Method, device and equipment for rapid reconnaissance of ground fixed targets by multiple UAVs

Abstract

The present application relates to a method, device and equipment for rapid reconnaissance of ground fixed targets by multiple UAVs. The method comprises: comprehensively considering factors such as the area to be scanned by multiple UAVs, the distribution of fixed targets and the air defense range, establishing a UAV minimum sortie model and an optimal drop point model for rapid reconnaissance of ground fixed targets, and solving the UAV minimum sortie model according to the branch boundary algorithm and the combination optimization algorithm to obtain the minimum UAV sortie required for reconnaissance of all ground fixed targets in the area to be scanned; solving the UAV cruising path corresponding to the air defense range and the minimum UAV sortie to obtain the optimal UAV drop point; finally, dispatching a large carrier aircraft to drop the calculated minimum UAV sortie over the optimal drop point, and completing the reconnaissance of all ground fixed targets in the area to be scanned based on the dropped UAVs. The method of the present invention can rationally plan the execution of reconnaissance missions by multiple UAVs and realize rapid reconnaissance of ground fixed targets.

Description

Technical Field

[0001] The present application relates to the field of UAV technology, and in particular to a method, device and equipment for rapid reconnaissance of ground fixed targets by multiple UAVs. Background Art

[0002] In the 21st century, drones have become an important supplement to manned reconnaissance aircraft and reconnaissance satellites. They have many advantages such as low cost, flexible reconnaissance, and high resolution, and have become an important reconnaissance means.

[0003] While traditional technologies offer numerous models for multi-drone reconnaissance, most are designed for mobile targets. While this is necessary, in practice, many ground targets are immobile, often requiring rapid reconnaissance of numerous fixed targets. Dispatching a drone for each target is clearly inefficient, nor is dispatching a single drone for all targets. Furthermore, due to the short range of drones, dispatching drones for reconnaissance missions requires considering appropriate drop points to meet reconnaissance requirements. Summary of the Invention

[0004] Based on this, it is necessary to provide a method, device and equipment for multiple UAVs to quickly reconnaissance ground fixed targets that can meet actual reconnaissance needs in response to the above technical problems.

[0005] A method for rapidly reconnaissance of ground fixed targets by multiple UAVs, the method comprising:

[0006] Based on the scanning area of ​​multiple drones and the positions of ground fixed targets in the scanning area, a minimum drone sortie model is constructed. The minimum drone sortie model is solved using a branch and bound algorithm and a combinatorial optimization algorithm to obtain the minimum number of drone sorties required to scout all ground fixed targets in the scanning area.

[0007] Obtain the air defense range within the area to be scanned, build an optimal drone release point model based on the air defense range and the drone cruising path corresponding to the minimum number of drone sorties, and obtain the optimal drone release point within the area to be scanned by solving the optimal drone release point model;

[0008] Send a large carrier aircraft to release the calculated minimum number of drones over the optimal release point, and complete the reconnaissance of all ground fixed targets in the area to be scanned based on the released drones.

[0009] In one embodiment, when the UAV performs a reconnaissance mission in the area to be scanned, it flies in a straight line and performs downward scanning detection and synthetic aperture radar detection according to the visible light detection payload and synthetic aperture radar detection payload carried by it.

[0010] In one embodiment, a minimum number of drone sorties model is constructed based on the area to be scanned by multiple drones and the positions of ground fixed targets within the area to be scanned, including:

[0011] According to the scanning area of ​​multiple UAVs and the positions of ground fixed targets within the scanning area, the UAV cruising paths are simplified into rectangular strips with fixed width. Based on the requirement that a minimum number of rectangular strips should cover all ground fixed targets, a minimum number of UAV sorties model is constructed. The rectangular strips corresponding to the cruising paths of different UAVs have the same fixed width and can overlap with each other.

[0012] In one embodiment, a minimum number of drone sorties model is solved using a branch and bound algorithm and a combinatorial optimization algorithm to obtain the minimum number of drone sorties required to conduct reconnaissance of all ground fixed targets in the area to be scanned, including:

[0013] A function model corresponding to the minimum number of drone sorties model is established using a branch-and-bound algorithm. The variation of the rectangular bar connecting any two ground fixed targets in the function model is analyzed. The situation where the rectangular bar connecting any two ground fixed targets covers other ground fixed targets is obtained and stored in a feasible result set.

[0014] When there is a duplication in the feasible result set where the rectangular strip connecting any two ground fixed targets covers other ground fixed targets, the feasible result set is deduplicated to obtain a deduplicated feasible result set;

[0015] According to the combinatorial optimization algorithm, all feasible solutions in the feasible result set after deduplication are combined and optimized to obtain the optimal solution. The optimal solution represents the minimum number of drone sorties required to conduct reconnaissance of all ground fixed targets in the area to be scanned.

[0016] In one embodiment, the change mode of the rectangular bar connecting any two ground fixed targets in the function model includes: the maximum distance the rectangular bar translates upward, the maximum distance the rectangular bar translates downward, the maximum angle the rectangular bar rotates counterclockwise, and the maximum angle the rectangular bar rotates clockwise.

