An air-ground cooperative detection networking deployment optimization method

Abstract

The application discloses an air-ground cooperative detection networking deployment optimization method, which comprises the following steps: firstly, a mathematical model of ground radar detection sensor networking deployment is established; secondly, a detection area is subjected to gridding treatment, and genetic algorithm is used to optimize the deployment of the ground radar detection sensor networking to obtain a Pareto solution; thirdly, the weak index of each grid of the detection area is calculated to obtain a weak matrix; then, the weak matrix is processed by using the breadth-first search thought to extract and sort weak areas; finally, air-based radar deployment tasks are formulated according to the weak areas, and an air-ground cooperative detection networking deployment scheme is finally generated. The application can make up for the poor detection performance of ground radar networking on low-altitude targets such as unmanned aerial vehicles and the insufficient scheduling mobility, improve the air-frequency domain coverage capability of the ground radar networking and the anti-electromagnetic interference and anti-stealth capability, and make the patrol route designation of the air-based radar detection sensor key task more professional and rigorous.

Description

Technical Field

[0001] This invention belongs to the field of radar sensor network detection technology, and in particular relates to an optimized method for air-ground cooperative detection network deployment. Background Technology

[0002] Networked radars, through the deployment of various radar locations, can form an all-round, all-weather, three-dimensional, and hierarchical detection system, possessing superior detection capabilities and anti-electromagnetic interference capabilities compared to traditional radars. Airborne radars have excellent low-altitude detection capabilities and scheduling mobility, exhibiting superior performance in detecting low-altitude, small, and slow-moving targets such as UAVs.

[0003] The effectiveness of radar network deployment depends on the spatial and frequency distribution of the networked radars. Optimized deployment is the prerequisite and foundation for significantly enhancing the efficiency of radar network detection missions. Current research on optimized deployment of ground-based radar networks mainly focuses on deployment under conditions of global uncertainty, employing methods such as enumeration, expert reasoning, and heuristic algorithms. Research on airborne radar deployment primarily focuses on patrol route planning, with commonly used patrol routes including runway-shaped, figure-eight-shaped, and circular routes.

[0004] Due to drawbacks such as combinatorial explosion and slow execution speed, enumeration and expert reasoning methods are almost impossible to obtain an optimal deployment scheme when the number of networked radars is large. Therefore, heuristic algorithms are mostly used in current practice. Patent (A Radar Network Optimization Deployment Method Based on Artificial Bee Colony Algorithm, Application No.: CN202010561560.X, Application Date: 2020-06-18) discloses a radar network optimization deployment method based on the artificial bee colony algorithm. This method constructs a more systematic radar deployment optimization objective function and uses the artificial bee colony algorithm to improve the convergence and convergence speed of iterative optimization. However, this method does not fully consider the requirements for electromagnetic interference resistance and anti-stealth in actual detection missions. The paper (Dai Yu, Wang Xianchao, Tang Ziyue, Zhang Yuanpeng. Airborne Early Warning Aircraft Route Planning for Key Mission Route Support [J]. Firepower and Command Control, 2018, 43(04):62-65+70.) proposes a segmented detection airborne early warning aircraft route planning method. This method adopts a runway-shaped patrol route and uses the particle swarm optimization algorithm to solve the optimal airborne early warning aircraft route planning for key mission support. However, the patrol route for key missions in this method needs to be manually specified, which is arbitrary. Summary of the Invention

[0005] The purpose of this invention is to compensate for the shortcomings of ground-based radar networks in low-altitude detection and dispatch mobility, solve the problems of low air-frequency domain coverage, electromagnetic interference resistance, and anti-stealth capability of ground-based radar networks, and overcome the defect of arbitrary designation of patrol routes for key missions of airborne radar.

[0006] To achieve the objective of this invention, a method for optimizing the deployment of air-ground cooperative detection networks is disclosed, characterized by the following steps:

[0007] Step 1: Determine the evaluation system for ground radar network deployment, and establish a mathematical model for ground radar network deployment based on the performance requirements and constraints of the evaluation system.

