A multi-task-oriented multi-radar optimization deployment method, electronic equipment and medium

Abstract

The present application relates to the field of radar deployment algorithm, in particular to a multi-task-oriented multi-radar optimization deployment method, electronic equipment and medium. The method comprises the following steps: obtaining the basic information of all tasks, randomly generating N deployment schemes, using the firework algorithm to perform optimization iteration until the iteration exit condition is met, obtaining an optimal deployment scheme, and the optimization target is to make the fitness value of the deployment scheme as small as possible. The present application faces actual engineering application, considers the power change factor of the radar under different working modes, optimizes the radar deployment position, and optimizes the working mode and array direction at the same time to meet the multi-task detection index requirement; the firework algorithm is used to solve the constructed optimization deployment model, and the convergence speed of the algorithm is improved.

Description

Technical Field

[0001] This invention relates to the field of radar deployment algorithms, specifically to a multi-task-oriented multi-radar optimized deployment method, electronic equipment, and medium. Background Technology

[0002] Optimal deployment of ground-based multi-radar systems is a key research area in radar networking systems. A good deployment scheme can improve the collaborative effectiveness of multiple radars, achieve optimal coverage of multiple mission airspaces, and effectively ensure mission success rates. Existing methods for optimizing the deployment of multiple mobile radars have three main problems:

[0003] First, existing research primarily focuses on optimizing the deployment positions and array pointing of multiple radars for single-space support missions, neglecting optimization methods for multi-mission scenarios, thus lacking practicality. Second, current models for optimizing multi-radar deployment are rather idealistic, typically optimizing array positions and pointing under fixed radar power parameters, ignoring the power variations of radars in different operating modes, resulting in significant discrepancies with engineering realities. Third, regarding model solving, existing methods typically employ traditional particle swarm optimization and genetic algorithms to search for the optimal solution. However, these algorithms suffer from slow convergence speeds and susceptibility to local optima, leading to slow model solving speeds and frequent inconsistencies in multiple solutions. Summary of the Invention

[0004] To address the above problems, this invention proposes a multi-radar optimization deployment method for multiple tasks. A multi-radar optimization deployment model is established, with overall multi-space coverage as the optimization objective, multi-radar deployment sites, operating modes, and array pointing as optimization variables, and multi-space detection index requirements as constraints. The firework algorithm is used to solve for the optimal solution, effectively improving the algorithm's convergence speed and demonstrating strong engineering applicability.

[0005] This invention provides a multi-radar optimized deployment method for multi-tasking, comprising the following steps:

[0006] S1: Obtain basic information for all tasks, including airspace range and priority;

[0007] The airspace range for all tasks is represented as follows:

[0008] A1, A2, A3, ... A j …A M

[0009] Among them, A j This represents the spatial range of the j-th task, and M is the total number of tasks;

[0010] The spatial domain of each task is a two-dimensional graphic.

[0011] The priority of all tasks is represented as follows:

[0012] D1, D2, D3, ...D j ...D M

[0013] Among them, D j D represents the priority of the j-th task. j ∈[0,1],D j The larger the value, the higher the priority;

[0014] S2: Randomly generate N deployment schemes, where N≥1. The deployment schemes are specifically represented as follows:

[0015] X1, X2, ... X i , ...X N

[0016] Among them, X i For the i-th deployment scheme, specifically...

[0017] X i =(L i1 Q i1 θ i1 ), (L i2 Q i2 θ i2 ), ......(L ik Q ik θ ik ), ......(L iP Q iP θ iP )

[0018] in,

[0019] P represents the number of radars to be deployed.

[0020] L ik This represents the location where the k-th radar is deployed in the i-th deployment scheme.

[0021] Q ik This represents the operating mode of the k-th radar deployment in the i-th deployment scheme.

[0022] θ ik This represents the azimuth angle of the array of the k-th radar in the i-th deployment scheme;

[0023] S3: Use the Fireworks Algorithm to optimize and iterate through N deployment schemes until the iteration exit condition is met, and obtain an optimal deployment scheme. The optimization goal is to minimize the fitness value of the deployment scheme.

[0024] The fitness function formula for calculating the fitness value of a deployment scheme is:

[0025]

[0026] in,

[0027] F i This represents the fitness value of the i-th deployment scheme;

[0028] λ1 is the multiple coverage weighting factor;

[0029] λ2 is the coverage weighting factor;

[0030] λ1∈[0, 1], λ2∈[0, 1], λ1+λ2=1;

[0031] f ij Let represent the coverage of the i-th deployment scheme relative to the j-th mission, specifically defined as: the area of ​​the airspace range of the j-th mission that is covered by at least one radar in the i-th deployment scheme divided by the area of ​​the airspace range of the j-th mission.