[0017] In one embodiment, all feasible solutions in the feasible result set after deduplication are combined and optimized according to a combinatorial optimization algorithm to obtain the optimal solution, including:

[0018] All feasible solutions in the feasible result set after deduplication are sorted and searched according to the combinatorial optimization algorithm, and the feasible solutions not in the optimal solution container are compared with the feasible solutions in the optimal solution container. When the feasible solution not in the optimal solution container is better than the feasible solution in the optimal solution container, the feasible solution not in the optimal solution container is stored in the optimal solution container and deduplication is performed; otherwise, continue to search for other feasible solutions not in the optimal solution container;

[0019] The coverage degree of ground fixed targets of all the feasible solutions after deduplication processing stored in the current optimal solution container is judged. When it is judged that all the feasible solutions after deduplication processing do not cover all ground fixed targets, continue to search for other feasible solutions that are not in the current optimal solution container; when it is judged that all the feasible solutions after deduplication processing can cover all ground fixed targets, all the feasible solutions after deduplication processing stored in the current optimal solution container are recorded and combined together as the optimal solution output.

[0020] In one embodiment, before solving the UAV minimum sortie model using the branch and bound algorithm and the combinatorial optimization algorithm, the method further includes:

[0021] The code compiler required to solve the minimum number of drone sorties model is downloaded in advance, the function modules corresponding to the branch and bound algorithm and the combinatorial optimization algorithm are imported into the code compiler in advance, and the code compiler is initialized.

[0022] In one embodiment, an air defense range within the area to be scanned is obtained, an optimal drone release point model is constructed based on the air defense range and the drone cruising path corresponding to the minimum number of drone sorties, and the optimal drone release point for drone release within the area to be scanned is obtained by solving the optimal drone release point model, including:

[0023] Obtain the air defense range within the area to be scanned, and construct an optimal drone release point model based on the air defense range and the drone cruise path corresponding to the minimum number of drone sorties. By solving the optimal drone release point model, the two intersection points between the air defense range boundary and the drone cruise path are determined, and the intersection point closest to the flight starting point of the large carrier aircraft is selected as the optimal release point;

[0024] When there are no obstacles between the optimal delivery point and the flight starting point of the large carrier aircraft, the large carrier aircraft flies directly to the optimal delivery point to release the drone; when there are obstacles between the optimal delivery point and the flight starting point of the large carrier aircraft, the shortest path between the optimal delivery point and the flight starting point of the large carrier aircraft is solved according to the Dijkstra algorithm, and the large carrier aircraft flies along the shortest path to the optimal delivery point to release the drone.

[0025] In one embodiment, a large carrier aircraft is dispatched to release the calculated minimum number of drone sorties over an optimal release point, and all ground fixed targets in the area to be scanned are reconnaissanced using the deployed drones, including:

[0026] A large carrier aircraft is dispatched to release the minimum number of drones calculated over the optimal release point, and the released drones are located on the center line of the drone's cruising path. The reconnaissance of all ground fixed targets in the area to be scanned is completed based on the released drones.

[0027] A device for rapidly reconnaissance of ground fixed targets by multiple UAVs, comprising:

[0028] The minimum number of drone sorties calculation module is used to build a minimum number of drone sorties model based on the area to be scanned by multiple drones and the positions of ground fixed targets in the area to be scanned. The minimum number of drone sorties model is solved using a branch and bound algorithm and a combinatorial optimization algorithm to obtain the minimum number of drone sorties required to conduct reconnaissance of all ground fixed targets in the area to be scanned.

[0029] The optimal release point calculation module is used to obtain the air defense range within the area to be scanned, build the optimal drone release point model based on the air defense range and the drone cruising path corresponding to the minimum number of drone sorties, and obtain the optimal release point for drone release in the area to be scanned by solving the optimal drone release point model;

[0030] The ground fixed target reconnaissance module is used to dispatch large carrier aircraft to release the calculated minimum number of drones over the optimal release point, and complete the reconnaissance of all ground fixed targets in the area to be scanned based on the released drones.

[0031] A computer device includes a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0032] Based on the scanning area of ​​multiple drones and the positions of ground fixed targets in the scanning area, a minimum drone sortie model is constructed. The minimum drone sortie model is solved using a branch and bound algorithm and a combinatorial optimization algorithm to obtain the minimum number of drone sorties required to scout all ground fixed targets in the scanning area.

[0033] Obtain the air defense range within the area to be scanned, build an optimal drone release point model based on the air defense range and the drone cruising path corresponding to the minimum number of drone sorties, and obtain the optimal drone release point within the area to be scanned by solving the optimal drone release point model;

[0034] Send a large carrier aircraft to release the calculated minimum number of drones over the optimal release point, and complete the reconnaissance of all ground fixed targets in the area to be scanned based on the released drones.

