CN115878959A - Situation awareness visualization system for complex electromagnetic spectrum - Google Patents
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Abstract
The invention discloses a situation awareness visualization system for complex electromagnetic spectrum, which comprises: a sensing layer, a data layer and a functional layer; the sensing layer is used for receiving spectrum sensing data collected by discrete position points; the data layer is used for storing and managing the acquired spectrum sensing data and map information data and corresponding equipment data and result data of the acquisition equipment; and the functional layer is used for carrying out fusion processing on the spectrum sensing data of the discrete position points to form regional electromagnetic spectrum situation distribution, presenting the regional electromagnetic spectrum situation distribution by combining with map information data, and positioning the position of the radiation source. The system of the invention forms the spectrum situation data of the whole target area by the interpolation completion and calculation mode for the collected data of the spectrum in the area, not only simply showing the spectrum situation of the data sampling point.
Description
Technical Field
The invention belongs to the technical field of electromagnetic environment measurement, and particularly relates to a situation awareness visualization system for complex electromagnetic spectrum.
Background
The wireless spectrum situation of the target area is presented in a visual mode in the electromagnetic spectrum battle, and the method has very important significance for frequency analysis, frequency assignment, spectrum situation trend analysis, spectrum resource management auxiliary decision and the like of the battle environment.
Currently, in the field of radio spectrum management, there are many software or methods for collecting and processing spectrum data. There are also many and mature processing methods for spectrum data acquisition, display, statistical information analysis and signal data analysis. However, the field has relatively little work in these aspects, in which a plurality of interpolation methods are used comprehensively based on discrete acquisition sample points to obtain the frequency spectrums of all target regions, and spectrum analysis, assistant decision information output and positioning of transmission signal sources are performed based on the frequency spectrum information of all regions.
The frequency spectrum data collected by the frequency spectrum sensing equipment is discrete point data, and a key technical point of comprehensive processing of the frequency spectrum situation is how to obtain the frequency spectrum situation on the target area from the frequency spectrum data of the discrete position points through calculation, completion and other processing, and display and support subsequent application in a visual mode.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provides a situation awareness visualization system for complex electromagnetic spectrum.
In order to achieve the above object, the present invention provides a situation awareness visualization system oriented to a complex electromagnetic spectrum, which is characterized in that the system includes: a sensing layer, a data layer and a functional layer; wherein,
the sensing layer is used for receiving spectrum sensing data collected by discrete position points;
the data layer is used for storing and managing the acquired spectrum sensing data, storing and managing map information data and acquisition equipment related information of the spectrum sensing data, and storing and managing result data processed by the functional layer;
and the functional layer is used for carrying out fusion processing on the spectrum sensing data of the discrete position points to form regional electromagnetic spectrum situation distribution, presenting the regional electromagnetic spectrum situation distribution by combining with map information data, and positioning the position of the radiation source.
As an improvement of the above system, the functional layer includes a fusion processing module, and the processing procedure of the fusion processing module includes:
acquiring spectrum sensing data of a designated section;
extracting frequency point data according to the frequency band and the step length;
filtering invalid data and repairing data with errors;
eliminating the influence of fast fading on the repaired spectrum sensing data through clustering filtering;
selecting a corresponding interpolation algorithm according to the frequency spectrum sensing data to generate a single-frequency point situation map;
and synthesizing the situation maps of the frequency points to obtain regional electromagnetic spectrum situation distribution.
As an improvement of the system, the corresponding interpolation algorithm comprises natural neighborhood interpolation processing, thin-plate spline interpolation processing and kriging interpolation processing.
As an improvement of the foregoing system, the natural neighbor interpolation processing specifically includes:
finding N discrete position points with the nearest distance to the point to be inquired, and establishing N corresponding Voronoi diagrams;
for a point z to be interpolated, defining a polygon which is changed due to the addition of z as a neighboring area of z, wherein the intersection of a new polygon and an original polygon determines the influence weight of a corresponding discrete position point on the interpolated point z;
and proportionally applying weights to the spectrum sensing data of the N discrete position points for interpolation based on the Voronoi diagram sizes of the N discrete position points.
