Rapid equipment deployment method for complex ground feature environment

Abstract

The invention discloses a rapid equipment deployment method for a complex ground object environment. The method comprises the following steps: constructing a three-dimensional space three-dimensional scene model for the complex ground object environment; determining an equipment deployment index system, wherein equipment deployment indexes comprise a detection range, a defense range, a coverage overlapping degree, a coverage gap and cost; determining an equipment system of the detection equipment; based on the three-dimensional scene model of the three-dimensional space, screening a plurality of alternative point locations; determining alternative position points from the plurality of alternative position points; deploying equipment simulation to each preselected position to form a plurality of combination schemes, and calculating an equipment deployment index of each combination scheme; and obtaining an optimal combination from the combination schemes according to the equipment deployment indexes, and optimizing the optimal combination to generate an optimal equipment deployment scheme. According to the technical scheme, the optimization problem of equipment deployment in a complex ground object environment can be effectively solved, and powerful support is provided for equipment position site selection.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of complex three-dimensional space environment defense, in particular to a complex-terrain-environment-oriented equipment rapid deployment method. BACKGROUND

[0002] Defense equipment deployment is an important link in the field of defense technology. When deploying defense equipment, the type, quantity and deployment location of the defense equipment that meets the task requirements need to be determined. The selection of the deployment location needs to consider factors such as terrain, environment, and effect. However, in a complex terrain environment, such as in a building, trees, and sloping land, the coverage area and defense effect of the defense equipment will be affected.

[0003] Currently, there is no scientific and unified site selection and reconnaissance process for countermeasures / defense equipment in complex three-dimensional space environments. The ability to collect and apply actual data on terrain, building undulations, electromagnetic, hydrological, and meteorological environments at service points has not formed a unified evaluation standard and decision-making system. Therefore, it is impossible to determine the best erection point of countermeasures / defense equipment based on data. As a result, decision-makers may rely on their senses and experience when selecting sites for detection and countermeasures equipment, which may result in a mismatch between deployed equipment and defense needs, and the difficulty of effectively utilizing comprehensive effectiveness in decision-making for detection and countermeasures equipment.

[0004] Therefore, there is a need for an equipment deployment technical solution for complex terrain environment three-dimensional space, which can provide a scientific basis for decision-making, reduce the difficulty of manual site selection in complex environments, and improve work efficiency. SUMMARY

[0005] To achieve the above-mentioned purpose, the present application provides a complex-terrain-environment-oriented equipment rapid deployment method, comprising the following steps: Construct a three-dimensional scene model of a complex-terrain-environment-oriented three-dimensional space; Determine an equipment deployment index system, which includes detection range, defense range, coverage overlap, coverage gap, and cost; Determine an equipment system of detection, soft disposal, and hard disposal equipment; Based on the three-dimensional scene model of the three-dimensional space, screen a plurality of candidate points; and determine a candidate array site from the plurality of candidate points; Deploy the equipment to each preselected array site to form a plurality of combined schemes, and calculate the equipment deployment index of each combined scheme; According to the equipment deployment index, obtain the optimal combination from the combined schemes, optimize the optimal combination, and generate an optimal equipment deployment scheme.

[0006] The constructing the three-dimensional scene model of the stereoscopic space comprises image data processing, elevation data processing and three-dimensional scene modeling. The image data processing comprises pre-processing of image data files, splicing two or more digital images of the same position obtained under different conditions to form an overall image, planning to a unified coordinate system, and cutting off the overlapping part; cutting the image data to obtain the image data after cutting; and using a unified coordinate system and projection to ensure system data sharing and normal operation of the system. The elevation data processing comprises verifying digital elevation model data, cutting the digital elevation model data that meets the needs of three-dimensional space modeling in complex terrain environment, and obtaining elevation data that meets the range. The three-dimensional scene modeling comprises collecting model style, structure, texture information and model attributes, making the model, forming a simulation effect, and superimposing data of satellite remote sensing image and elevation data to show the three-dimensional effect of the topography.

[0007] Further, when screening multiple candidate points, the slope direction data is extracted from the grid digital elevation model, the slope direction matrix is formed by the slope direction data, and the following steps are sequentially judged: Extracting the point to be judged; Taking the point to be judged as the center, the slope direction values of all grids around the point to be judged are obtained through a set analysis window; the slope direction values of adjacent grids are compared in a clockwise direction one by one, and the number of grids whose slope direction values of the previous grid are less than those of the next grid is recorded; If the number of grids meeting the condition is m, the size of the analysis window is n, and then it is considered that the point to be judged is a potential mountain top point under ideal conditions; Repeat the above process until all points to be judged are processed; According to the order from high to low of the slope direction values, multiple candidate points meeting the basic conditions are screened out.

