CN105897488A - Visualization method of radio signal data - Google Patents

Visualization method of radio signal data Download PDF

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CN105897488A
CN105897488A CN201610419842.XA CN201610419842A CN105897488A CN 105897488 A CN105897488 A CN 105897488A CN 201610419842 A CN201610419842 A CN 201610419842A CN 105897488 A CN105897488 A CN 105897488A
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signal
radio
timeslice
frequency
color
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CN105897488B (en
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周芳芳
曾媛
赵颖
张蓉
李俊材
佘燕敏
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Central South University
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
    • H04L41/22—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks comprising specially adapted graphical user interfaces [GUI]
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B17/00—Monitoring; Testing
    • H04B17/30—Monitoring; Testing of propagation channels
    • H04B17/309—Measuring or estimating channel quality parameters
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B17/00—Monitoring; Testing
    • H04B17/30—Monitoring; Testing of propagation channels
    • H04B17/309—Measuring or estimating channel quality parameters
    • H04B17/318—Received signal strength

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  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Quality & Reliability (AREA)
  • Physics & Mathematics (AREA)
  • Electromagnetism (AREA)
  • Human Computer Interaction (AREA)
  • Testing, Inspecting, Measuring Of Stereoscopic Televisions And Televisions (AREA)
  • Monitoring And Testing Of Transmission In General (AREA)

Abstract

The invention provides a visualization method of radio signal data. The visualization method of the radio signal data comprises a first step of obtaining the radio signal data extracted from frequency spectrum data and original electric level sampling data; a second step of drawing a frequency-bandwidth scatter diagram; a third step of clustering the radio signal data by using a clustering algorithm; a fourth step of dividing time slices; a fifth step of calculating an average center frequency, an average bandwidth, an average signal-to-noise ratio and an average signal intensity of each time slice for each cluster; and a sixth step of drawing a signal flow diagram. Multiple characteristics of radio signals are coded efficiently by utilizing the signal flow diagram, multiple types of important characteristics of relatively scattered signal data at a time frequency are shown smoothly, a multi-characteristic time-varying mode of the radio signal is shown in a better manner, and a macroscopic perceiving efficiency of an analyzer for the radio signal time-varying mode is speeded up.

Description

A kind of method for visualizing of radio-signal data
Technical field
The present invention relates to information visualization field, particularly to the method for visualizing of a kind of radio-signal data.
Background technology
Radio-frequency spectrum is a kind of limited natural resources, is the underlying carrier of modern wireless information transfer.In order to reduce radio Interfering, in order to ensure the unimpeded, in order to better profit from limited frequency spectrum resource, especially of important communication link between signal It is in the key area such as airport and border and in Security ensuring of important activities task, enhanced radio spectrum monitoring and radio signal Management, to safeguarding national security and promoting that national economy steady development has its own strategic significance.
Being monitored radio-frequency spectrum in certain frequency range is the foundation stone of radio control activity, the frequency spectrum that various monitoring devices gather Monitoring Data is that frequency spectrum occupancy rate calculates, disturbs signal monitoring and frequency spectrum resource division to provide information source.Tradition frequency spectrum data divides The method for visualizing such as frequency spectrum amplitude frequency diagram, time-frequency figure and sunset glow figure are first displayed by analysis, then by the personnel of analysis according to various frequencies The time-frequency distributions of spectrogram perceptual signal and searching signal of interest.But this way is the highest to analyzing personnel specialty competency profiling, general General family not through professional training and accumulate practical operation experience be difficult to from spectrogram, identify radio signal timely and accurately, and When the monitoring time is elongated or more radio signal occurs in frequency range, manual analysis efficiency can quickly reduce, thus causes being difficult to Active detecting unknown signal associates with the complexity analyzed between signal, and radio control excessively relies on the passive management modes such as report.
