CN110366188B - Interference measurement point deployment method, interference measurement path planning method and system - Google Patents
Interference measurement point deployment method, interference measurement path planning method and system Download PDFInfo
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Abstract
The invention discloses an interference measurement point deployment method, an interference measurement path planning method and an interference measurement path planning system.
Description
Technical Field
The invention relates to a deployment method of interference measurement points of a power wireless private network, and a planning method and a system of interference measurement paths, and belongs to the field of power grid optimization.
Background
LTE (Long Term Evolution) is a Long Term Evolution Project of UMTS (Universal Mobile Telecommunications System) technical standards, which is established by The 3rd Generation Partnership Project (3 GPP) organization. With the popularization of the LTE system, the network scale and the number of users increase rapidly, and the wireless environment becomes more complex, so that the interference problem becomes more and more prominent, and becomes an important factor affecting the call quality, the network coverage and the like. Interference present in an LTE network can be divided into intra-network interference and extra-network interference. The interference in the network mainly comes from co-frequency interference and adjacent frequency interference, and compared with the interference in the network, the wireless propagation environment outside the network is complex, and the interference sources outside the network are various, such as a television station, a high-power radio station, a radar, a simulation base station and the like. The acquisition of the off-grid interference measurement information mainly depends on a technician driving a vehicle to a field test by using a sweep generator, and large manpower and material resources are consumed.
In order to efficiently acquire the outward interference, interference measurement points are deployed in an area to measure information such as the intensity of the interference, but how to reasonably select the interference measurement points and plan a measurement path is still a problem which needs to be solved urgently.
Disclosure of Invention
The invention provides an interference measurement point deployment method, an interference measurement path planning method and an interference measurement path planning system, which solve the problems disclosed in the background technology.
In order to solve the technical problems, the technical scheme adopted by the invention is as follows:
an interference measurement point deployment method comprises the following steps,
constructing an interference measurement point deployment model of a deployment area;
based on an interference measurement point deployment model, a multi-objective evolutionary algorithm is adopted to obtain a group of deployment schemes;
and evaluating all the deployment schemes in the group, and selecting a plurality of deployment schemes with the top evaluation ranking as final schemes.
The process of determining the deployment area is as follows,
determining all interfered points;
as bounding boxes B enclosing all disturbed points1Surrounding box B1The enclosed area is an interfered area;
in the bounding box B1Searching the nearest undisturbed point in each direction;
as bounding boxes B enclosing undisturbed points2Surrounding box B2The enclosed area is a deployment area.
The deployment model structure of the interference measurement point is that,
optimizing the target:
the number of interference measurement points in the deployment area is minimal;
the coverage rate of interference measurement points in a deployment area is maximum;
the sum of the distances between all the interference measurement points and the nearest road in the deployment area is minimum;
the number of all interference measurement points in the deployment area far away from the road is minimum;
the density of interference measurement points deployed in the area with strong interference is greater than that of the area with weak interference;
constraint conditions are as follows:
the number of the interference measurement points is greater than or equal to the lower number limit and less than or equal to the upper number limit;
the interference measurement point is located in the deployment area;
inputting:
the boundary information of the deployment area comprises the number of boundary inflection points and inflection point coordinates;
grid information of the grid deployment area comprises grid center coordinates, grid quantity, grid geographic attributes after the grid image layers and the ground object image layers are overlapped, information carried by the grid geographic attributes and interference strength marks borne by the grids;
an upper limit and a lower limit of the number of interference measurement points;
and (3) outputting:
and a plurality of deployment schemes, wherein the deployment schemes comprise the number of the interference measurement points and the coordinates of the interference measurement points.
And obtaining a group of deployment schemes by adopting a Pareto competition method based on the interference measurement point deployment model.
An interference measurement path planning method comprises the following steps,
adopting an interference measurement point deployment method to obtain a plurality of deployment schemes of the interference measurement points;
constructing an interference measurement path scheme according to the deployment scheme;
and evaluating all interference measurement path schemes, and selecting a plurality of interference measurement path schemes which are evaluated and ranked in the front as final paths.
The process of constructing the interference measurement path scheme is,
abstracting road network information and interference measuring point information into a graph G;
converting the graph G into an Euler graph according to the number of odd degree nodes in the graph G;
the euler loop of the euler diagram is an interference measurement path scheme.