[0032] The multi-coverage rate of the i-th deployment scheme relative to the j-th mission is specifically defined as: the area of ​​the airspace range of the j-th mission that is covered by at least s radars in the i-th deployment scheme divided by the area of ​​the airspace range of the j-th mission, where s≥2.

[0033] Preferably, in step S1, the metric requirements for all tasks are also obtained, and the metric requirements include minimum coverage.

[0034] The minimum coverage for all tasks is expressed as:

[0035] Fg1, Fg2, Fg3, ... Fg j ...Fg M

[0036] Among them, Fg j This represents the minimum coverage for the j-th task;

[0037] It also includes step S4: check whether the obtained optimal deployment plan meets the indicator requirements of all tasks. If the optimal deployment plan meets the indicator requirements of all tasks, a success message is returned; otherwise, a failure message is returned.

[0038] Preferably, in step S3, the value of s is 3.

[0039] Preferred, f ij and The value is obtained through the following method:

[0040] S3.1: Transform the spatial domain of the j-th task into a grid, resulting in multiple grids;

[0041] S3.2: Based on the deployment site, deployment mode, and array pointing azimuth of each radar in the i-th deployment scheme, obtain the effective range, azimuth, and elevation range of each radar in the i-th deployment scheme based on its location.

[0042] S3.3: Determine which radars in the ith deployment scheme cover each grid that divides the airspace of the j-th task;

[0043] S3.4: The number of grids covered by at least one radar in the i-th deployment scheme is divided by the total number of grids divided by the airspace of the j-th mission, which gives f. ij ;

[0044] The result is obtained by dividing the number of grids covered by at least s radars in the i-th deployment scheme by the total number of grids divided by the airspace range of the j-th mission.

[0045] Preferably, in step S3.1, the step size of the gridding is 0.1 degrees for longitude and 0.1 degrees for latitude.

[0046] The present invention also provides an electronic device,

[0047] include:

[0048] Memory, used to store computer programs;

[0049] When a processor executes a program stored in memory, it implements the above method steps.

[0050] The present invention also provides a computer-readable storage medium.

[0051] The computer-readable storage medium stores a computer program, which, when executed by a processor, implements the above-described method steps.

[0052] Beneficial effects:

[0053] This invention addresses resource conflicts in multi-space support missions by establishing a reasonable optimized deployment model. Simultaneously, it uses available radar sites and their operational modes as inputs, and multiple radar deployment positions, operational modes, and array orientations as optimization variables, resulting in optimization outcomes that better align with actual engineering requirements. Furthermore, based on the established optimization model, this scheme employs the fireworks algorithm to solve the model, effectively improving solution efficiency. The significant advantages of this invention are:

[0054] 1. Innovatively proposes an optimized deployment method for multi-mission mobile radars, establishes an optimized deployment model under multiple constraints, effectively solves the problem of multi-mission resource conflicts, and improves the collaborative detection efficiency of multi-radar systems;

[0055] 2. For practical engineering applications, considering the power variation factors of radar under different working modes, while optimizing the radar deployment site, the working mode and array pointing are selected to meet the requirements of multi-mission detection indicators.

[0056] 3. The firework algorithm is used to solve the constructed optimized deployment model, which improves the convergence speed of the algorithm.

[0057] 4. When constructing the fitness function, although the goal is to maximize the coverage of all tasks, this invention incorporates multiple coverage rates as an inverse objective, which allows the Fireworks Algorithm to be better optimized. Attached Figure Description

[0058] Figure 1 A schematic diagram illustrating a scenario for optimized deployment of multiple radars for multi-space support missions.

[0059] Figure 2 This is a schematic diagram of a typical simulation scenario;

[0060] Figure 3 The results of the multi-radar optimization deployment algorithm in the simulation scenario are verified. Detailed Implementation

[0061] To make the objectives, features, and advantages of this invention more apparent and understandable, the technical solutions of the embodiments of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the embodiments described below are only some embodiments of this invention, and not all embodiments. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this invention.

[0062] like Figure 1 As shown, the present invention is used to select appropriate deployment sites, operating modes, and array pointing azimuth angles for a preset number of radars to be deployed, so that the deployed radars can maximize the coverage of all tasks.