By signal processing and mathematical analysis, radio frequency line modal data being converted into radio-signal data is the new square of radio control To, each data record of radio-signal data represents an in esse radio signal, and it is right that its each data item reflects Answer the multidimensional characteristics such as the mid frequency of radio signal, bandwidth, signal to noise ratio.This structuring degree is higher, signal characteristic is brighter Clear radio-signal data is the useful supplement of radio frequency line modal data, is conducive to merging public frequency storehouse and authorizing station storehouse etc. Basic data resource, is also beneficial to solidify expertise, promotes the application with various intelligent data analysis means.But radio Signal data there is also some problems needing solution badly, first radio-signal data in actual applications and extracts in time, A large amount of corresponding same actual non-momentary radio signals of signal characteristic records possibility, due to unstability and the possibility of monitoring of environmental There is interference signal and the same frequency of multi-user's time division multiplex, use automatic mode to be difficult to correctly and gather by the actual wireless signal of telecommunication Class signal characteristic record；Then, the method for visualizing such as tradition scatterplot, line chart and parallel coordinates, all it is difficult to show radio The time-varying pattern of signal multiple features, brainstrust lacks valid wireless electrical signal data method for visualizing and observes, compares and analyze Radio signal.
Summary of the invention
It is an object of the invention to provide a kind of effective method for visualizing and observe, compare and analyze radio signal, the present invention Provide a kind of new can accurately showing radio signal multiple features time-varying pattern and be easy to the method for visualizing of comparative analysis.
The technical scheme is that
A kind of method for visualizing of radio-signal data, including following step:
Step 1: acquisition radio-signal data:
Radio-signal data is included in a time period [tstart,tendAll n the radio detected in detection frequency range in] Signal { S1,S2,…Si,…,Sn, the feature that each radio signal comprises have mid frequency (freq), bandwidth (baud), Signal to noise ratio (snr), signal intensity (dbm) and timestamp, timestamp represents the time point that this signal is detected, and labelling is believed Number SiMid frequency, bandwidth, signal to noise ratio, signal intensity and the timestamp of (1≤i≤n) is respectively
Step 2: the radio-signal data drafting frequency bandwidth scatterplot obtained according to step 1:
In scatterplot, X-axis represents that frequency, Y-axis represent that bandwidth draws scatterplot, and frequency range is the frequency that radio signal is collected Rate is interval, and bandwidth range is 0 to obtain the maximum of bandwidth in all radio signals to step 1；According to each signal Mid frequency and bandwidth value find its position in frequency bandwidth scatterplot, draw all signaling points；Record each aerogram Number SiCoordinate S in frequency bandwidth scatterploti(xi,yi)(1≤i≤n)；Encode according to signal strength color, filling signal point；Letter Number intensity colors coding refers to ascending for the signal strength values RGB color degree bar being encoded to gradual change；
Step 3: the radio-signal data using clustering algorithm to be obtained step 1 clusters, and obtains k cluster {C1,C2,C3,…,Ck, m noise spot；
Radio-signal data is extracted and is carried out at timed intervals, and the non-momentary radio signal in detection frequency range can repeatedly be remembered Record, due to signal and the unstability of collecting device, the feature of same radio signal there will be a range of fluctuation, so Need to use clustering algorithm that the radio-signal data obtained is clustered.
Step 4: division timeslice:
By interval for whole radio signal acquisition time [tstart,tend] it is divided into the p section that length is identical, i.e. p timeslice, The labelling jth time period is tj(1≤j≤p)
To each cluster CiAll signals in this cluster are divided in corresponding timeslice, often by (1≤i≤k) according to its timestamp Individual cluster Ci(1≤i≤k) obtains a timeslice dividing sequence Csti={ sti1,sti2,…,stij,…,stip(1≤i≤k), wherein stij(1≤j≤p) (1≤i≤k) represents cluster Ci(1≤i≤k) is divided into timeslice tjSet { the S of the signal in (1≤j≤p)q,…,Sq+r, In set, signal number is r (0≤r≤n), and the timestamp of all signals in this set is in timeslice tjIn (1≤j≤p)；