The process of abstracting the graph G is,
projecting the interference measurement points in the deployment scheme into a road network;
in response to the fact that the distance between the interference measuring point and the nearest road exceeds the maximum measuring range of the interference measuring point, the interference measuring point is split to a plurality of surrounding roads to form a new interference measuring point;
the interference measurement point and the drive test starting point are set as vertices, the distance between each vertex is set as an edge, and the vertices and the edges form a graph G.
The process of converting the graph G into the euler graph is,
there are no odd numbered nodes in graph G: FIG. G is a Euler diagram;
there are two odd degree nodes in graph G:
finding out the shortest path of two odd-degree node pieces;
adding the shortest path in the graph G to obtain an Euler graph;
there are 2n odd degree nodes in graph G, n being an integer greater than 1:
finding out the shortest paths among all odd degree nodes;
using a 0-1 programming method to obtain the optimal pairing among all odd-degree nodes;
and adding the shortest path of the optimal matching part in the graph G to obtain an Euler graph.
An interference measurement point deployment system includes,
a deployment model building module: constructing an interference measurement point deployment model of a deployment area;
a deployment scenario acquisition module: based on an interference measurement point deployment model, a multi-objective evolutionary algorithm is adopted to obtain a group of deployment schemes;
a deployment scenario evaluation module: and evaluating all the deployment schemes in the group, and selecting a plurality of deployment schemes with the top evaluation ranking as final schemes.
An interference measurement path planning system, comprising,
an interference measurement point deployment system;
an interference measurement path scheme construction module: constructing an interference measurement path scheme according to the deployment scheme;
an interference measurement path scheme evaluation module: and evaluating all interference measurement path schemes, and selecting a plurality of interference measurement path schemes which are evaluated and ranked in the front as final paths.
The invention achieves the following beneficial effects: according to the method, a group of deployment schemes are obtained by adopting a multi-objective evolutionary algorithm, a plurality of deployment schemes with the front evaluation sequencing are selected as final schemes, interference measurement path schemes are constructed according to the final schemes, and a plurality of interference measurement path schemes with the front evaluation sequencing are selected as final paths, so that interference measurement points and planning measurement paths are conveniently selected.
Drawings
FIG. 1 is a flow chart of the present invention;
FIG. 2 is a diagram of a deployment area architecture;
FIG. 3 is a flow chart of a solution of a multi-objective evolutionary algorithm;
FIG. 4 is a split view of interference measurement points;
fig. 5 is a schematic view of fig. G.
Detailed Description
The invention is further described below with reference to the accompanying drawings. The following examples are only for illustrating the technical solutions of the present invention more clearly, and the protection scope of the present invention is not limited thereby.
As shown in fig. 1, the method for deploying interference measurement points includes the following steps:
step 1, network coverage area B0And (6) rasterizing.
1.1) along X axis, Y axis and Z axis of a space rectangular coordinate system, respectively covering the network coverage area B with side lengths l, w and h0Divided into three-dimensional grids, i.e. network coverage areas B0Dividing grids, wherein the length of the grid is l, the width of the grid is w, and the height of the grid is h, and obtaining a grid set { g (x, y, z) }, wherein g (x, y, z) is the grid, and (x, y, z) is the coordinate of the center point of the grid, and the strength of the signal received by the grid from the interference measurement point is defined as the strength of the signal at the center point of the grid.
1.2) carrying out superposition analysis on the grid map layer and the ground object map layer by utilizing a superposition analysis function of a GIS (geographic information system), recording a geographic identification ID in each grid and a ratio of the geographic identification ID to the current grid, wherein the ratio belongs to [0,1], and providing a basis for subsequent obstacle avoidance deployment of interference measurement points, wherein the geographic identification ID corresponds to geographic attributes (such as rivers, greenbelts, buildings and the like) and information carried by the geographic attributes and the like.
1.3) obtaining interference data from a network management platform, analyzing by interpolation methods such as spatial interpolation and the like to obtain the interfered degree inf of each grid, wherein inf belongs to [0,1], marking and distinguishing the grids with high interfered strength, providing reference for subsequent interference measurement point deployment, and if the areas with high interfered strength need to deploy more interference measurement points for measurement.
1.4) get the expanded grid set g (x, y, z, ID, ratio, inf).
And 2, determining a deployment area of the interference measurement point.