[0008] Deploying the simulation equipment to each preselected position to form multiple combination schemes comprises: Interpolation calculation based on the visibility analysis algorithm of the grid digital elevation model; Auxiliary visibility analysis through the visibility domain, statistics and labeling of the grid whose value in the visibility grid matrix is 1, and obtaining the visibility domain of the study area; Calculating the equipment deployment index of each deployment site.

[0009] Further, the elevation of the point on the line of sight is interpolated with a fixed step size, and the step size calculation method is: △ x = x B -x A, △ y = yB -y A, △ = max (△ x, △ y ), s = int (△ / m ), In the formula, m is the grid spacing. x A and x B , y A and y B These are the coordinates of the four vertices of the grid, △ x and △ y These represent the coordinate differences, △ represents the maximum value of △x and △y, and int is the integer function.

[0010] Furthermore, obtaining the optimal combination from the combination schemes includes: With the goal of maximizing the deployment effectiveness of detection equipment, the optimal deployment location for each detection equipment is obtained; The location corresponding to the deployment scheme that maximizes the objective function of the detection equipment is embedded in the application scenario. Then, the deployment of soft and hard processing equipment is optimized, with the optimization objectives being to maximize the deployment efficiency of soft and hard processing equipment, to obtain the optimal deployment location for each piece of soft and hard processing equipment. Based on the equipment deployment location, perform single-objective optimization to determine the optimal combination.

[0011] Among them, the optimization goal of maximizing the deployment effectiveness of detection equipment includes: Construct an optimization objective function to maximize the deployment efficiency of detection equipment, including: definition It is an optimization variable. Let the objective function be the optimization problem, which is expressed as: in Indicates the equipment deployment range. Indicates the first Equipment deployment efficiency in various scenarios represent The first type of equipment Equipment deployment location, This includes deployment location and geographic information; By solving the problem, at least one deployment scheme that maximizes the objective function can be obtained.

[0012] Maximizing soft handling equipment deployment efficiency and maximizing hard handling equipment deployment efficiency as optimization objectives are expressed as: In the formula, respectively represent the detection equipment, soft handling equipment, hard handling equipment deployment efficiency, respectively represent the detection, soft handling, hard handling equipment deployment position.

[0013] Further, single-target optimization includes optimization of the airspace detection capability f and optimization of the detection probability: The optimization of the airspace detection capability f is expressed as: , wherein, To obtain the alert area, is the detection area of the i-th equipment, and λ is the importance degree of the red target in the key detection area. C=A (P≥P0 or K≥K0) is the obtained key detection area; The optimization of the detection probability is expressed as: wherein, is the detection probability of the i-th equipment, and it is assumed that each equipment is statistically independent; and N is the number of equipment.

[0014] Further, the optimization of the optimal combination means that after determining the area equipment type and deployment position, the blind area binary graph is obtained by inputting the detection equipment coverage data and using the threshold method / assignment method, the single-point blind area grid points and fragmented blind areas are removed, the optimal detection equipment and deployment position are matched, and the deployment scheme is perfected.

[0015] According to the present application, the complex terrain environment is digitized and modeled to realize rapid site selection calculation, and the problem that it is difficult to quickly give reasonable detection, soft handling and hard handling equipment deployment position under the complex terrain environment is effectively solved, so that various types of equipment cannot play the expected efficiency. The present application provides strong support for equipment site selection. BRIEF DESCRIPTION OF DRAWINGS

[0016] Figure 1 is a rapid equipment deployment method step diagram for a complex terrain environment according to an embodiment of the present application; Figure 2 is a process step diagram for generating an optimal equipment deployment scheme according to an embodiment of the present application; Figure 3 is a process schematic diagram for constructing a three-dimensional scene model of a solid space according to an embodiment of the present application. DETAILED DESCRIPTION

[0017] The application provides a complex-terrain-environment-oriented equipment rapid deployment method, which is based on terrain data, vector map data and complex three-dimensional space building data, realizes model construction for a three-dimensional scene of a complex three-dimensional space for defense, selects a preselected position by using terrain analysis technology, fully considers the defense requirements and the spatial features of a defense area in the selection process, proposes reasonable deployment positions of detection, soft disposal and hard disposal equipment, generates multiple combination schemes, establishes a screening basis for the combination schemes in combination with an index system, and finally forms an optimal equipment deployment scheme.