Step 5: according to each cluster C obtained in step 4iThe timeslice dividing sequence Cst of (1≤i≤k)i= {sti1,sti2,…,stip(1≤i≤k), calculate each cluster Ci(1≤i≤k) is divided into timeslice tjPutting down of all signals in (1≤j≤p) All mid frequency (mFreq), average bandwidth (mBaud), average signal-to-noise ratio (mSnr) and average signal strength (mDbm)；
Step 6: the cluster result obtained according to step 3 and the result of calculation of step 5 draw signal flow diagram, specifically include Following steps:
Step 6.1): drawing signal flow diagram coordinate system, wherein X-axis represents frequency, Y-axis express time；Frequency range is wireless The frequency separation that electrical signal data is collected, time range is the time period that radio-signal data is collected；Each cluster is painted Make a bars stream；
Step 6.2): to cluster Ci(1≤i≤k), according to this clustering to timeslice tjThe mean center frequency of (1≤j≤p) interior signal Value mFreqij, frequency corresponding in signal flow diagram coordinate system and timeslice tjOriginal position graphical pointv A, according to division To timeslice tj+1Mean center frequency mFreq of interior signali(j+1), frequency corresponding in signal flow diagram coordinate system and time Sheet tj+1Original position i.e. timeslice tjFinal position graphical pointv B, junction point A and some B, draw a line segment AB, with really Fixed signal stream corresponding to this cluster is in timeslice tjCenter；
If timeslice tjContinuous print subsequent time sheet t the most therewithj+1, then timeslice tjCorresponding signal stream is not drawn；
Step 6.3): according to this clustering to timeslice tjThe average bandwidth of interior signal determines the width of signal stream, and draws The left margin of signal stream and right margin, left margin and right margin are symmetrical about line segment AB；
Step 6.4): according to this clustering to timeslice tjThe value of the average signal strength of interior signal and signal strength color are compiled Code, the region between filling left margin to line segment AB；
Step 6.5): according to this clustering to timeslice tjThe average signal-to-noise ratio of interior signal and signal to noise ratio color coding, fill out Fill line segment AB to right border area；Signal to noise ratio color coding refers to ascending for the snr value gradual change gray value being encoded to gradual change；
Step 6.6): repeat the above steps 6.2) to step 6.5), draw C successivelyi(1≤i≤k) all of timeslice, and all Cluster.
In the scatterplot of described step 2, it is that R circle represents a signal with radius, according to the signal intensity of this signal, Signal strength color coding finds the color filling circle corresponding to its value.
Described signal strength color coding concrete methods of realizing is: color mode uses RGB pattern, to the parameter in color RGB Realizing gradual change with certain increments (being incremented by), the span of three parameters of RGB color pattern is 0 to 255.Initially Color is red (255,0,0), it is assumed that step-length is i, and the second parameter of priming color is incremented by i successively, fades to yellow (255,255,0), then first parameter is successively decreased i successively, fades to green (0,255,0), and then the 3rd parameter is passed successively Increasing i, fade to cyan (0,255,255), then second parameter successively decreases i successively, fades to blueness (0,0,255), then 3rd parameter is successively decreased i successively, finally fades to black (0,0,0).From priming color redness be gradient to black the distance of process Length distance is (5*255)/i, and the signal strength values of (0,140) dbm scope is converted into (0, (5*255)/i) Each signal strength values m (dbm) in scope, i.e. (0,140) scope is in (0, (5*255)/i) scope correspondence one Individual unique value mindex, obtains the color corresponding to this signal strength values by following manner after obtaining mindex Color (r, g, b):
If mindex >=0 and mindex≤255/i, then make
R=255；
G=map (mindex, 0,255/i, 0,255)；
B=0；
If mindex > 255/i and mindex≤255*2/i, then make
R=map (mindex, 255/i, 255*2/i, 0,255)；
G=255；
B=0；
If mindex > 255*2/i and mindex≤255*3/i, then make
R=0；
G=255
B=map (mindex, 255*2/i, 255*3/i, 0,255)；
If mindex > 3*255/i and mindex≤255*4/i, then make
R=0；
G=map (mindex, 255*3/i, 255*4/i, 0,255)；
B=255；
If mindex > 4*255/i and mindex≤255*5/i, then make
R=0；
G=0；
B=map (mindex, 255*4/i, 255*5/i, 0,255)；
Wherein map (x, x1, x2, x3, x4) function is to return value x in the range of (x1, x2) to be transformed into the right of (x3, x4) scope Should be worth；
With it, make the signal strength values of 0 to 140dbm be encoded to be faded to yellow by redness fade to green more gradually Become cyan and fade to blueness again, finally fade to the colourity bar of black.