As an improvement of the above system, the thin-plate spline interpolation processing process specifically includes:
collecting frequency spectrum data at a certain region position as spline interpolation data p at a corresponding region position i ，p j The radial basis function U (p) is calculated according to the following formula i ,p j )：
U(p i ,p j )＝σ(p i -p j ) 2 log(σ(p i -p j ))
Wherein, σ (p) i -p j ) Corresponding to the Euclidean distance, lng, between two points on a two-dimensional plane i 、lng j Longitude, lat, representing the ith, j data collected i 、lat j Representing the latitude of the ith and j th acquired data;
based on radial basis function U (p) i ,p j ) Obtaining the weight w of the predicted point x of the ith sample point i,x ，
Obtaining a numerical value V (x) of a point to be predicted by adopting weighting calculation:
wherein w i,x Is, V (x) i ) Is the value of the ith sample point.
As an improvement of the above system, the kriging interpolation processing process specifically includes:
and establishing an unbiased estimation matrix of the measurement difference and the distance between the data position points based on the corresponding relation between the path loss and the distance of the electromagnetic radiation, and realizing interpolation prediction.
As an improvement of the above system, the functional layer includes a situation localization module, and a processing procedure of the situation localization module specifically includes:
and positioning the radiation source by combining a preset signal intensity threshold and geographic information data according to the frequency spectrum situation graph generated by the fusion processing module.
As an improvement of the foregoing system, the functional layer further includes an available frequency recommending module, and a processing procedure of the available frequency recommending module specifically includes:
judging whether the field intensity value of each frequency point in the service frequency band exceeds a set threshold value one by one according to the frequency spectrum sensing data, if so, judging that the frequency point is occupied, otherwise, judging that the frequency point is not occupied, and performing channel quality analysis;
and counting the available frequency conditions in the service frequency band and outputting an available frequency recommendation list by combining with channel quality analysis.
Compared with the prior art, the invention has the advantages that:
1. compared with the prior similar technology, the system has the greatest characteristic that the frequency spectrum situation data of the whole target area is formed by the interpolation completion and calculation mode for the acquired data of the frequency spectrum in the area, not only the frequency spectrum situation of the data sampling points is simply displayed;
2. the method supports the comprehensive application of various interpolation methods on the basis of the existing interpolation processing method, supports three methods of a natural neighborhood interpolation method, a kriging interpolation method and a thin plate spline interpolation at present, and can be used for selecting a proper processing method according to different application scenes;
3. the statistical analysis function based on the regional frequency spectrum is another characteristic of the system, and comprises results of frequency spectrum occupation of a target region, available frequency recommendation of any position point in the region and the like, and the results can be displayed in a visual mode in the system.
4. The invention can provide positioning based on the regional spectrum situation, and can find out the region which accords with the signal situation characteristics of the emission source based on the result of the regional spectrum situation, thereby positioning the emission signal source.
Drawings
FIG. 1 is a system composition diagram of the present invention;
FIG. 2 is a software system composition diagram;
FIG. 3 is a diagram of data and interface protocol relationships;
FIG. 4 is a flow chart of available frequency recommendation;
FIG. 5 is an example of a list of available frequency recommendations;
FIG. 6 is a situation localization flow diagram;
FIG. 7 is a fusion process flow;
FIG. 8 is a schematic diagram of a natural neighbor interpolation algorithm;
FIG. 9 is a schematic diagram of a thin plate spline algorithm;
FIG. 10 is a block diagram of a standalone task deployment mode;
figure 11 is a block diagram of a local networking deployment scenario.
Detailed Description
The method mainly comprehensively applies the existing multiple interpolation methods to the processing of the frequency spectrum acquisition data by points and planes, and calculates and supplements the frequency spectrum sensing sample data of the movable equipment to obtain the frequency spectrum situation result on the target area. And analyzing the spectrum situation on the basis, and displaying the results of spectrum occupation statistical analysis, available frequency, emission signal positioning and the like in a visual mode.
The technical solution of the present invention will be described in detail below with reference to the accompanying drawings and examples.