2.1) for B0Determining the interfered cell/base station according to the cell/base station network management statistical information, the equipment terminal measurement information, the drive test frequency sweep information, the user complaint and other information; determining an interfered equipment terminal according to a measurement index reported by the equipment terminal; according to the interference measurement value of the sweep frequency/road measurement point, determining the interfered sweep frequency/road measurement point, wherein the interfered cell/base station, the equipment terminal and the sweep frequency/road measurement point form an interfered point set InfSet0。
2.2) determining all interfered points: from InfSet according to a predefined interference threshold0And screening interfered points with interference degrees exceeding an interference threshold value to form an interfered point set InfSet.
2.3) making a bounding box B surrounding all disturbed points, as shown in FIG. 21Surrounding box B1The enclosed area is an interfered area.
2.4) in the bounding box B1And searching the nearest undisturbed point in all directions.
2.5) making a bounding box B surrounding the undisturbed point2Surrounding box B2The enclosed area is a deployment area.
And 3, determining the upper limit and the lower limit of the number of the interference measurement points in the deployment area.
3.1) determining the physical characteristics such as the strength, the type and the like of the interference measurement point signal;
through a drive test management platform or other various channels, the type and the strength of a signal used in the drive test are acquired, factors such as city actual environment or weather conditions are considered, and the attenuation degree of the signal in different media is evaluated and analyzed.
3.2) determining the maximum range reached by the interference measuring point signal;
and 3.1, obtaining the maximum range Maxrange reached by the signal and the minimum range Minrange reached by the signal due to interference of some factors by referring to a type attenuation formula used by the drive test signal and combining with the actual situation of the city and considering the surrounding environment and terrain factors of the city according to the data obtained in the step 3.1.
3.3) determining the upper limit and the lower limit of the number of the interference measurement points;
in B2And obtaining a signal coverage range (the signal coverage is a circle, and the side length of the inscribed square is the coverage radius)
Multiple) of the largest inscribed square and the smallest inscribed square; binding of B2The shape of (2) and the coordinates of the boundary points, the whole B being inscribed by a square2And covering, and calculating the maximum number Maxnum and the minimum number Minnum of the interference measurement points.
And 4, constructing an interference measurement point deployment model of the deployment area.
And selecting a plurality of grid points from the deployment area according to different optimization targets and constraint conditions to form an interference measurement point deployment scheme, so that a good optimization effect is achieved on each optimization target during interference path measurement.
By researching and analyzing factors such as distribution of possible interference, attenuation of measurement signals, maximum and minimum range of signals and the like, various qualitative and quantitative constraints required to be met by an optimization scheme and a plurality of expected quantitative optimization targets are determined, and a multi-target multi-optimization model of the interference measurement point deployment problem is established.
The structure of the deployment model of the interference measurement points is as follows:
optimizing the target:
1. the number of interference measurement points in the deployment area is minimal, i.e. min (pointnum)g) Wherein poitnumgThe number of interference measurement points in the g solution is taken;
2. coverage of interference measurement points in the deployment area is maximal, namely max (coverage area)g) Wherein coverareagFor interference measurement points in the g-th solutionCoverage rate;
3. the sum of the distances between all the interference measurement points and the nearest road in the deployment area is minimum, i.e.
Wherein outputgIs the g-th solution, disiThe distance between the ith interference measurement point in the g solution and the nearest road is calculated;
4. the minimum number of interference measurement points in the deployment area that are far from the road, min (numwaroad)g) Wherein numwayroadgThe number of interference measurement points far away from the road in the g solution is determined;
5. the interference measurement points are arranged more densely in the areas with strong interference than in the areas with weak interference.
Constraint conditions are as follows:
the number of the interference measurement points is more than or equal to the lower limit of the number and less than or equal to the upper limit of the number, namely, Maxnum is less than or equal to pointnumg≤Minnum；
The interference measurement point is located within the deployment area.