Described signal to noise ratio color coding concrete methods of realizing be: use greyscale color pattern, i.e. with 0 to 255 different gray values Representing color, 0 represents black, and 255 represent white；The snr value that scope is 0 to 100 is converted into 0 to 255 scopes Color value, i.e. a color value of corresponding (0, the 255) scope of each snr value in the range of (0,100), this color value is i.e. Greyscale color for this signal to noise ratio encodes；The snr value of 0 to 100 is encoded to gradual change gray scale from white to black；
Described step 3 uses DBScan clustering algorithm to cluster radio-signal data, specifically comprises the following steps that
Step 3.1: two parameters needed for DBScan clustering algorithm is set: quantity minpts of minimum point in radius eps and neighborhood； Labelling original state a little be accessed (unvisited)；
Step 3.2: the Euclidean distance of calculation procedure 2 frequency bandwidth scatterplot:As poly- Two signal S in class algorithmi,SjDistance between (1≤i, j≤n, i ≠ j)；
The concrete grammar of DBScan algorithm: the point of optional not accessed (unvisited) starts, and finds out with its distance at eps Within (including eps) all near point.If the quantity >=minpts of neighbouring point, then current point forms one with its neighbouring point Bunch, and starting point is marked as accessing (visited).Then recurrence, processes all in this bunch not being labeled in the same way For accessing the point of (visited), thus to bunch being extended.If < minpts, then this point is temporarily labeled the quantity of neighbouring point As noise spot.If bunch be expanded fully, i.e. bunch interior being marked as a little accesses, then goes with same algorithm Process and be not accessed for a little；
Step 3.3: obtain the result of DBScan clustering algorithm, altogether k cluster, m noise spot.
DBScan clustering algorithm is a representational density-based algorithms of comparison.With divide and hierarchy clustering method not With, it bunch will be defined as the maximum set of the point that density is connected, it is possible to is divided into bunch having the most highdensity region, and can The cluster of arbitrary shape is found in the spatial database of noise.
In DBScan clustering algorithm, use the Euclidean distance between signaling point in frequency bandwidth scatterplotMeasure two signal Si,SjDistance between (1≤i, j≤n, i ≠ j)；This be because mid frequency and Bandwidth is to identify the core feature of a radio signal, and between mid frequency (unit Mhz) and bandwidth (unit db) Value difference is relatively big, and it is too big that direct use can make the distance judging between two signaling points during cluster be affected by bandwidth, and in The impact of frequency of heart is negligible substantially, thus cluster to obtain result error the biggest.
In described step 3, use clustering algorithm that radio-signal data is clustered, and the color of each cluster self-defined； When defining the color of each cluster, the distribution situation of combining wireless electrical signal data signal intensity, select signal intensity coding not make Use and the color high with the signaling point Fill Color discrimination in this cluster, in order to better discriminate between out in cluster and this cluster Signaling point.
In described step 4, time span and sample rate that the basis of design radio signal of p gathers select；Such as: signal The acquisition interval time is 1 second, then can arrange a length of 1 second of timeslice, then p equal to [tstart,tend] number of seconds.
In described step 4, in described step 5, cluster Ci(1≤i≤k) is divided into timeslice tjAll signals in (1≤j≤p) Mean center frequency (mFreq), average bandwidth (mBaud), average signal-to-noise ratio (mSnr) and average signal strength (mDbm) Calculation as follows:
mFreq i j = &Sigma; m = q q + r S m f r , ( 1 &le; i &le; k ) ( 1 &le; j &le; p ) ;
mBaud i j = &Sigma; m = q q + r S m b r , ( 1 &le; i &le; k ) ( 1 &le; j &le; p ) ;
mDbm i j = &Sigma; m = q q + r S m d r , ( 1 &le; i &le; k ) ( 1 &le; j &le; p ) ;
mSnr i j = &Sigma; m = q q + r S m s r , ( 1 &le; i &le; k ) ( 1 &le; j &le; p ) .
In described step 6, when drawing signal stream, signal is not had to occur if there is in continuous a period of time, because each poly- May all there is signal in not all timeslice in apoplexy due to endogenous wind, then this stream is it is possible to there is discontinuous situation, in order to show The time discontinuity of signal, arranges two rendering parameters: timeslice signaling point degree of rarefication e and continuous sparse timeslice number z, time Between sheet signaling point degree of rarefication represent the minimum signal number in a timeslice, continuous sparse timeslice number represents that signal number is less than The sequential time slices number of timeslice signal degree of rarefication, is less than e if there is more than or equal to the signaling point in the sequential time slices of z, The most do not draw this segment signal stream.