[0018] The specific implementation of the application will be described in detail below with reference to the accompanying drawings.

[0019] The complex-terrain-environment-oriented equipment rapid deployment method provided by the application, as shown in Figure 1 , includes the following steps. Step S100: constructing a three-dimensional space three-dimensional scene model for a complex-terrain-environment; In this step, terrain data and building information are extracted based on aerospace remote sensing data, and a complex three-dimensional space scene is constructed together; in the implementation process, modeling is performed according to terrain data, vector map data and complex three-dimensional space building data, and the required image data, elevation data and complex three-dimensional space building data are corrected, processed, inlaid, cropped, coordinate-converted, projection-converted and format-converted, three-dimensional space three-dimensional scene modeling is constructed for a complex-terrain-environment, and fixed-format data is supported to be exported for display in a three-dimensional scene display system. The specific implementation process is shown in Figure 3 , which includes three parts of image data processing, elevation data processing and three-dimensional scene modeling. 1) image data processing; First, the image data file is preprocessed: including using atmospheric correction, geometric correction, image contrast enhancement and other methods to verify the position, range, color, resolution, uniformity and other indicators of the image data, and supporting export of image data of different resolutions; then, by using the image inlay method, two or more digital images of associated positions obtained under different conditions are spliced to form an overall image, which is planned to a unified coordinate system and cropped to remove the overlapping part; the image data is cut according to different conditions such as administrative division, specified image range size and map coordinate range, to obtain the image data after cutting; a unified coordinate system and projection are used to ensure system data sharing and normal system operation. The satellite remote sensing image data and elevation data use a unified coordinate system and projection method; the image data, especially the image data of key areas, is processed to eliminate cloud and fog and eliminate noise, effectively improving the image quality.

[0020] 2) elevation data processing; It refers to the processing procedure of digital elevation model data preprocessing, data cutting, coordinate conversion, projection conversion, format conversion and the like.

[0021] 3) three-dimensional scene modeling; It comprises collecting model style, structure and the like information to be made, and existing texture information and model attribute, using 3DMAX software to make the model, sticking the photo image to the surface of the three-dimensional object to enhance the sense of reality, using light calculation, image mixing and the like technology to form the simulation effect, optimizing the model according to the application and performance requirements, and after the processed satellite remote sensing image and elevation data are superimposed and fused, the three-dimensional effect of the topography and geomorphology can be presented.

[0022] Step S110: determining equipment deployment index system; The equipment deployment index comprises factors such as detection range, defense range, coverage overlap degree, coverage gap and cost, and each index value can be acquired through the three-dimensional scene model.

[0023] Step S120: determining equipment system of detection equipment; The detection equipment involved in the application is a defense equipment, and the main performance parameters and attributes of each equipment are managed through the equipment system; in the application, one equipment system is composed of N pieces of possibly different equipment, and the equipment types usually comprise detection, soft disposal and hard disposal equipment.

[0024] Step S130: screening a plurality of alternative points based on the three-dimensional scene model of the stereoscopic space; and determining an alternative array site from the plurality of alternative points. 1) a small amount of alternative points meeting the basic conditions or being relatively reasonable are preliminarily screened out: In the specific implementation, the potential mountain top point is accurately extracted by using the slope direction distribution characteristics: firstly, the slope direction data is extracted from the grid digital elevation model, the slope direction data is used to form a slope direction matrix and is sequentially judged, and the process comprises: extracting a point to be judged; all the slope direction values of the grid around the point to be judged are acquired through a set analysis window with the point to be judged as the center; the slope direction values of the adjacent grids are compared in the clockwise direction one by one, and the number of grids with the slope direction value of the previous grid smaller than that of the next grid is recorded; if m>n, the point to be judged is a potential mountain top point; if m<=n, the point to be judged is not a potential mountain top point. If the slope direction of the point is consistent with the slope direction of the point, the point is considered to be a potential mountain peak point under ideal conditions; wherein, the greater the m is, the more stringent the slope direction constraint condition of the point to be judged is, and the more uniform the slope direction distribution of the grid around the point is; the smaller the m is, the looser the slope direction constraint condition of the point to be judged is, and the more discrete the slope direction distribution of the grid around the point is. The above process is repeated until all points to be judged are processed. After extracting the potential mountain peak points in the digital elevation model region, the potential mountain peak points are sorted and indexed according to the slope direction value from high to low, and the first K potential mountain peak points are stored as a preliminary candidate set, and a plurality of candidate points meeting the basic conditions are preliminarily screened out. The basic conditions can be determined according to actual conditions, for example, a slope direction value threshold, or the number of candidate points.