Inputting:
boundary information mean { (x) of deployment areaj,yj，zj) J is more than or equal to 1 and less than or equal to w, and comprises the number of inflection points of the boundary and inflection point coordinates, wherein (x)j,yj，zj) Is a coordinate of an inflection point, and w is the number of the inflection points;
grid information grid { (x) of the rasterized deployment regionj′,yj′，zj′,propertyj′,propertyinfoj′,strengthj′) J' is more than or equal to 1 and less than or equal to t), and the grid geographical attribute comprises grid center coordinates, the number of grids, grid geographical attribute after the grid layer and the ground object layer are superposed, information carried by the grid geographical attribute and interference strength identification borne by the grids, wherein (x) isj′,yj′，zj′) Is the jth' grid center coordinate, t is the number of grids, propertyj′For the geographic attribute of the jth grid, propertyinfoj′Strength, the information carried for the jth grid geographical attributej′For the interference intensity of the jth gridDistinguishing a strong interference region from a weak interference region;
an upper limit and a lower limit for the number of interference measurement points.
And (3) outputting:
the deployment schemes comprise the number of interference measurement points and coordinates of the interference measurement points;
wherein, outputgFor the g-th solution, i.e. the g-th deployment scenario,
is poitnumgThe coordinates of the individual interference measurement points.
And 5, acquiring a group of deployment schemes by adopting a multi-objective evolutionary algorithm based on the interference measurement point deployment model.
A Pareto competition method is adopted, candidate individuals are expressed in a vector or binary form, parameters such as population size, population number and evolution algebra are set according to problem scale, and generation-by-generation optimization is performed through genetic operations such as selection, variation and intersection on the premise that constraint conditions specified by a model are met, so that a group of multiple candidate schemes meeting the constraint conditions and conforming to a Pareto non-dominated solution are obtained. The solving flowchart is shown in fig. 3, and specifically as follows:
5.1) coding mode
The size scale of the population is artificially set, and each initial individual in the population is represented as p (m) { (pointnum, x)1,y1，z1,...xpointnum,ypointnum，zpointnum) In which x1,y1，z1,...xpointnum,ypointnum，zpointnumCoordinates of pointnum interference measurement points.
5.2) population initialization
5.2.1) for B2Selecting a plurality of grid points according to a random function;
5.2.2) analyzing the grid point set, and removing obviously wrong or repeated grid points;
5.2.3) carrying out encoding processing of the step 5.1 aiming at the grid points obtained in the step 5.2.2 to obtain new individuals;
5.2.4) repeating the steps 5.2.1-5.2.3 until the previously set population size scale is reached.
5.3) constructing a non-dominated solution set
Constructing a non-dominated solution set by adopting a quick sorting method, wherein the detailed steps are as follows:
5.3.1) select the first individual P (start) of the current sequence as the reference, and set the non-dominated solution set Nondominatedset to null.
5.3.2) dividing the sequence into two sub-sequences with the actual position of the reference in the sequence, such that the individuals to the left of the reference are either dominated by, equal to, or mutually exclusive of the reference, and the elements to the right of the reference are either dominated by, or equal to, the reference.
5.3.3) if the reference is not dominated by all individuals in the current sequence, adding the non-dominating set Nondominatedset.
5.3.4) recursively performs the processing of step 5.3.1 to step 5.3.3 on the right sequence until the sequence is empty or there is only one individual.
5.4) controlling the size of the non-dominated solution set and maintaining its distribution
In the later stage of evolution, the number of non-dominated individuals is increased, and the size of a non-dominated solution set needs to be controlled by adopting a self-adaptive grid method and the distribution of the non-dominated solution set is kept.
5.4.1) determining the number of the optimization targets, the maximum value and the minimum value on each target and the division times of the grid on each dimension, and calculating the grid width on each target to construct the self-adaptive grid.
5.4.2) calculating the position of each target of all non-dominant individuals in the grid on the corresponding dimension and putting the position into the corresponding grid.
5.4.3) selecting the grid containing the most non-dominant individuals, and deleting one non-dominant individual. This step is repeated until the non-dominated solution set size meets the specified size.
5.5) selection, crossover, mutation operations
And carrying out selection, crossing and mutation operations on the obtained solution set according to the characteristics required to be reserved by the parents and the characteristics required to be added by the individuals, carrying out generation-by-generation evolution under the condition of reserving the excellent attributes of the parents, continuously judging whether the evolution conditions are met, and finally obtaining a group of approximately optimal solutions.
The most common multi-objective evolutionary algorithm is adopted, and if the core idea is not changed, such as a coding mode, the design of an evolutionary operator and the like, a multi-objective algorithm framework based on intelligent optimization or a multi-objective algorithm based on cluster intelligence can be applied to the calculation in the step.