Beneficial effect
The invention provides the method for visualizing of a kind of radio-signal data, step 1: sample from frequency spectrum data and original level Extracting data radio-signal data；Step 2: use clustering algorithm that radio-signal data is clustered；Step 3: right Mean center frequency, average bandwidth, average signal-to-noise ratio and the average signal strength of each timeslice of each cluster calculation；Step 4: Draw signal flow diagram.Utilize the various features of signal flow diagram efficient coding radio signal, by signal data more discrete on time-frequency Multiple key character smoothly display, the preferably effective multiple features time-varying pattern showing radio signal, it is simple to point Analyse personal observations, compare and analyze radio signal, improve the analysis personnel identification energy to radio signal quantity and microscopic feature Power, accelerates the analysis personnel macroscopical perception efficiency to radio signal time-varying pattern.
Accompanying drawing explanation
Fig. 1 is the flow chart of the method for the invention；
Fig. 2 is frequency bandwidth two dimension scatterplot；
After Fig. 3 is use DBScan clustering algorithm cluster and each cluster is distributed the frequency bandwidth two dimension scatterplot of color；
Fig. 4 signal flow diagram.
Detailed description of the invention
The present invention is described in further detail with specific embodiment below in conjunction with the accompanying drawings.
A kind of method for visualizing of radio-signal data, including following step:
Step 1: obtaining radio-signal data, radio-signal data is 2016/4/715:16:08 to 2016/4/715:17:42, In the time period of 94 seconds, frequency range is all signaling points of 952 961Mhz altogether, each data note of radio-signal data The all corresponding radio signal of record, the feature that each radio signal comprises have mid frequency (freq), bandwidth (baud), Signal to noise ratio (snr), signal intensity (dbm) and timestamp, represent that this signal is detected at the time point represented by timestamp, Comprise 6437 radio signals, marking signal S altogetheriThe mid frequency of (1≤i≤6437), bandwidth, signal to noise ratio, signal intensity and time Between stamp be respectively
Step 2: drawing frequency bandwidth scatterplot according to the radio-signal data that step 1 is obtained, wherein X-axis represents frequency, Frequency range is 952 961Mhz, and Y-axis represents bandwidth, bandwidth range 0 to 4050db.In frequency bandwidth scatterplot, each It is the circle of R that signal is represented as a radius, the color of circle represent the signal intensity of this signal, signal strength color be encoded to by Redness fades to yellow and fades to green again and fade to cyan again and fade to blueness again, finally fades to the colourity bar coding 0 of black To the signal strength values of 140dbm, tracer signal point SiCoordinate S in frequency bandwidth scatterploti(xi,yi)(1≤i≤n).Frequency Bandwidth scatterplot is as shown in Figure 2；
Step 3: the radio-signal data using DBScan clustering algorithm to be obtained step 1 clusters.Radio signal Data are extracted and are carried out at timed intervals, the non-momentary radio signal in monitoring frequency range can by repeatedly record, due to signal and The unstability of collecting device, the feature of same radio signal there will be a range of fluctuation, so needing to use cluster to calculate The radio-signal data obtained is clustered by method.DBScan clustering algorithm is that a comparison is representational based on density poly- Class algorithm.From divide and hierarchy clustering method is different, it bunch will be defined as the maximum set of the connected point of density, it is possible to having The most highdensity region is divided into bunch, and can find the cluster of arbitrary shape in the spatial database of noise.In clustering algorithm Two signal Si,SjThe Euclidean distance of the distance use step 2 frequency bandwidth scatterplot between (1≤i, j≤n, i ≠ j):DBScan clustering algorithm desired parameters eps=30, minpts=40 are set.DBScan clusters Algorithm obtains 7 cluster { C1,C2,C3,Λ,C7, 640 noise spots, the color of each cluster self-defined, the value ratio of signal intensity Relatively concentrating between 30 to 80dbm, the color i.e. put is mainly in the orange interval being gradient to green, so selecting cluster color Time can use other other color not used.Frequency bandwidth scatterplot such as Fig. 3 institute after using DBScan to cluster Showing, each cluster uses a polygon to be surrounded；
