized in that each data frame feature vector of current demand signal frequency point and mute template electric
The maximum value that level values correspondence makees absolute value of the difference is less than the value；
Step 5.2 finds out the second data frame set for meeting step 5.1.
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| CN109245841A (en) * | 2018-08-03 | 2019-01-18 | 天维讯达（北京）科技有限公司 | A kind of multichannel FM broadcasting audio information acquisition device, method and system |
| CN110971324B (en) * | 2019-03-29 | 2021-07-30 | 国家无线电监测中心检测中心 | Black broadcast signal monitoring method |
| CN111934800B (en) * | 2019-05-13 | 2022-05-13 | 北京市博汇科技股份有限公司 | Broadcast content monitoring method and system |
| CN112929103A (en) * | 2021-01-26 | 2021-06-08 | 赵炳健 | Illegal broadcasting station detection method and system |
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