Examples
As shown in fig. 1, embodiment 1 of the present invention provides a situation awareness visualization system for complex electromagnetic spectrum, which includes: a sensing layer, a data layer and a functional layer; wherein,
the sensing layer is used for receiving spectrum sensing data collected by discrete position points;
the data layer is used for storing and managing the acquired spectrum sensing data and map information data and corresponding equipment data and result data of the acquisition equipment;
the functional layer is used for carrying out fusion processing on the frequency spectrum sensing data of the discrete position points to form regional electromagnetic spectrum situation distribution, presenting the regional electromagnetic spectrum situation distribution by combining with map information data and positioning the position of the radiation source
The sensing layer is a digital signal comprehensive analysis unit and is used for collecting frequency spectrum data; the data layer comprises data for analysis, result data, map data for display and the like; and (3) a service layer: spectrum collection, background spectrum, statistical analysis, available frequency recommendation and situation localization.
1. Software composition
The specific software composition is shown in fig. 2. The system mainly comprises data management and service functions, wherein the data management comprises geographic information data management, frequency spectrum data management, acquisition equipment management and result data management; the service function comprises five functions of frequency spectrum acquisition, background frequency spectrum learning, statistical analysis, available frequency recommendation and situation positioning, and the service requirement is met.
2. Data and interface protocol
The spectrum data collected by the digital signal comprehensive analysis unit is subjected to fusion algorithm analysis and visualized display, and the specific interface relationship is shown in fig. 3.
3. Function and performance index design
1. Background spectrum learning function
Through deep analysis of monitoring data acquired by the frequency spectrum, a background frequency spectrum is learned, an initial frequency, a step and a threshold value are formulated according to different service frequency bands, and a stable background frequency spectrum is generated in different time periods.
TABLE 1 background Spectrum learning index List
Setting starting frequency, learning stepping and time period setting, and supporting generation of independent background frequency spectrum every time, every day and every week.
2. Statistical analysis function
The system provides a plurality of data analysis functions, including frequency scanning data (maximum, minimum and mean), single-frequency point stability statistics, frequency scanning waterfall diagram analysis and frequency occupancy statistics in different time periods.
The functions are as follows:
frequency sweep data (maximum, minimum, mean)
And analyzing the maximum value and the minimum value appearing in the scanning data in a period of time, and calculating the average value of the scanning data in the accumulation time.
Single frequency Point stability statistics
And continuously monitoring the single frequency point, and recording the change condition of the intensity of the frequency signal within a period of time.
Waterfall graph analysis
The scan data is accumulated over time and the signal strength of the scan data is represented in different colors.
Statistics of occupancy rates at different time bands
And analyzing whether the signal intensity in a certain frequency reaches or exceeds the threshold of the frequency or not by using a manually or automatically calculated signal threshold, and counting the times of reaching or exceeding the threshold, wherein the times account for the percentage of the total measurement times and are the time occupancy rate.
Frequency occupancy refers to the percentage of occupied frequencies to the total frequency.
3. Available frequency recommendation
And acquiring the occupation and non-occupation conditions of the frequency points on different channels according to the sweep frequency test data, feeding back that the frequency points are occupied when the field intensity value of the frequency points exceeds a set threshold value, and feeding back that the frequency points are not occupied when the field intensity value of the frequency points does not exceed the set threshold value. And counting the available frequency situation in the service frequency band. Fig. 4 is a flow chart illustrating the available frequency recommendation. Fig. 5 is an example of a list of available frequency recommendations.
And analyzing the frequency use condition at a certain position based on the existing monitoring data and the frequency division condition thereof.
4. Situation localization
The system generates a spectrum situation map by combining spectrum acquisition monitoring data fusion analysis and an interpolation algorithm, and analyzes the change of field intensity values in a region to position the position of a radiation source.
Function input:
Function output
Radiation source position information. Fig. 6 shows a situation localization flowchart.
And for scenes with higher requirements on processing speed and larger sample size, natural neighbor interpolation processing is adopted. The natural neighborhood method is a reinforced form of the Thiessen polygon method, has general expression in approximation degree and better expression in calculation capacity, is simpler and more accords with the inherent thinking of people. But is limited in use range, and is mainly suitable for scenes with small range areas and low spatial variability. Because the processing method is relatively simple, the method has better performance in the aspect of processing speed, and the sample size of a larger scene can be used;
for the case that the number of data sample points is large, thin plate spline interpolation processing is adopted, and the method can complete calculation processing within an acceptable time range. The deformation in physical shape simulated by the thin-plate spline interpolation method is nearly all bio-related deformations that can be approximated by this method. The method has the advantages that relatively good effect can be obtained on the electromagnetic wave spectrum data calculation by using the thin plate spline interpolation, and the method has certain disadvantage on the theoretical approximation degree, but has great advantages in the aspects of calculation speed and calculation capacity;
and performing kriging interpolation processing on the spectrum sensing data of the discrete sampling points. The common Kriging interpolation has the characteristics of good approximation degree, strong calculation capability and wide application range. However, the interpolation algorithm of the common kriging requires a large amount of calculation in processing speed, and particularly under the condition of a large number of sample points, the calculation time of the method is long. For this reason, in the application of actual electromagnetic spectrum situation generation, when the number of sample points exceeds 100, the method is not suitable for processing.