Step 4: divide timeslice, by interval for whole radio signal acquisition time 2016/4/7 15:16:08 to 2016/4/7 15:17:42 is divided into 94 sections, and every segment length is 1 second, and the labelling jth time period is tj(1≤j≤94).According to obtained by step 3 7 clusters, to each cluster Ci(1≤i≤7), when being divided into corresponding by all signaling points in this cluster according to its timestamp Between in sheet, each cluster Ci(1≤i≤6) obtain time series Csti={ sti1,sti2,…,sti94(1≤i≤7), wherein stij(1≤j≤94) (1≤i≤7) represent the set { S of a signaling pointq,…,Sq+r, in set, signal number is r (0≤r≤6437), owning in this set The timestamp of signaling point is at tjIn (1≤j≤94) timeslice；
Step 5: according to each cluster C obtained in step 4iSequence C st after the division of (1≤i≤7) timeslicei= {sti1,sti2,…,sti94(1≤i≤7), the timeslice dividing sequence to each cluster, calculate each timeslice tj(1≤j≤94) interior signal Mean center frequency (mFreq), average bandwidth (mBaud), average signal-to-noise ratio (mSnr) and average signal strength (mDbm), Calculation is as follows:
mFreq i j = &Sigma; m = q q + r S m f r , ( 1 &le; i &le; k ) ( 1 &le; j &le; p ) ;
mBaud i j = &Sigma; m = q q + r S m b r , ( 1 &le; i &le; k ) ( 1 &le; j &le; p ) ;
mDbm i j = &Sigma; m = q q + r S m d r , ( 1 &le; i &le; k ) ( 1 &le; j &le; p ) ;
mSnr i j = &Sigma; m = q q + r S m s r , ( 1 &le; i &le; k ) ( 1 &le; j &le; p ) .
Step 6: the mean center frequency of each timeslice after dividing according to the timeslice of the calculated each cluster of step 5 (mFreq), average bandwidth (mBaud), average signal-to-noise ratio (mSnr) and average signal strength (mDbm) draw signal Flow graph, in signal flow diagram, X-axis represents that frequency, Y-axis express time, and time are incremented by from top to bottom, and frequency range is wireless The frequency separation that electrical signal data is collected, time range is the time period that radio-signal data is collected；Each cluster is painted Make a bars stream.First take first cluster, draw its first timeslice, according to the mid frequency of first timeslice Value and the frequency corresponding in signal flow diagram coordinate system of the center frequency value of second timeslice and corresponding to this timeslice time Between region draw straight line, determine that the signal stream corresponding to this cluster is in the center of this timeslice；Then according to this cluster Average signal bandwidth in this timeslice draws left margin and the right margin of signal stream, and the distance of left margin to right margin is its letter The value of number bandwidth, owing to signal bandwidth may be relatively big, can be multiplied by a coefficient less than 1, and left margin is to mid frequency straight line Distance be 1/2nd of its average bandwidth, the distance of right margin to mid frequency straight line is also 1/2nd of its average bandwidth, Left margin and right margin are parallel to the straight line of mid frequency straight line；Then fill according to the value of average signal strength in this timeslice Left margin is to mid frequency line region, and color coding is identical with the color coding of signal round dot in step 2；Then according to this time In sheet, average signal-to-noise ratio is filled mid frequency line and is used gradual change gray-coded from white to black to right border area, color coding The snr value of 0 to 100；Repeat the above steps draws remaining timeslice successively, and last timeslice is not drawn.In like manner Draw all of cluster.When drawing signal stream, if certain stream does not all have signal to occur in continuous a period of time, then this Bar stream is it is possible to there is discontinuous situation, and in order to show the time discontinuity of signal, we arrange two rendering parameters here: Signaling point degree of rarefication per second and continuous sparse number of seconds, the most sparse if there is continuous z second signaling point, then signal stream will not Draw this section.Drawn signal flow diagram is as shown in Figure 4.