And 6, evaluating all the deployment schemes in the group, and selecting a plurality of deployment schemes with the top evaluation sequence as final schemes.
Consider the following angles:
the number of interference measurement points in the deployment area is minimal;
the coverage rate of interference measurement points in a deployment area is maximum;
the sum of the distances between all the interference measurement points and the nearest road in the deployment area is minimum;
the number of all interference measurement points in the deployment area far away from the road is minimum;
the density of interference measurement points deployed in the area with strong interference is greater than that of the area with weak interference;
comprehensively estimating each deployment scheme by adopting a weighted estimation or other estimation modes, and selecting a plurality of deployment schemes with the front estimation sequence as final schemes according to the estimation or scoring of the deployment schemes and the arrangement of each deployment scheme from high to low according to the scoring; the number of final solutions is determined according to actual conditions and requirements.
The interference measurement path planning method specifically comprises the following steps:
after the deployment schemes of the interference measurement points are obtained by adopting the deployment method of the interference measurement points, the interference measurement path schemes are constructed according to the deployment schemes, all the interference measurement path schemes are evaluated finally, and a plurality of interference measurement path schemes which are ranked in the front of the evaluation order are selected as final paths.
The process of constructing the interference measurement path scheme is as follows:
step A, abstracting road network information and interference measurement point information into a graph G.
The process of abstracting graph G is as follows:
A1) projecting the interference measurement points in the deployment scheme into a road network;
A2) and in response to the fact that the distance between the interference measurement point and the nearest road exceeds the maximum measurement range of the interference measurement point, splitting the interference measurement point into a plurality of vertical lines on the surrounding roads, and forming a new interference measurement point with the intersection of the roads so as to ensure that the road with the nearest position of each interference measurement point is in a proper range.
As shown in fig. 4, the interference measurement point O in the graph is a point to be split, and the interference measurement point O is split to 5 surrounding paths according to actual conditions to obtain the split point O1、O2、O3、O4、O5。
A3) The interference measurement point and the drive test starting point are used as vertexes, the connecting line between each vertex is used as an edge, the distance is used as the weight of the edge, and the vertexes and the edges form a graph G which is shown in FIG. 5.
And step B, converting the graph G into an Euler graph according to the number of odd degree nodes in the graph G.
And step C, an Euler loop of the Euler diagram is an interference measurement path scheme.
The number of odd degree nodes of graph G has the following three cases:
1) there are no odd numbered nodes in graph G: graph G is an euler graph, then the euler loop is the only minimum length tour; this path is obtained by:
arbitrarily selecting a vertex V0Let the initial trajectory W0＝V0。
Assumed trajectory Wp＝V0e1V1…epVpHaving determined that E is to be selected from the set of edges Ep+1：
Removing selected trace e from Euler graph G1,…,ep}。
Selection ep+1And VpAssociating;
unless no other edge is selectable, ep+1Not the cut edge c of the remaining euler graph.
Wherein, V0、V1、VpAre all vertices, e1、ep、ep+1Are all edges.
2) There are two odd degree nodes in graph G: then there is a slave Vi1To Vj1Euler trace of from Vj1Back to Vi1Then some edges must be repeated to minimize the total length of the repeated edges, which translates into a requirement from Vi1To Vj1The shortest path of (2). The algorithm is as follows:
finding out the shortest path of two odd-degree node pieces;
and adding the shortest path in the graph G to obtain an Euler graph, wherein the Euler loop is an interference measurement path scheme.
3) There are 2n odd degree nodes in graph G, n being an integer greater than 1:
finding out the shortest paths among all odd degree nodes;
using a 0-1 programming method to obtain the optimal pairing among all odd-degree nodes;
and adding the shortest path of the optimal matching part in the graph G to obtain an Euler graph, wherein an Euler loop is an interference measurement path scheme.
Consider the following angles:
the length of the traversal path is minimum;
the manpower loss is minimum;
the instrument loss is minimum;
comprehensively estimating each interference measurement path by adopting a weighting estimation or other estimation modes, and then selecting a plurality of interference measurement paths with front estimation sequencing as final paths according to the estimation or scoring of each interference measurement path and the ranking from high to low of each interference measurement path; the number of final paths is determined according to actual conditions and requirements.