5. Situation flow design
In order to realize the fusion of the spectrum sensing data of the sensing node collected discrete position points into regional electromagnetic spectrum situation distribution and further combine the geographic information system for presentation, the scheme is supposed to adopt three interpolation algorithms to perform data fusion processing: interpolation of natural neighbors, thin-plate spline interpolation, kriging interpolation.
The data fusion processing flow is shown in fig. 7.
The three interpolation algorithms are described in detail below.
1) Interpolation of natural neighbors
The natural neighborhood algorithm may find the subset of input samples that are closest to the query point and apply weights to these samples in proportion based on the region size for interpolation. This interpolation is also referred to as Sibson or "area-occupying" interpolation. The interpolation algorithm is also divided into two steps, firstly, a Voronoi diagram is established by using the monitoring points, then, each grid point is interpolated, and the establishment and the interpolation of the Voronoi diagram are respectively explained below.
Voronoi diagram, also called a thiessen polygon or Dirichlet diagram, is a continuous polygon composed of a set of perpendicular bisectors connecting two adjacent point lines. N points which are distinguished on the plane are divided into planes according to the nearest principle; each point is associated with its nearest neighbor region. A Delaunay triangle is a triangle formed by connecting related points that share one edge with adjacent Voronoi polygons. The center of the circumscribed circle of the Delaunay triangle is a vertex of the Voronoi polygon associated with the triangle. The Voronoi triangle is an even graph of the Delaunay diagram.
If the set of points consists of N points, the area of points closer to Pi than to other points is the intersection of the N-1 half-planes containing Pi. The N-1 half planes are defined by the perpendicular bisectors of the Pi points and the other points. V (i) is a polygon made up of perpendicular bisector segments. The area of each point is made by the method described above, and a point Voronoi diagram is formed. The method divides the whole plane into N areas, each area comprises a point, the area is the area of the point, line segments or rays in the area are called Voronoi edges, the line segments or rays are certainly a segment of a perpendicular bisector of a connecting line of two points, the two points are called relevant points of the Voronoi edges, intersection points between the Voronoi edges are called Voronoi vertexes, and the relevant points of the Voronoi edges are also the relevant points of the Voronoi vertexes. In addition, if the point (x, y) ∈ V (i), pi is the closest point to the point (x, y). As shown in fig. 8.
Regarding interpolation: if x is the point to be interpolated, the original Voronoi will change due to the addition of the point x, and as shown in the above figure, because the polygon changed due to the addition of x is the neighborhood of x, the intersection of the new polygon and the original polygon determines the weight of the influence of the sample point on the interpolated point x, so that the value of x can be calculated by the following formula:
wherein ai is the value of the ith adjacent cell sample point, wi is the weight of the ith adjacent cell, and the calculation formula of the weight wi is as follows:
2) Thin plate sample strip method
Thin Plate Spline interpolation TPS (Thin Plate Spline) is an interpolation constructed by constructing a smooth functional expression. When the interpolation is applied to the radio wave propagation condition, the radial change rule of the measuring point and the peripheral points thereof is comprehensively considered. On the basis of comprehensively considering the distance and the loss of the propagation model, a gradient change matrix of the electromagnetic prediction points and the measurement points is constructed, and the interpolation has certain outward ductility.
Thin-plate spline interpolation is the visualization of an interpolation function to bend a thin steel sheet so that it passes through a given point, which would require a bending energy. The interpolation method can minimize the bending amount of the steel plate under the condition of ensuring that all control points can be matched as much as possible. Fig. 9 shows a schematic diagram of the control points and the interpolation surface.