Claims (9)

1. the method for visualizing of a radio-signal data, it is characterised in that include following step:
Step 1: acquisition radio-signal data:
Radio-signal data is included in a time period [tstart,tendAll n the radio detected in detection frequency range in] Signal { S1,S2,…Si,…,Sn, the feature that each radio signal comprises has mid frequency, bandwidth, signal to noise ratio, signal Intensity and timestamp, timestamp represents the time point that this signal is detected, marking signal SiThe mid frequency of (1≤i≤n), bandwidth, Signal to noise ratio, signal intensity and timestamp are respectively
Step 2: the radio-signal data drafting frequency bandwidth scatterplot obtained according to step 1:
In scatterplot, X-axis represents that frequency, Y-axis represent that bandwidth draws scatterplot, and frequency range is the frequency that radio signal is collected Rate is interval, and bandwidth range is 0 to obtain the maximum of bandwidth in all radio signals to step 1；According to each signal Mid frequency and bandwidth value find its position in frequency bandwidth scatterplot, draw all signaling points；Record each aerogram Number SiCoordinate S in frequency bandwidth scatterploti(xi,yi)(1≤i≤n)；Encode according to signal strength color, filling signal point；Letter Number intensity colors coding refers to ascending for the signal strength values RGB color degree bar being encoded to gradual change；
Step 3: the radio-signal data using clustering algorithm to be obtained step 1 clusters, and obtains k cluster {C1,C2,C3,…,Ck, m noise spot；
Step 4: division timeslice:
By interval for whole radio signal acquisition time [tstart,tend] it is divided into the p section that length is identical, i.e. p timeslice, The labelling jth time period is tj(1≤j≤p)；
To each cluster CiAll signals in this cluster are divided in corresponding timeslice, often by (1≤i≤k) according to its timestamp Individual cluster Ci(1≤i≤k) obtains a timeslice dividing sequence Csti={ sti1,sti2,…,stij,…,stip(1≤i≤k), wherein stij(1≤j≤p) (1≤i≤k) represents cluster Ci(1≤i≤k) is divided into timeslice tjSet { the S of the signal in (1≤j≤p)q,…,Sq+r, In set, signal number is r (0≤r≤n), and the timestamp of all signals in this set is in timeslice tjIn (1≤j≤p)；
Step 5: according to each cluster C obtained in step 4iThe timeslice dividing sequence Cst of (1≤i≤k)i= {sti1,sti2,…,stip(1≤i≤k), calculate each cluster Ci(1≤i≤k) is divided into timeslice tjPutting down of all signals in (1≤j≤p) All mid frequency, average bandwidth, average signal-to-noise ratio and average signal strength；
Step 6: the cluster result obtained according to step 3 and the result of calculation of step 5 draw signal flow diagram, specifically include Following steps:
Step 6.1): drawing signal flow diagram coordinate system, wherein X-axis represents frequency, Y-axis express time, and frequency range is wireless The frequency separation that electrical signal data is collected, time range is the time period that radio-signal data is collected；Each cluster is painted Make a bars stream；
Step 6.2): to cluster Ci(1≤i≤k), according to this clustering to timeslice tjThe mean center frequency of (1≤j≤p) interior signal Value mFreqij, frequency corresponding in signal flow diagram coordinate system and timeslice tjOriginal position graphical pointv A, according to division To timeslice tj+1Mean center frequency mFreq of interior signali(j+1), frequency corresponding in signal flow diagram coordinate system and time Sheet tj+1Original position i.e. timeslice tjFinal position graphical pointv B, junction point A and some B, draw a line segment AB, with really Fixed signal stream corresponding to this cluster is in timeslice tjCenter；
If timeslice tjContinuous print subsequent time sheet t the most therewithj+1, then timeslice tjCorresponding signal stream is not drawn；
Step 6.3): according to this clustering to timeslice tjThe average bandwidth of interior signal determines the width of signal stream, and draws The left margin of signal stream and right margin, left margin and right margin are symmetrical about line segment AB；
Step 6.4): according to this clustering to timeslice tjThe value of the average signal strength of interior signal and signal strength color are compiled Code, the region between filling left margin to line segment AB；
Step 6.5): according to this clustering to timeslice tjThe average signal-to-noise ratio of interior signal and signal to noise ratio color coding, fill out Fill line segment AB to right border area；Signal to noise ratio color coding refers to ascending for the snr value gradual change gray value being encoded to gradual change；
Step 6.6): repeat the above steps 6.2) to step 6.5), draw C successivelyi(1≤i≤k) all of timeslice, and all Cluster.
Method for visualizing based on radio-signal data the most according to claim 1, it is characterised in that described step 2 Scatterplot in, be that R circle represents a signal with radius, according to the signal intensity of this signal, compile in signal strength color The color filling circle corresponding to its value is found in Ma.