[0008] Step 2: The detection area is rasterized, and the ground radar network is optimized and deployed using a genetic algorithm to obtain the Pareto solution for the ground radar network deployment.

[0009] Step 3: Based on the Pareto solution of the ground radar network deployment, calculate the weakness index of each grid in the detection area, and then obtain the weakness matrix of the entire detection area.

[0010] Step 4: Use breadth-first search to process the weak matrix, extract the weak regions, and sort them according to region size and degree of weakness;

[0011] Step 5: Based on the number of air-based radars and the ranking of weak areas, formulate air-based radar deployment tasks, find the longest diagonal of the weak area, form the patrol route of the air-based radar, and finally generate an air-ground collaborative detection network deployment plan.

[0012] Furthermore, the performance requirements of the evaluation system are airspace coverage coefficient, airspace overlap coverage coefficient, and frequency interference coefficient.

[0013] The airspace coverage coefficient characterizes the effective coverage capability of a ground-based radar over the airspace of the detection area and key detection areas. The airspace coverage coefficient α is expressed by the following formula:

[0014]

[0015] In the formula, n represents the number of ground-based networked radars; S i Let S be the detection range of the i-th ground radar, and S be the size of the detection area. key The size of the key detection area; the value range of α is [0,1].

[0016] The airspace overlap coverage coefficient characterizes the overlap coverage rate of two adjacent radars in the detection area. Improving the double coverage range of a radar network is an effective means to enhance the radar network's anti-electromagnetic interference capability. The airspace overlap coverage coefficient β is as follows:

[0017]

[0018] In the formula, the value of β ranges from [0,1].

[0019] The frequency interference coefficient characterizes the degree of interference between two adjacent radars in the frequency domain. Radars in close frequency bands will interfere with each other. The frequency interference coefficient γ is as follows:

[0020]

[0021] In the formula, f i and f j γ represents the operating frequency bands of the i-th and j-th radars, respectively; the value range of γ is [0,1].

[0022] The constraint in the mathematical model is the overlap coefficient, which characterizes the tightness of the overlap between adjacent radars. Its value needs to be limited within a certain range to ensure the rational utilization of radar resources. The overlap coefficient δ is shown in the following formula:

[0023] δ=S cHR / S rHR

[0024] In the formula, S cHR The overlapping detection range of two adjacent radars; S rHR The smaller radar detection range is δ; the value range of δ is [0,1].

[0025] Based on performance requirements and constraints, the mathematical model for the deployment of ground-based radar networks can be established as follows:

[0026]

[0027] In the formula, w i The weighting coefficients for different altitude layers can be set according to the air situation volume and mission importance at different altitude layers; k1, k2, and k3 are the weighting coefficients for each performance indicator, which can be set according to mission requirements.

[0028] Furthermore, the detection area is rasterized. Using the criterion of whether the center of each grid falls within the radar detection range, the calculation of the polygon area generated by the intersection and union of radar ranges can be transformed into the calculation of the intersection and union of grid center points. This aims to reduce computational load while maintaining accuracy. Then, parameters such as radar information, detection area size, and key detection area size are input into a genetic algorithm, and through iteration, the Pareto solution for the ground radar network deployment is obtained.

[0029] Furthermore, the weakness index W is an index specifically designed and proposed by this invention for optimizing the deployment of air-to-ground cooperative detection networks. Its purpose is to identify deficiencies in the deployment of ground-based radar networks targeting low, small, and slow targets (including UAVs) to guide the deployment planning of air-based radars. The weakness index W for each grid cell in the detection area is calculated using the Pareto solution obtained in step 2. The weakness index W is derived from the airspace weakness index W0. ky and frequency domain weakness index W py composition.