[0025] 2) In combination with artificial judgment and constraint conditions, a small number of optimal candidate points are selected from the plurality of candidate points; at the same time, in combination with the properties of the detection equipment, the highest point (mountain head, high building top) of the local terrain where the candidate point is located is selected as a to-be-deployed position, and each to-be-deployed position can generate a combination scheme, such as Figure 2 As shown in S210 in the middle, each combination scheme includes detection, soft disposal, and hard disposal equipment.

[0026] Step S140: Simulate deployment of detection equipment to each preselected position to form a plurality of combination schemes, and calculate equipment deployment indexes of each combination scheme; First, interpolation calculation is performed based on the visibility analysis algorithm of the grid digital elevation model: specifically, the elevation of the point on the line of sight is interpolated at a fixed step, and the step calculation method is: △ x = x B -x A, △ y = y B -y A, △ = max (△ x, △ y ), s = int (△ / m ), In the formula, m is the grid spacing, x A and x B , y A and y B are the coordinates of the four vertices of the grid, respectively, △ x and △ y are the coordinate differences, △ is the maximum value of △x and △y, int is the integer function, and the elevation interpolation is performed by using the four vertices of the grid unit.

[0027] Next, a visibility-assisted viewpoint analysis is performed: the analysis process is represented in discrete form, dividing the visibility into visible and invisible grid cells. When the target point is visible, the value of the corresponding grid cell in the auxiliary grid matrix is ​​the elevation value of the target point, and the value of the corresponding grid cell in the visible grid matrix is ​​1. When the target point is invisible, the value of the corresponding grid cell in the auxiliary grid matrix is ​​the minimum elevation value that makes the target point visible, which can be obtained by interpolation. The value of the corresponding grid cell in the visible grid matrix is ​​set to 0. After traversing the grid points within the visible range, the grid cells with a visible grid matrix value of 1 are counted and labeled to obtain the visibility of the study area.

[0028] Furthermore, a reference surface method is used to determine whether the observation point is visible to all target points: after line-of-sight analysis, a numerical grid with line-of-sight attributes is formed. Based on this numerical grid, the equipment deployment indicators for each deployment site are calculated. The equipment deployment indicators include factors such as detection range, defense range, coverage overlap, coverage gaps, and cost (e.g., Figure 2 (See step S220).

[0029] Step S150: Obtain the optimal combination from the combination schemes based on the equipment deployment indicators, optimize the optimal combination, and generate the optimal equipment deployment scheme.

[0030] In this step, as Figure 2 As shown in S230, the equipment deployment indicators of each combination scheme are substituted into the multi-type multi-objective deployment model, and the optimal solution of each combination scheme is calculated according to the objective function and then sorted. 1) With the goal of maximizing the deployment effectiveness of detection equipment, obtain the optimal deployment location for each type of detection equipment; Specifically, an objective function for maximizing the deployment efficiency of detection equipment is constructed, and a hierarchical optimization approach is used to solve the multi-objective problem.

[0031] Includes: Definition It is an optimization variable. Let the objective function be the optimization problem, which is expressed as: in Indicates the equipment deployment range. Indicates the first Equipment deployment efficiency in various scenarios represent The first type of equipment Equipment deployment location, This includes deployment location and geographic information. Let the deployment radius of the j-th device be in polar coordinates. is the deployment angle of the jth equipment in polar coordinates, is the equipment deployment point.

[0032] By solving, at least one deployment scheme is found to maximize the objective function and satisfy the following constraint conditions: wherein, is the maximum radius that can be deployed.