Method for visualizing based on radio-signal data the most according to claim 2, it is characterised in that described signal is strong Degree color coding concrete methods of realizing is: color mode uses RGB pattern, by the signal strength values of (0,140) dbm scope Be converted into (0, (5*255)/i) scope, i.e. each signal strength values m (dbm) in (0,140) scope (0, (5*255) / i) the corresponding unique value mindex of scope, obtained corresponding to this signal strength values by following manner after obtaining mindex Color color (r, g, b):
If mindex >=0 and mindex≤255/i, then make
R=255；
G=map (mindex, 0,255/i, 0,255)；
B=0；
If mindex > 255/i and mindex≤255*2/i, then make
R=map (mindex, 255/i, 255*2/i, 0,255)；
G=255；
B=0；
If mindex > 255*2/i and mindex≤255*3/i, then make
R=0；
G=255
B=map (mindex, 255*2/i, 255*3/i, 0,255)；
If mindex > 3*255/i and mindex≤255*4/i, then make
R=0；
G=map (mindex, 255*3/i, 255*4/i, 0,255)；
B=255；
If mindex > 4*255/i and mindex≤255*5/i, then make
R=0；
G=0；
B=map (mindex, 255*4/i, 255*5/i, 0,255)；
Wherein map (x, x1, x2, x3, x4) function is to return value x in the range of (x1, x2) to be transformed into the right of (x3, x4) scope Should be worth；With it, make the signal strength values of 0 to 140dbm be encoded to be faded to yellow by redness fade to green again Fade to cyan again and fade to blueness again, finally fade to the colourity bar of black.
Method for visualizing based on radio-signal data the most according to claim 3, it is characterised in that described signal to noise ratio Color coding concrete methods of realizing is: use greyscale color pattern, the snr value that scope is 0 to 100 is converted into 0 to 255 One color value of corresponding (0, the 255) scope of each snr value in the range of the color value of scope, i.e. (0,100), this color Value is the greyscale color coding of this signal to noise ratio；The snr value of 0 to 100 is encoded to gradual change gray scale from white to black.
Method for visualizing based on radio-signal data the most according to claim 4, it is characterised in that described step 3 Use DBScan clustering algorithm that radio-signal data is clustered, the Euclidean distance of calculation procedure 2 frequency bandwidth scatterplotAs in clustering algorithm two signal Si,SjDistance between (1≤i, j≤n, i ≠ j).
Method for visualizing based on radio-signal data the most according to claim 5, it is characterised in that described step 3 In, use clustering algorithm that radio-signal data is clustered, and the color of each cluster self-defined；Define each cluster During color, the distribution situation of combining wireless electrical signal data signal intensity, select signal intensity coding do not use and gather with this The color that signaling point Fill Color discrimination in class is high.
7. according to the method for visualizing based on radio-signal data according to any one of claim 1～6, it is characterised in that In described step 4, time span and sample rate that the basis of design radio signal of p gathers select.
8. according to the method for visualizing based on radio-signal data according to any one of claim 1～6, it is characterised in that In described step 4, in described step 5, cluster Ci(1≤i≤k) is divided into timeslice tjAll signals in (1≤j≤p) average The calculation of mid frequency, average bandwidth, average signal-to-noise ratio and average signal strength is as follows:
mFreq i j = &Sigma; m = q q + r S m f r , ( 1 &le; i &le; k ) ( 1 &le; j &le; p ) ;
mBaud i j = &Sigma; m = q q + r S m b r , ( 1 &le; i &le; k ) ( 1 &le; j &le; p ) ;
mDbm i j = &Sigma; m = q q + r S m d r , ( 1 &le; i &le; k ) ( 1 &le; j &le; p ) ;
mSnr i j = &Sigma; m = q q + r S m s r , ( 1 &le; i &le; k ) ( 1 &le; j &le; p ) .
9. according to the method for visualizing based on radio-signal data according to any one of claim 1～6, it is characterised in that In described step 6, two rendering parameters are set: timeslice signaling point degree of rarefication e and continuous sparse timeslice number z, timeslice is believed Number some degree of rarefication represents the minimum signal number in a timeslice, and continuous sparse timeslice number represents that signal number is less than timeslice The sequential time slices number of signal degree of rarefication, is less than e if there is more than or equal to the signaling point in the sequential time slices of z, then Do not draw this segment signal stream.
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