The principle of the thin-plate spline is based on the fact that the surface represented by it minimizes a functional consisting of the norm of the 2 nd derivative of an element in the Hilbert space, i.e., the upper
The functional has rotational invariance and can approximately represent the bending energy of the sheet as determined by the binary function Φ. The curved surface obtained by the thin plate spline method corresponds to a curved surface obtained by deforming a thin plate under a certain pressure. This pressure is applied at each observation point (known as a scatter point) with a magnitude proportional to the property value of the observation data point. The thin-plate splines have the property of minimal bending, and Φ becomes a spline of minimal bending.
Φ in the above formula is defined as follows:
wherein m is 0 、m 1 And m 2 Is a real number, ω i Is the weight of the observed sample point. Is a radial basis function. This function is a combination of the interpolation method and the patented method, and is described with emphasis in the following paragraphs.
According to the requirement of minimum bending energy, omega can be solved i 、m 0 、m 1 And m 2 Thus, the value of any point can be predicted. The formula solved is as follows:
(ω 1 ,ω 2 ,...,ω n ,m 0 ,m 1 ,m 2 ) T ＝L -1 *Y
Y＝(v 1 ,v 2 ,...,v n ,0,0,0) T
estimated value Z (p) at any point x,y ) Can be calculated by the following formula
The thin plate spline interpolation method is applied to the system, and spectrum data on a certain area position are collected to be used as input data of the interpolation method. The distribution of the acquired data per se on the region position corresponds to p of the thin plate spline interpolation data i . The process calculates the weights using the radial basis functions. Radial basis function U (p) i ,p j ) The expression of (a) is as follows:
U(p i ,p j )＝σ(p i ,p j ) 2 log(σ(p i ,p j ))
wherein σ (p) i -p j ) Corresponding to the Euclidean distance between two points on a two-dimensional plane
Wherein lng i 、lng j Longitude, lat, representing the ith, j data collected i 、lat j The latitude of the ith and jth acquired data is shown.
3) Kriging (Kriging) interpolation
The kriging method is to generate continuous surface data from discrete reference point data according to related attribute values, and the regional variable of the kriging method has two characteristics: 1) Randomness: features that appear local, irregular, random, difficult to predict; 2) The structure is as follows: the random variables Z (x) and Z (x + h) of two points x and x + h in space have the characteristic of autocorrelation, and the autocorrelation characteristic is related to the distance h between the two points in space and the characteristic of the variables.
The perception data Z (x, y) can be considered as regionalized study variables, which are two-dimensional spatially distributed data. On one hand, after a point m in space is fixed, the sensing data measurement value Z (m) is uncertain and can be regarded as a random variable, so that the randomness of the sensing data measurement value Z (m) is reflected; on the other hand, the perceptual data measurements Z (m) and Z (m + h) at two different points m and m + h in space (where h represents a distance vector in two-dimensional space whose modulo | h | represents the distance of points m and m + h) have some degree of autocorrelation, generally the smaller h the better the correlation. The autocorrelation embodies certain continuity and relevance of the sensing data measured value variable and embodies one side of the structure of the sensing data measured value variable.
There is a certain investigation region D for which the regionalized investigation variable Z (x) is E.D, x 1 ,x 2 ,…,x n Obtaining n observation points, Z (x), for a region 1 ),Z(x 2 ),…,Z(x n ) Is the corresponding observed value. There is some unsampled point x in the area 0 The estimated value is z * (x 0 )，z * (x 0 ) The estimate can be made by a linear relationship:
in the above formula λ i The measured value at the ith position is unknown weight, and therefore the aim of the kriging interpolation is to obtain the weight. Since the kriging interpolation is an unbiased optimization interpolation, the unbiased and minimum estimation variance become the selection standard of the weight lambda, and the equation set of the kriging interpolation can be obtained
Writing the equation set of the above formula into a matrix form
[K']·[λ']＝[M']
The attribute value of an unsampled point is obtained through a kriging interpolation, known sampling point data need to be analyzed, an experimental variation function value is obtained, and a discrete experimental variation function value is fitted through a theoretical variation function model to obtain a variation function model of the sampling point data.
And solving the equation set to obtain the weighted value of the kriging interpolation.