[0063] A multi-task-oriented multi-radar optimized deployment method includes the following steps:

[0064] S1: Obtain the basic information and performance requirements of all tasks. The basic information includes airspace range and priority. The performance requirements include minimum coverage.

[0065] The airspace range for all tasks is represented as follows:

[0066] A1, A2, A3, ... A j ...A M

[0067] Among them, A j This represents the spatial range of the j-th task, and M is the total number of tasks;

[0068] The spatial domain of each task is a two-dimensional graphic.

[0069] The priority of all tasks is represented as follows:

[0070] D1, D2, D3, ...D j ...D M

[0071] Among them, D j D represents the priority of the j-th task. j ∈[0,1],D j The larger the value, the higher the priority;

[0072] The minimum coverage for all tasks is expressed as:

[0073] Fg1, Fg2, Fg3, ... Fg j …Fg M

[0074] Among them, Fg j This represents the minimum coverage for the j-th task;

[0075] S2: Randomly generate N deployment schemes, where N≥1. The deployment schemes are specifically represented as follows:

[0076] X1, X2, ... X i , ...X N

[0077] Among them, X i For the i-th deployment scheme, specifically...

[0078] X i =(L i1 Q i1 θ i1 ), (L i2 Q i2 θ i2 ), ......(L ik Q ik θ ik ), ......(L iP Q iP θ iP )

[0079] in,

[0080] P represents the number of radars to be deployed.

[0081] L ik This represents the location where the k-th radar is deployed in the i-th deployment scheme.

[0082] Q ik This represents the operating mode of the k-th radar deployment in the i-th deployment scheme.

[0083] θ ik This represents the azimuth angle of the array of the k-th radar in the i-th deployment scheme;

[0084] S3: Optimize and iterate the N deployment schemes using the Fireworks Algorithm until the iteration exit condition is met, and obtain an optimal deployment scheme. The optimization objective is to minimize the fitness value of the deployment scheme. The specific details of the Fireworks Algorithm are existing technologies and will not be elaborated here.

[0085] The fitness function formula for calculating the fitness value of a deployment scheme is:

[0086]

[0087] in,

[0088] F i This represents the fitness value of the i-th deployment scheme;

[0089] λ1 is the multiple coverage weighting factor;

[0090] λ2 is the coverage weighting factor;

[0091] λ1∈[0, 1], λ2∈[0, 1], λ1+λ2=1;

[0092] f ij Let represent the coverage of the i-th deployment scheme relative to the j-th mission, specifically defined as: the area of ​​the airspace range of the j-th mission that is covered by at least one radar in the i-th deployment scheme divided by the area of ​​the airspace range of the j-th mission.

[0093] The multi-coverage rate of the i-th deployment scheme relative to the j-th task is specifically defined as: the area of ​​the region in the airspace of the j-th task that is covered by at least s radars in the i-th deployment scheme divided by the area of ​​the airspace of the j-th task, where s≥2, preferably s=3.

[0094] As a preferred calculation method, f ij and The value is obtained through the following method:

[0095] S3.1: The spatial range of the j-th task is gridded to obtain multiple grids, with a gridding step size of 0.1 degrees longitude and 0.1 degrees latitude;

[0096] S3.2: Based on the deployment site, deployment mode, and array pointing azimuth of each radar in the i-th deployment scheme, obtain the effective range, azimuth, and elevation range of each radar in the i-th deployment scheme based on its location.

[0097] S3.3: Determine which radars in the ith deployment scheme cover each grid that divides the airspace of the j-th task;

[0098] S3.4: The number of grids covered by at least one radar in the i-th deployment scheme is divided by the total number of grids divided by the airspace of the j-th mission, which gives f. ij ;

[0099] The result is obtained by dividing the number of grids covered by at least s radars in the i-th deployment scheme by the total number of grids divided by the airspace range of the j-th mission.

[0100] S4: Check whether the obtained optimal deployment scheme meets the indicator requirements of all tasks. In this embodiment, specifically, check whether the coverage of the optimal deployment scheme relative to each task is greater than the minimum coverage of the corresponding task.

[0101] If the optimal deployment plan meets the performance requirements of all tasks, a success message is returned; otherwise, a failure message is returned. Verification example:

[0102] In this embodiment, there are a total of two tasks, and the airspace range is shown in Table 1:

[0103] Table 1 Mission Airspace Scope

[0104]

[0105] Both tasks have a priority of 1;

[0106] Both tasks require a minimum coverage rate of 10%.