[0030] Furthermore, the weakness index W is as follows:

[0031] W = W ky +W py

[0032] Airspace Weakness Index W ky W is determined by the coverage multiplicity of the current raster. ky The value range is [0,1], as shown in the table below:

[0033] Coverage multiplicity No coverage First layer of coverage Double coverage Triple or higher coverage Airspace Weakness Index 0 0.7 0.9 1

[0034] Frequency domain weakness index W py Frequency band electromagnetic interference resistance F kgr and frequency band anti-stealth capability F fys The composition is as follows:

[0035] W py =F kgr +F fys

[0036] Frequency band electromagnetic interference resistance F kgr As shown in the following formula:

[0037]

[0038] In the formula, To form the union of the operating frequency bands of k radars covering the current grid, To enable the deployment of a union of all operating frequency bands for ground-based radars, F kgr The value range is [0,1];

[0039] Frequency band anti-stealth capability F fys As shown in the following formula:

[0040]

[0041] In the formula, To score the anti-stealth capability of k radars operating in the current grid, F fys The value range is [0,1].

[0042] The scores for a single radar's anti-stealth capability are shown in the table below:

[0043] Operating frequency band HF VHF UHF L S C X other Score 1 1 0.8 0.5 0.5 0.5 0.5 0.6

[0044] After calculating the weakness index W of all grids, the weakness matrix of the entire detection area is obtained.

[0045] Furthermore, a threshold W is set according to the requirements of the detection mission. min If for weak matrix any element W i Satisfy W i <W min Then W i These are called weak points; the breadth-first search is used to find each weak point in the weak matrix, and adjacent weak points are merged into a weak region.

[0046] Furthermore, each weak area is sorted in descending order. The first criterion for sorting is the size of the area, i.e., the number of weak points, and the second criterion is the degree of weakness, i.e., the average weakness index of each weak point.

[0047] Furthermore, based on the number of air-based radars and the ranking of vulnerable areas, and adhering to the principle that one air-based radar protects one vulnerable area, the patrol routes of the air-based radars are selected in runway shape, and the deployment tasks of the air-based radars are formulated.

[0048] Furthermore, the weak areas are mapped back to the detection area grid, and the longest diagonal of the weak area grid is found to form the patrol route of the air-based radar, ultimately generating an air-ground collaborative detection network deployment scheme.

[0049] Compared with the prior art, the significant advancements of this invention are: 1) This invention utilizes the high-altitude detection advantages of airborne radar, combining ground radar networking with airborne radar to compensate for the shortcomings of ground radar in low-altitude detection and dispatch mobility, and improves the air-frequency domain coverage capability, anti-electromagnetic interference, and anti-stealth capability of ground radar networking; 2) This invention performs a vulnerability assessment on the ground radar networking sites obtained after using heuristic algorithms, extracts key information such as vulnerable areas to plan the patrol routes of airborne radar, making the designation of patrol routes for key tasks of airborne radar more professional and rigorous.

[0050] To more clearly illustrate the functional characteristics and structural parameters of the present invention, further explanation is provided below in conjunction with the accompanying drawings and specific embodiments. Attached Figure Description

[0051] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this application, illustrate exemplary embodiments of the invention and, together with their description, serve to explain the invention and do not constitute an undue limitation thereof. In the drawings:

[0052] Figure 1 This is a framework diagram of an optimized deployment method for air-ground collaborative detection networks. Detailed Implementation

[0053] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0054] like Figure 1 As shown, an optimized deployment method for air-to-ground collaborative detection networks includes the following steps:

[0055] 1) Determine the evaluation system for ground radar network deployment, and establish a mathematical model for ground radar network deployment based on the performance requirements and constraints of the evaluation system;

[0056] 2) The detection area is rasterized, and the ground radar network is optimized using a genetic algorithm to obtain the Pareto solution for the ground radar network deployment;

[0057] 3) Based on the Pareto solution of the ground radar network deployment, calculate the weakness index of each grid in the detection area, and then obtain the weakness matrix of the entire detection area.