The method adopts a multi-objective evolutionary algorithm to continuously adjust and optimize the setting of the interference measurement points to obtain a plurality of optimal deployment schemes, abstracts the interference measurement points and the road network in the deployment schemes into a graph G, converts the graph G into an Euler diagram according to the number of odd-degree nodes in the graph G, and realizes convenient selection of the interference measurement points and the planning measurement path by using the Euler loop of the Euler diagram as an interference measurement path scheme.
An interference measurement point deployment system includes,
a deployment model building module: constructing an interference measurement point deployment model of a deployment area;
a deployment scenario acquisition module: based on an interference measurement point deployment model, a multi-objective evolutionary algorithm is adopted to obtain a group of deployment schemes;
a deployment scenario evaluation module: and evaluating all the deployment schemes in the group, and selecting a plurality of deployment schemes with the top evaluation ranking as final schemes.
An interference measurement path planning system, comprising,
the interference measurement point deployment system;
an interference measurement path scheme construction module: constructing an interference measurement path scheme according to the deployment scheme;
an interference measurement path scheme evaluation module: and evaluating all interference measurement path schemes, and selecting a plurality of interference measurement path schemes which are evaluated and ranked in the front as final paths.
A computer readable storage medium storing one or more programs, the one or more programs comprising instructions, which when executed by a computing device, cause the computing device to perform an interference measurement point deployment method and/or an interference measurement path planning method.
A computing device comprising one or more processors, memory, and one or more programs stored in the memory and configured to be executed by the one or more processors, the one or more programs including instructions for performing an interference measurement point deployment method and/or an interference measurement path planning method.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The present invention is not limited to the above embodiments, and any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention are included in the scope of the claims of the present invention which are filed as the application.
Claims (7)
1. The method for deploying the interference measurement points is characterized by comprising the following steps: comprises the steps of (a) preparing a mixture of a plurality of raw materials,
constructing an interference measurement point deployment model of a deployment area,
the process of determining the deployment area is as follows:
determining all interfered points;
as bounding boxes enclosing all disturbed pointsB 1Enclosing boxB 1The enclosed area is an interfered area;
in the bounding boxB 1Searching the nearest undisturbed point in each direction;
as bounding boxes enclosing undisturbed pointsB 2Enclosing boxB 2The enclosed area is a deployment area;
the structure of the deployment model of the interference measurement point is as follows:
optimizing the target:
the number of interference measurement points in the deployment area is minimal;
the coverage rate of interference measurement points in a deployment area is maximum;
the sum of the distances between all the interference measurement points and the nearest road in the deployment area is minimum;
the number of all interference measurement points in the deployment area far away from the road is minimum;
the density of interference measurement points deployed in the area with strong interference is greater than that of the area with weak interference;
constraint conditions are as follows:
the number of the interference measurement points is greater than or equal to the lower number limit and less than or equal to the upper number limit;
the interference measurement point is located in the deployment area;
inputting:
the boundary information of the deployment area comprises the number of boundary inflection points and inflection point coordinates;
grid information of the grid deployment area comprises grid center coordinates, grid quantity, grid geographic attributes after the grid image layers and the ground object image layers are overlapped, information carried by the grid geographic attributes and interference strength marks borne by the grids;
an upper limit and a lower limit of the number of interference measurement points;
and (3) outputting:
a plurality of deployment schemes, wherein the deployment schemes comprise the number of interference measurement points and coordinates of the interference measurement points;
obtaining a group of deployment schemes by adopting a Pareto competition method based on an interference measurement point deployment model;
evaluating all the deployment schemes in the group, and selecting a plurality of deployment schemes with the top-ranked evaluation as final schemes, wherein the evaluation considers the following angles:
the number of interference measurement points in the deployment area is minimal;
the coverage rate of interference measurement points in a deployment area is maximum;
the sum of the distances between all the interference measurement points and the nearest road in the deployment area is minimum;
the number of all interference measurement points in the deployment area far away from the road is minimum;
the interference measurement points are arranged more densely in the areas with strong interference than in the areas with weak interference.
2. The interference measurement path planning method is characterized by comprising the following steps: comprises the steps of (a) preparing a mixture of a plurality of raw materials,
obtaining a plurality of deployment schemes of the interference measurement points by using the interference measurement point deployment method of claim 1;
constructing an interference measurement path scheme according to the deployment scheme;
and evaluating all interference measurement path schemes, and selecting a plurality of interference measurement path schemes which are evaluated and ranked in the front as final paths.