λ'＝K' -1 *M'
Substituting the solved weight into a formula to obtain the attribute value of the non-sampling point. Of the system of equations
Is a half variance function and is considered ≥ due to a spatial similarity attribute>
The half variance function and the spatial distance d (x) i ，x j ) The relationship can be fitted with a linear, exponential or logarithmic relationship. In the method, a kriging exponential model function is used for fitting.
When electromagnetic spectrum interpolation is considered, an unbiased estimation matrix of the measurement difference and the distance between monitoring points is established based on the corresponding relation between the path loss and the distance of electromagnetic radiation (based on an electromagnetic wave propagation model), and Kriging interpolation prediction is realized.
The application of the kriging interpolation method in combination with the present invention is in the distance d (x) between points from a data location i ，x j ) To the formula for covariance calculation. This transformation is modeled as a kriging exponential function, as shown in the above equation. In the formula c 0 The piece constant of the kriging index model is generally 0.c is the arch height in the model, d 0 For variables in the model, c and d 0 And an empirical value with a good effect can be obtained according to the result of actual sample data processing.
4. Software deployment
The system supports two working deployment modes of stand-alone deployment and networking.
The stand-alone task is to analyze the spectrum information by connecting the receiver to a handheld device or a notebook computer as shown in fig. 10.
The local networking deployment mode is composed of a plurality of units and a control terminal, and the devices realize a working mode of networking cooperative communication through a local area network, as shown in fig. 11.
5. Environmental and adaptive design
The system is compatible with a Windows system and an Android system, can be used at a computer end and a mobile phone end, and is convenient to use in different scenes.
6. Reliability design
The system can continuously work for 7 multiplied by 24 hours, and the following strategies are adopted to ensure the reliable work of the system:
(1) Data slicing strategy
After the system software starts to collect the frequency spectrum data, the frequency spectrum data is automatically stored in the appointed attached record and is stored as a file in the size of 200M, and the problem that the loading is slow due to the fact that the file is too large is solved.
(2) Software hierarchy
The software structure can be roughly divided into four layers of programs, sub-programs, modules and program units. The program refers to an instruction set which can independently run and execute a complete function in software; split refers to a subset of primary functions in a program; a module refers to a logically separable portion of a program; a program element refers to a procedure or routine. A good software hierarchy should be a tree-like structure with clear stems and veins and well-defined levels.
(3) Avoiding design complications
The software design should implement the principle of simplicity, namely reliability, and the internal logic structure and algorithm of the program are clear and easy to read. The number of parallel modules, the number of multiple cycles and the depth of a nested layer are controlled within 7; the maximum number of executable source code statements of each program unit is not more than 200, and the average number of executable source code statements of each program unit is not more than 60; each program should be started with brief descriptions about functions, input and output, local variables, etc., and the program is supplemented with an appropriate amount (generally not less than 20% of the source code) of comment statements.
(4) Fault tolerant design
The software fault tolerance refers to the adoption of a fault-tolerant software structure design, and when the software fails, the software automatically recovers the function or controls the influence caused by the failure under the condition of no manual intervention.
7. Maintainability design
The following measures are taken to ensure system maintainability:
(1) The system is designed in a modularized mode, the problem is convenient to maintain and troubleshoot, and the system software has an operation log file, records the operation log of the software and is convenient to trace the problem.
(2) The system design and the coding are standard, and the system software is realized according to the standard, so that the software can be conveniently understood and modified.
(3) The system has a complete and simple system installation tool, and can support functions of local or full system automatic installation and deployment, rapid repair, version upgrade and the like.
(4) The log is recorded in key operation and abnormal conditions in the system operation process, and when problems are checked, the method is beneficial to software operation and maintenance personnel to quickly position, reproduce and solve the problems.
Innovation point
Spectrum situation synthesis and presentation technology based on geographic information
Aiming at the bottleneck problem that the traditional spectrum sensing means cannot acquire complete wide-area spectrum situation information and the like due to the current situations of electromagnetic space three-dimension, spectrum fragmentation and the like, the method takes GIS information as data base, performs spectrum data fusion from time, space and frequency universes based on a self-adaptive interpolation algorithm, and presents a multi-dimensional spectrum situation.
Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not limited. Although the present invention has been described in detail with reference to the embodiments, it will be understood by those skilled in the art that various changes may be made and equivalents may be substituted without departing from the spirit and scope of the invention as defined in the appended claims.