[0058] 4) Use breadth-first search to process the weak matrix, extract the weak regions, and sort them according to region size and degree of weakness;

[0059] 5) Based on the number of air-based radars and the ranking of weak areas, formulate air-based radar deployment tasks, find the longest diagonal of the weak area, form the patrol route of the air-based radar, and finally generate an air-ground collaborative detection network deployment plan.

[0060] In step 1, the performance requirements of the evaluation system are spatial coverage coefficient, spatial overlap coverage coefficient, and frequency interference coefficient.

[0061] The airspace coverage coefficient characterizes the effective coverage capability of a ground-based radar over the airspace of the detection area and key detection areas. The airspace coverage coefficient α is expressed by the following formula:

[0062]

[0063] In the formula, n represents the number of ground-based networked radars; S i Let S be the detection range of the i-th ground radar, and S be the size of the detection area. key The size of the key detection area; the value range of α is [0,1].

[0064] The airspace overlap coverage coefficient characterizes the overlap coverage rate of two adjacent radars in the detection area. Improving the double coverage range of a radar network is an effective means to enhance the radar network's anti-electromagnetic interference capability. The airspace overlap coverage coefficient β is as follows:

[0065]

[0066] In the formula, the value of β ranges from [0,1].

[0067] The frequency interference coefficient characterizes the degree of interference between two adjacent radars in the frequency domain. Radars in close frequency bands will interfere with each other. The frequency interference coefficient γ is as follows:

[0068]

[0069] In the formula, f i and f j γ represents the operating frequency bands of the i-th and j-th radars, respectively; the value range of γ is [0,1].

[0070] The constraint in the mathematical model is the overlap coefficient, which characterizes the tightness of the overlap between adjacent radars. Its value needs to be limited within a certain range to ensure the rational utilization of radar resources. The overlap coefficient δ is shown in the following formula:

[0071] δ=S cHR / δ rHR

[0072] In the formula, S cHR The overlapping detection range of two adjacent radars; S rHR The smaller radar detection range is δ; the value range of δ is [0,1].

[0073] Based on performance requirements and constraints, the mathematical model for the deployment of ground-based radar networks can be established as follows:

[0074]

[0075] In the formula, w i The weighting coefficients for different altitude layers can be set according to the air situation volume and mission importance at different altitude layers; k1, k2, and k3 are the weighting coefficients for each performance indicator, which can be set according to mission requirements.

[0076] Step 2, use [X] to detect the area. min ,X max ]×[Y min ,Y max The area can be represented in the form of [], for example, the detection area can be defined as [0,1000]×[0,600], that is, the detection area is a rectangle with a horizontal width of 1000km and a vertical width of 600km. The key detection area can also be represented in the same way, which will not be elaborated further.

[0077] The detection area is rasterized, that is, it is divided into several grids Δx×Δy, and the x-axis is divided into N. x The y-axis is divided into N parts.y If the grid consists of multiple grid cells, then the coordinates of the center point of any grid cell can be expressed as:

[0078] (X min +i x Δx + Δx / 2, Y min +i y Δy+Δy / 2)

[0079] Where: 0≤i x <N x ;0≤i y <N y The size of the grid can be coarsely adjusted by changing the values ​​of Δx and Δy according to the actual task requirements.

[0080] By using whether the center of each grid falls within the radar detection range as the standard, the calculation of the polygon area generated by the intersection and union of radar ranges can be transformed into the calculation of the intersection and union of grid center points. The purpose is to reduce the amount of calculation while ensuring accuracy.

[0081] Then, parameters such as radar information, detection area size, and key detection area size are input into the genetic algorithm, and the Pareto solution for the deployment of ground radar network is obtained through iteration.