[0033] 2) The position corresponding to the deployment scheme of the detection equipment that maximizes the objective function is embedded in the application scenario, and the soft treatment equipment and the hard treatment equipment are optimized and deployed to maximize the soft treatment equipment deployment efficiency and the hard treatment equipment deployment efficiency as the optimization target, to obtain the best deployment position of each soft treatment equipment: According to the problem solving idea of hierarchical optimization, combined with the modeling of each equipment deployment optimization problem, the system deployment optimization problem is expressed as: In the formula, represent the detection equipment, soft treatment equipment, and hard treatment equipment deployment efficiency, respectively, represent the detection, soft treatment, and hard treatment equipment deployment position, respectively.

[0034] 3) Combined with the equipment deployment position, single-target optimization is performed to determine the optimal combination: In actual application, according to the importance of equipment, the equipment deployment position is divided into alert area and key area: the alert area refers to the area that can be covered by the detection area of at least one equipment, represented by Ag; the key area is represented by Ac, and the equipment overlap coefficient K≥K0 (K0>1) in the area is required, or the probability P≥P0 that the enemy target in the area is detected by the equipment, and: Ag⊃Ac. Since an equipment system is composed of N equipment that may not be the same, a deployment scheme needs to be found to obtain the maximum alert area G and key area C.

[0035] In this step, the optimal deployment part obtained is converted into a single-target optimization problem by weighting, including the optimization of airspace detection capability f and the optimization of detection probability: The geographical position of each equipment is appropriately deployed to obtain the maximum airspace detection capability f, and the mathematical model is: , wherein, is the obtained alert area, is the detection area of the ith equipment, and λ is the importance degree of the red target in the key detection area. C=A (P≥P0 or K≥K0) is the obtained key detection area; The optimization of detection probability is expressed as: wherein: Pi is the detection probability of the ith equipment, where it is assumed that each equipment is statistically independent; and N is the number of equipment.

[0036] The above model is substituted into the deployment position and equipment deployment index of the combined scheme, so that the ranking of the optimization function of the combined scheme in the region is obtained, and the optimal combination is determined according to the ranking result.

[0037] 4) Blind area elimination and equipment blind area compensation are performed on the optimal combination to perfect the optimized deployment scheme; further, after the type and deployment position of the regional equipment are determined, blind area binary graph is obtained by inputting detection equipment coverage data and using threshold method / assignment method, single-point blind area grid points and fragmented blind areas are eliminated, the optimal detection equipment and deployment position are matched, and the deployment scheme is perfected.

[0038] According to the present application, the complex terrain environment is digitized and modeled to realize rapid site selection calculation, and the problem that it is difficult to quickly give reasonable detection, soft treatment and hard treatment equipment deployment positions under the complex terrain environment is effectively solved, so that the problem that various types of equipment cannot play the expected efficiency is solved, and strong support is provided for equipment site selection.

[0039] The above only discloses several specific embodiments of the present application, but the present application is not limited thereto, and any changes that can be thought of by those skilled in the art shall fall within the protection scope of the present application.

Claims

1. A method for rapid deployment of equipment in a complex terrain environment, characterized by, The method comprises the following steps: constructing a three-dimensional scene model of a complex-terrain environment; determining an equipment deployment index system, wherein the equipment deployment index comprises a detection range, a defense range, an overlap degree, a coverage gap, and a cost; determining an equipment system of detection, soft disposal, and hard disposal equipment; based on the three-dimensional scene model, screening a plurality of candidate points; and determining a candidate array site from the plurality of candidate points; deploying equipment simulation to each preselected site to form a plurality of combined schemes, and calculating the equipment deployment index of each combined scheme; obtaining an optimal combination from the combined schemes according to the equipment deployment index, optimizing the optimal combination, and generating an optimal equipment deployment scheme.

2. The method of rapid deployment of equipment according to claim 1, characterized in that, The construction of the three-dimensional scene model comprises image data processing, elevation data processing, and three-dimensional scene modeling; the image data processing comprises preprocessing image data files, splicing two or more digital images of the same position obtained under different conditions to form an overall image, planning to a unified coordinate system, and cutting off the overlapping part; cutting the image data to obtain the image data after cutting; and using a unified coordinate system and projection to ensure system data sharing and normal operation of the system; the elevation data processing comprises verifying digital elevation model data, cutting the digital elevation model data that meets the requirements of three-dimensional modeling of a complex-terrain environment, and obtaining elevation data that meets the range; the three-dimensional scene modeling comprises collecting model styles, structures, texture information, and model attributes, making models, forming simulation effects, and superimposing satellite remote sensing images and elevation data to display the three-dimensional effect of the terrain.