Claims (8)
1. A situation awareness visualization system oriented to complex electromagnetic spectrum, the system comprising: a sensing layer, a data layer and a functional layer; wherein,
the sensing layer is used for receiving spectrum sensing data collected by discrete position points;
the data layer is used for storing and managing the acquired spectrum sensing data, storing and managing map information data and acquisition equipment related information of the spectrum sensing data, and storing and managing result data processed by the functional layer;
the functional layer is used for carrying out fusion processing on the frequency spectrum sensing data of the discrete position points to form regional electromagnetic spectrum situation distribution, presenting the regional electromagnetic spectrum situation distribution by combining with map information data, and positioning the position of the radiation source.
2. The complex electromagnetic spectrum-oriented situation awareness visualization system according to claim 1, wherein the functional layer comprises a fusion processing module, and a processing procedure of the fusion processing module comprises:
acquiring spectrum sensing data of a designated section;
extracting frequency point data according to the frequency band and the step length;
filtering invalid data and repairing data with errors;
eliminating the influence of fast fading on the repaired spectrum sensing data through clustering filtering;
selecting a corresponding interpolation algorithm according to the frequency spectrum sensing data to generate a single-frequency point situation map;
and synthesizing the situation maps of the frequency points to obtain regional electromagnetic spectrum situation distribution.
3. The complex electromagnetic spectrum-oriented situation awareness visualization system according to claim 2, wherein the corresponding interpolation algorithm comprises natural neighborhood interpolation, thin-plate spline interpolation, and kriging interpolation.
4. The complex electromagnetic spectrum-oriented situation awareness visualization system according to claim 3, wherein the natural neighborhood interpolation processing specifically includes:
finding N discrete position points with the nearest distance to the point to be inquired, and establishing N corresponding Voronoi diagrams;
for a point z to be interpolated, defining a polygon which is changed due to the addition of z as a neighboring area of z, wherein the intersection of a new polygon and an original polygon determines the influence weight of a corresponding discrete position point on the interpolated point z;
and proportionally applying weights to the spectrum sensing data of the N discrete position points for interpolation based on the Voronoi diagram sizes of the N discrete position points.
5. The complex electromagnetic spectrum-oriented situational awareness visualization system according to claim 3, wherein the thin-plate spline interpolation processing specifically includes:
collecting frequency spectrum data at a certain region position as spline interpolation data p at a corresponding region position i ，p j The radial basis function U (p) is calculated according to the following formula i ,p j )：
U(p i ,p j )＝σ(p i -p j ) 2 log(σ(p i -p j ))
Wherein, σ (p) i -p j ) Corresponding to the Euclidean distance, lng, between two points on a two-dimensional plane i 、lng j Longitude, lat, representing the ith, j data collected i 、lat j Representing the latitude of the ith and the jth acquired data;
based on radial basis function U (p) i ,p j ) Obtaining the weight w of the ith sample point to the predicted point x i,x ，
Obtaining a numerical value V (x) of a point to be predicted by adopting weighting calculation:
wherein, V (x) i ) Is the value of the ith sample point.
6. The complex electromagnetic spectrum-oriented situation awareness visualization system according to claim 3, wherein the kriging interpolation processing procedure specifically comprises:
and establishing an unbiased estimation matrix of the measurement difference and the distance between the data position points based on the corresponding relation between the path loss and the distance of the electromagnetic radiation, and realizing interpolation prediction.
7. The complex electromagnetic spectrum-oriented situation awareness visualization system according to claim 2, wherein the functional layer comprises a situation localization module, and a processing procedure of the situation localization module specifically comprises:
and positioning the radiation source by combining the preset signal intensity threshold and the geographic information data according to the frequency spectrum situation map generated by the fusion processing module.
8. The complex electromagnetic spectrum-oriented situation awareness visualization system according to claim 1, wherein the functional layer further comprises an available frequency recommendation module, and the processing procedure of the available frequency recommendation module specifically comprises:
judging whether the field intensity value of each frequency point in the service frequency band exceeds a set threshold value one by one according to the frequency spectrum sensing data, if so, judging that the frequency point is occupied, otherwise, judging that the frequency point is not occupied, and analyzing the channel quality;
and counting the available frequency conditions in the service frequency band and outputting an available frequency recommendation list by combining with channel quality analysis.
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