[0082] Step 3: Calculate the weakness index W for each grid cell in the detection area using the obtained Pareto solution. The weakness index W is derived from the spatial weakness index W0. ky and frequency domain weakness index W py The weakness index W is specifically designed for optimizing air-to-ground collaborative detection network deployments. Its purpose is to identify weaknesses in ground-based radar network deployments targeting low, small, and slow targets (including UAVs) to guide the deployment planning of air-based radars. The purpose of calculating the airspace weakness index is to evaluate the tightness of the radar network in the airspace, while the calculation of the frequency domain weakness index evaluates the radar network's resistance to electromagnetic interference and anti-stealth capabilities. The weakness index W of a single grid is as follows:

[0083] W = W ky +W py

[0084] In the formula, W ky W is the airspace weakness index. py The frequency domain weakness index is represented by W, which ranges from [0,3].

[0085] Airspace Weakness Index W ky W is determined by the coverage multiplicity of the current raster. ky The value range is [0,1], as shown in the table below:

[0086] Table 1 Airspace Weakness Index

[0087] Coverage multiplicity No coverage First layer of coverage Double coverage Triple or higher coverage Airspace Weakness Index 0 0.7 0.9 1

[0088] Frequency domain weakness index W py Frequency band electromagnetic interference resistance F kgr and frequency band anti-stealth capability F fys The composition is as follows:

[0089] W py =F kgr +F fys

[0090] Frequency band electromagnetic interference resistance F kgr As shown in the following formula:

[0091]

[0092] In the formula, To form the union of the operating frequency bands of k radars covering the current grid, For the union of all operating frequency bands of ground radars that can be deployed; F kgr The value range is [0,1].

[0093] Frequency band anti-stealth capability F fys As shown in the following formula:

[0094]

[0095] In the formula, The score is the anti-stealth capability score for k radars operating in the current grid; F kgr The value range is [0,1].

[0096] The scores for a single radar's anti-stealth capability are shown in the table below:

[0097] Table 2 Scoring of Single Radar Anti-Stealth Capability

[0098] Operating frequency band HF VHF UHF L S C X other Score 1 1 0.8 0.5 0.5 0.5 0.5 0.6

[0099] By mapping the calculated weakness indices of all grid cells to a matrix, the weakness matrix of the entire detection area can be obtained.

[0100] Step 4: Set the threshold W according to the task requirements. min If for weak matrix any element W i Satisfy W i <W min Then W i These are called weak points. A breadth-first search is used to traverse the entire weak point matrix, finding each weak point and merging adjacent weak points (i.e., those above, below, left, and right) into a single weak area, ultimately resulting in multiple weak areas.

[0101] Then, each vulnerable area is sorted in descending order to facilitate the planning of patrol routes for airborne radar. The first criterion for sorting is the size of the area, i.e., the number of vulnerable points, and the second criterion is the degree of vulnerability, i.e., the average vulnerability index of each vulnerable point.

[0102] Step 5: Based on the number of air-based radars and the ranking of vulnerable areas, formulate the air-based radar deployment plan according to the principle of one air-based radar covering one vulnerable area. This is because in actual missions, the number of air-based radars is limited, and only the most vulnerable areas can be prioritized for deployment. The patrol routes of the air-based radars are selected in a runway shape to ensure the detection performance of the air-based radars.

[0103] The most important aspect of planning a runway-shaped patrol route is determining the patrol route's rotation angle and center. The range of an airborne radar can be simplified to a circle. To maximize coverage of vulnerable areas, the longest diagonal within those areas can be found to plan the patrol route. By mapping the vulnerable areas back to the detection area grid and connecting the centers of the edge grid cells of the vulnerable areas in pairs, the longest diagonal can be calculated, forming the airborne radar's patrol route. This ultimately generates an air-to-ground collaborative detection network deployment scheme.