3. The interference measurement path planning method according to claim 2, characterized in that: the process of constructing the interference measurement path scheme is,
abstracting road network information and interference measuring point information into a graph G;
converting the graph G into an Euler graph according to the number of odd degree nodes in the graph G;
the euler loop of the euler diagram is an interference measurement path scheme.
4. The interference measurement path planning method according to claim 3, characterized in that: the process of abstracting the graph G is,
projecting the interference measurement points in the deployment scheme into a road network;
in response to the fact that the distance between the interference measuring point and the nearest road exceeds the maximum measuring range of the interference measuring point, the interference measuring point is split to a plurality of surrounding roads to form a new interference measuring point;
the interference measurement point and the drive test starting point are set as vertices, the distance between each vertex is set as an edge, and the vertices and the edges form a graph G.
5. The interference measurement path planning method according to claim 3, characterized in that: the process of converting the graph G into the euler graph is,
there are no odd numbered nodes in graph G: FIG. G is a Euler diagram;
there are two odd degree nodes in graph G:
finding out the shortest path of two odd-degree node pieces;
adding the shortest path in the graph G to obtain an Euler graph;
presence of 2 in graph GnThe number of the odd-degree nodes is,nis an integer greater than 1:
finding out the shortest paths among all odd degree nodes;
using a 0-1 programming method to obtain the optimal pairing among all odd-degree nodes;
and adding the shortest path of the optimal matching part in the graph G to obtain an Euler graph.
6. Interference measurement point deployment system, its characterized in that: comprises the steps of (a) preparing a mixture of a plurality of raw materials,
a deployment model building module: constructing an interference measurement point deployment model of a deployment area,
the process of determining the deployment area is as follows:
determining all interfered points;
as bounding boxes enclosing all disturbed pointsB 1Enclosing boxB 1The enclosed area is an interfered area;
in the bounding boxB 1Searching the nearest undisturbed point in each direction;
as bounding boxes enclosing undisturbed pointsB 2Enclosing boxB 2The enclosed area is a deployment area;
the structure of the deployment model of the interference measurement point is as follows:
optimizing the target:
the number of interference measurement points in the deployment area is minimal;
the coverage rate of interference measurement points in a deployment area is maximum;
the sum of the distances between all the interference measurement points and the nearest road in the deployment area is minimum;
the number of all interference measurement points in the deployment area far away from the road is minimum;
the density of interference measurement points deployed in the area with strong interference is greater than that of the area with weak interference;
constraint conditions are as follows:
the number of the interference measurement points is greater than or equal to the lower number limit and less than or equal to the upper number limit;
the interference measurement point is located in the deployment area;
inputting:
the boundary information of the deployment area comprises the number of boundary inflection points and inflection point coordinates;
grid information of the grid deployment area comprises grid center coordinates, grid quantity, grid geographic attributes after the grid image layers and the ground object image layers are overlapped, information carried by the grid geographic attributes and interference strength marks borne by the grids;
an upper limit and a lower limit of the number of interference measurement points;
and (3) outputting:
a plurality of deployment schemes, wherein the deployment schemes comprise the number of interference measurement points and coordinates of the interference measurement points;
a deployment scenario acquisition module: based on an interference measurement point deployment model, a multi-objective evolutionary algorithm is adopted to obtain a group of deployment schemes;
a deployment scenario evaluation module: evaluating all the deployment schemes in the group, and selecting a plurality of deployment schemes with the top-ranked evaluation as final schemes, wherein the evaluation considers the following angles:
the number of interference measurement points in the deployment area is minimal;
the coverage rate of interference measurement points in a deployment area is maximum;
the sum of the distances between all the interference measurement points and the nearest road in the deployment area is minimum;
the number of all interference measurement points in the deployment area far away from the road is minimum;
the interference measurement points are arranged more densely in the areas with strong interference than in the areas with weak interference.
7. Interference measurement path planning system, its characterized in that: comprises the steps of (a) preparing a mixture of a plurality of raw materials,
the interference measurement point deployment system of claim 6;
an interference measurement path scheme construction module: constructing an interference measurement path scheme according to the deployment scheme;
an interference measurement path scheme evaluation module: and evaluating all interference measurement path schemes, and selecting a plurality of interference measurement path schemes which are evaluated and ranked in the front as final paths.
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