3. The method of rapid deployment of equipment according to claim 1, characterized in that, When the plurality of candidate points are screened, the slope direction data is extracted from the grid digital elevation model, the slope direction data is used to form a slope direction matrix, and the slope direction matrix is sequentially judged, including the following steps: extracting a point to be judged; obtaining the slope direction values of all grids around the point to be judged through a set analysis window with the point to be judged as the center; comparing the slope direction values of adjacent grids in a clockwise direction one by one, and recording the number of grids whose slope direction values of the previous grid are less than those of the next grid; Let the number of grids satisfying the condition be m, the analysis window size be n, and if then it is considered that the to-be-judged point is a potential mountain peak point under ideal conditions. repeating the above process until all the points to be judged are processed; sorting the slope direction values from high to low, and screening a plurality of candidate points that meet the basic conditions.

4. The method of rapid deployment of equipment according to claim 1, characterized in that, The deployment of the detection equipment simulation to each preselected site to form a plurality of combined schemes comprises: interpolation calculation based on the visibility analysis algorithm of the grid digital elevation model; statistical and annotation of the grid whose value in the visible grid matrix is 1 through the visual field auxiliary visibility analysis to obtain the visual field of the study area; calculating the equipment deployment index of each to-be-deployed site.

5. The method of rapid deployment of equipment according to claim 4, characterized in that, The interpolation calculation interpolates the elevation of the point on the line of sight at a fixed step, and the step calculation method is as follows: △ x=x B -x A ，△ y=y B -y A ， △ =max (△ x, △ y )， s =int (△ / m )， where m is the grid spacing, x A and x B , y A and y B are the coordinates of the four vertices of the grid, respectively, Δ x and Δ y are the coordinate differences, respectively, and Δ is the maximum of Δx and Δy, and int is the integer function.

6. The method of rapid deployment of equipment according to claim 1, characterized in that, The optimal combination is obtained from the combined schemes, including: maximizing the detection equipment deployment efficiency as the optimization target to obtain the best deployment position of each detection equipment; The deployment scheme corresponding to the position of the detection equipment maximizing the objective function is embedded in the application scenario, and the soft treatment equipment and the hard treatment equipment are optimized and deployed to maximize the deployment efficiency of the soft treatment equipment and the deployment efficiency of the hard treatment equipment as the optimization target, so as to obtain the optimal deployment position of each soft treatment equipment and hard treatment equipment: Combined with the equipment deployment position, single-target optimization is performed to determine the optimal combination.

7. The method of rapid deployment of equipment according to claim 6, characterized in that, The optimization target of maximizing the deployment efficiency of the detection equipment includes: The optimization target function of maximizing the deployment efficiency of the detection equipment is constructed, including: Definitions is the optimization variable, is the objective function, the optimization problem is formulated as: wherein represents the equipment deployment range, represents the equipment deployment efficiency in the th scenario, represents the type of the equipment, the position of the equipment deployment, , including the deployment position and geographical information; At least one deployment scheme maximizing the objective function is obtained by solving.

8. The method of rapid deployment of equipment according to claim 6, characterized in that, The optimization target of maximizing the deployment efficiency of the soft treatment equipment and the deployment efficiency of the hard treatment equipment is represented as: wherein respectively represent the deployment effectiveness of the detection equipment, the soft handling equipment, and the hard handling equipment, respectively represent the deployment location of the detection equipment, the soft handling equipment, and the hard handling equipment.

9. The method of rapid deployment of equipment according to claim 6, characterized in that, The single-target optimization includes optimization of the space detection capability f and optimization of the detection probability: The optimization of the airspace exploration capability f is expressed as: , wherein, is the obtained alert area, is the ith equipped detection area, and λ is the importance degree of the red target in the key detection area. C = A (P ≥ P0 or K ≥ K0) is the obtained key detection area; The optimization of the detection probability is expressed as: where: is the detection probability of the ith equipment, where it is assumed that each equipment is statistically independent; and N is the number of equipment.

10. The method of rapid deployment of equipment according to claim 6, wherein, The optimization of the optimal combination refers to, after determining the regional equipment type and the deployment position, inputting the detection equipment coverage data, obtaining a blind area binary graph by using a threshold method / assignment method, eliminating single-point blind area grid points and fragmented blind areas, matching the optimal detection equipment and the deployment position, and perfecting the deployment scheme.

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