[0104] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0105] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A method for optimizing the deployment of air-to-ground collaborative detection networks, characterized in that, Includes the following steps: Step 1: Determine the evaluation system for ground radar network deployment, and establish a mathematical model for ground radar network deployment based on the performance requirements and constraints of the evaluation system. Step 2: The detection area is rasterized, and the ground radar network is optimized and deployed using a genetic algorithm to obtain the Pareto solution for the ground radar network deployment. Step 3: Based on the Pareto solution of the ground radar network deployment, calculate the weakness index of each grid in the detection area, and then obtain the weakness matrix of the entire detection area. Step 4: Use breadth-first search to process the weak matrix, extract the weak regions, and sort them according to region size and degree of weakness; Step 5: Based on the number of air-based radars and the ranking of weak areas, formulate air-based radar deployment tasks, find the longest diagonal of the weak area, form the patrol route of the air-based radar, and finally generate an air-ground collaborative detection network deployment plan. In step 3, the weakness index This index is designed and proposed for optimizing the deployment of air-to-ground collaborative detection networks. Its purpose is to identify the deficiencies in the deployment of ground-based radar networks for low, small, and slow targets, so as to guide the deployment planning of air-based radars. The Pareto solution obtained in step 2 is used to calculate the weakness index of each grid in the detection area. Weakness Index Airspace Weakness Index and frequency domain weakness index composition; The weakness index As shown in the following formula: The airspace weakness index Determined by the coverage multiplicity of the current raster. The value range is [0,1]; The frequency domain weakness index Frequency band electromagnetic interference resistance and frequency band anti-stealth capabilities The composition is as follows: Electromagnetic interference resistance of the frequency band As shown in the following formula: In the formula, To cover the current grid Union of the operating frequency bands of the radar To be a union of all operating frequency bands of ground radar that can be deployed, The value range is [0,1]; The frequency band's anti-stealth capability As shown in the following formula: In the formula, To cover the current grid The score for the anti-stealth capability of the radar operating frequency band. The value range is [0,1]; After calculating the weakness index of all grids The weak matrix of the entire detection area is obtained. .

2. The air-ground cooperative detection network deployment optimization method according to claim 1, characterized in that, In step 1, the performance requirements of the evaluation system are spatial coverage coefficient, spatial overlap coverage coefficient and frequency interference coefficient, and the constraint condition of the evaluation system is the connection coefficient.

3. The air-ground cooperative detection network deployment optimization method according to claim 1, characterized in that, In step 2, the detection area is rasterized. The calculation of the polygon area generated by the intersection and union of the radar range is transformed into the calculation of the intersection and union of the grid center points, based on whether the center of each grid falls within the radar detection range. This aims to reduce the amount of calculation and ensure accuracy. Then, the radar information, the size of the detection area, and the size of the key detection area are input into the genetic algorithm. After iteration, the Pareto solution for the deployment of the ground radar network is obtained.

4. The air-ground cooperative detection network deployment optimization method according to claim 1, characterized in that, In step 4, the threshold is set according to the requirements of the detection mission. If for the weak matrix any element satisfy ,but These are called weak points; the breadth-first search is used to find each weak point in the weak matrix, and adjacent weak points are merged into a weak region.

5. The air-ground cooperative detection network deployment optimization method according to claim 1, characterized in that, In step 4, each weak area is sorted in descending order. The first criterion for sorting is the size of the area, i.e., the number of weak points, and the second criterion is the degree of weakness, i.e., the average weakness index of each weak point.

6. The air-ground cooperative detection network deployment optimization method according to claim 1, characterized in that, In step 5, based on the number of air-based radars and the ranking of vulnerable areas, and following the principle that one air-based radar protects one vulnerable area, the patrol routes of the air-based radars are selected in runway shape, and the deployment tasks of the air-based radars are formulated.

7. The method for optimizing the deployment of air-ground collaborative detection networks according to claim 1, characterized in that, In step 5, the weak area is mapped back to the detection area grid, the longest diagonal of the weak area grid is found to form the patrol route of the air-based radar, and finally the air-ground collaborative detection network deployment scheme is generated.

Images