[0107] Five radars are to be deployed, and their information is shown in Table 2:

[0108] Table 2 Radar Power Information

[0109]

[0110] The locations where radar can be deployed are shown in Table 3:

[0111] Table 3. Site Information

[0112]

[0113]

[0114] After using the above method, the optimal deployment scheme is obtained, as shown in Table 4:

[0115] Table 4 Optimal Allocation Scheme

[0116]

[0117] The process of this verification example is as follows: Figure 2 , 3 As shown in the chart analysis, in the optimization results, each radar selected a reasonable deployment site, working mode and pointing, which can effectively cover the airspace range of the two tasks. The model fitness value reached 19.04%, and the airspace coverage of both airspaces met the index requirements, so the solution results are valid.

[0118] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A multi-radar optimized deployment method for multi-task applications, characterized in that... Includes the following steps: S1: Obtain basic information for all tasks, including airspace range and priority; The airspace range for all tasks is represented as follows: in, This represents the spatial range of the j-th task, and M is the total number of tasks; The spatial domain of each task is a two-dimensional graphic. The priority of all tasks is represented as follows: in, This indicates the priority of the j-th task. , The larger the value, the higher the priority; S2: Randomly generate N deployment schemes, where N≥1. The deployment schemes are specifically represented as follows: in, For the i-th deployment scheme, specifically... in, P represents the number of radars to be deployed. This represents the location where the k-th radar is deployed in the i-th deployment scheme. This represents the operating mode of the k-th radar deployment in the i-th deployment scheme. This represents the azimuth angle of the array of the k-th radar in the i-th deployment scheme; S3: Use the Fireworks Algorithm to optimize and iterate through N deployment schemes until the iteration exit condition is met, and obtain an optimal deployment scheme. The optimization goal is to minimize the fitness value of the deployment scheme. The fitness function formula for calculating the fitness value of a deployment scheme is: in, This represents the fitness value of the i-th deployment scheme; Multiple coverage weighting factors; Coverage weighting factor; , , ； Let represent the coverage of the i-th deployment scheme relative to the j-th mission, specifically defined as: the area of ​​the airspace range of the j-th mission that is covered by at least one radar in the i-th deployment scheme divided by the area of ​​the airspace range of the j-th mission. The multi-coverage rate of the i-th deployment scheme relative to the j-th task is specifically defined as: the area of ​​the airspace of the j-th task that is covered by at least s radars in the i-th deployment scheme divided by the area of ​​the airspace of the j-th task, where s≥2. Specifically, based on the deployment site, operating mode, and azimuth angle of each radar array in the i-th deployment scheme, the effective range, azimuth, and elevation angle range of each radar in the i-th deployment scheme based on its location are obtained.

2. The multi-radar optimized deployment method for multi-task applications according to claim 1, characterized in that: In step S1, the metric requirements for all tasks are also obtained, including the minimum coverage rate. The minimum coverage for all tasks is expressed as: in, This represents the minimum coverage for the j-th task; It also includes step S4: check whether the obtained optimal deployment plan meets the indicator requirements of all tasks. If the optimal deployment plan meets the indicator requirements of all tasks, a success message is returned; otherwise, a failure message is returned.

3. The multi-radar optimized deployment method for multi-task applications according to claim 1, characterized in that: In step S3, the value of s is 3.

4. The multi-radar optimized deployment method for multi-task applications according to claim 1, characterized in that: and The value is obtained through the following method: S3.1: Transform the spatial domain of the j-th task into a grid, resulting in multiple grids; S3.2: Based on the deployment site, deployment mode, and array pointing azimuth of each radar in the i-th deployment scheme, obtain the effective range, azimuth, and elevation range of each radar in the i-th deployment scheme based on its location. S3.3: Determine which radars in the ith deployment scheme cover each grid that divides the airspace of the j-th task; S3.4: The number of grids covered by at least one radar in the i-th deployment scheme is divided by the total number of grids divided by the airspace of the j-th mission, thus obtaining the result. ; The result is obtained by dividing the number of grids covered by at least s radars in the i-th deployment scheme by the total number of grids divided by the airspace range of the j-th mission. .

5. The multi-radar optimized deployment method for multi-task applications according to claim 4, characterized in that: In step S3.1, the step size for gridding is 0.1 degrees for longitude and 0.1 degrees for latitude.

6. An electronic device, characterized in that, include: Memory, used to store computer programs; A processor, when executing a program stored in memory, implements the steps of the method described in any one of claims 1-5.

7. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the steps of the method described in any one of claims 1-5.

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