[0035] The above-mentioned method, device, and equipment for rapid reconnaissance of ground fixed targets by multiple drones comprehensively consider factors such as the size of the area to be scanned by multiple drones, the distribution of fixed targets, and the air defense range. A minimum drone sortie model and an optimal drop point model for rapid reconnaissance of ground fixed targets by multiple drones are established. The minimum drone sortie model is solved using a branch-and-bound algorithm and a combinatorial optimization algorithm to obtain the minimum number of drone sorties required to reconnoiter all ground fixed targets within the area to be scanned. The optimal drone drop point is then determined based on the drone cruising path corresponding to the air defense range and the minimum number of drone sorties. Finally, a large carrier aircraft is dispatched to release the calculated minimum number of drone sorties over the optimal drop point, and reconnaissance of all ground fixed targets within the area to be scanned is completed using the deployed drones. The method proposed by the present invention enables the rational planning of multiple drone reconnaissance missions and the rapid reconnaissance of ground fixed targets. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 A schematic flow chart of a method for rapidly reconnaissance of ground fixed targets by multiple UAVs according to one embodiment;

[0037] Figure 2 Schematic diagrams of three detection modes for a UAV performing a reconnaissance mission in one embodiment: (a) represents a side-view strip scan, (b) represents a downward-view circular scan, and (c) represents a downward-view strip scan;

[0038] Figure 3 A schematic diagram of target distribution of basic positions in one embodiment;

[0039] Figure 4 Schematic diagram of a minimum number of drone sorties model in one embodiment;

[0040] Figure 5 A schematic diagram of a variation of a rectangular bar connecting any two fixed ground objects in one embodiment;

[0041] Figure 6 A schematic diagram of a flow chart of a combinatorial optimization algorithm in one embodiment;

[0042] Figure 7 A schematic diagram of an optimal solution in an embodiment;

[0043] Figure 8 A schematic diagram of the air defense range within the area to be scanned in one embodiment

[0044] Figure 9 FIG. 1 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0045] In order to make the purpose, technical solutions and advantages of this application more clearly understood, the present application is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0046] In one embodiment, Figure 1 As shown, a method for rapidly reconnaissance of ground fixed targets by multiple UAVs is provided, comprising the following steps:

[0047] In step S1, a minimum number of drone sorties model is constructed based on the area to be scanned by multiple drones and the positions of ground fixed targets in the area to be scanned. The minimum number of drone sorties model is solved by a branch and bound algorithm and a combinatorial optimization algorithm to obtain the minimum number of drone sorties required to conduct reconnaissance on all ground fixed targets in the area to be scanned.

[0048] Step S2: Obtain the air defense range within the area to be scanned, build an optimal drone release point model based on the air defense range and the drone cruising path corresponding to the minimum number of drone sorties, and obtain the optimal drone release point for drone release within the area to be scanned by solving the optimal drone release point model.

[0049] Step S3: dispatch a large carrier aircraft to release the calculated minimum number of drones over the optimal release point, and complete the reconnaissance of all ground fixed targets in the area to be scanned based on the released drones.

[0050] The above-mentioned method for rapid reconnaissance of ground fixed targets by multiple drones comprehensively considers factors such as the size of the area to be scanned by multiple drones, the distribution of fixed targets, and the air defense range. It establishes a minimum drone sortie model and an optimal drop point model for rapid reconnaissance of ground fixed targets by multiple drones. The minimum drone sortie model is solved using a branch and bound algorithm and a combinatorial optimization algorithm to obtain the minimum drone sorties required to reconnoiter all ground fixed targets within the area to be scanned. The optimal drone drop point is then obtained based on the drone cruising path corresponding to the air defense range and the minimum drone sortie. Finally, a large carrier aircraft is dispatched to release the calculated minimum drone sorties over the optimal drop point, and reconnaissance of all ground fixed targets within the area to be scanned is completed based on the deployed drones. The method proposed by the present invention can rationally plan the execution of reconnaissance missions by multiple drones and achieve rapid reconnaissance of ground fixed targets.

[0051] In a specific example, consider a drone reconnaissance environment involving a Red vs. Blue confrontation, with the Blue team acting as the defender and the Red team acting as the attacker. Before launching an attack, the Red team will conduct intelligence reconnaissance on the Blue team to determine their true situation and then take appropriate action based on the enemy's situation. The Red team can employ various reconnaissance methods, including dispatching drones to conduct reconnaissance over the Blue team's territory, which is the simplest and most effective method. Properly planning drone sorties and reconnaissance routes while ensuring the Red team's own safety is crucial to the reconnaissance mission.

[0052] As the defending side, the Blue team will launch air defense and anti-missile defense to ensure the safety of important key areas. When conducting air defense and anti-missile defense, the number of key areas of the Blue team is greater than the number of available air defense firepower units, so it will take the form of mobile defense to ensure the safety of key areas. The Blue team has a total of basic positions B i (i=1,2,...,15) 15 in total, reserve position C i (i=1,2,...,45) 45 in total, important city O i (i=1,2,...,5) 5 in total, secondary city D i (i=1,2) 2 in total.

[0053] As the attacking side, the Red Army is equipped with several sorties of W-type UAVs. The maximum flight time of the W-type UAV is t = 10 minutes, the reconnaissance altitude is h = 30 km, and the reconnaissance speed is v = 3600 km / h. When performing reconnaissance missions, the detection payloads carried by the W-type UAVs include two types of detection payloads: visible light detection payloads and synthetic aperture radar (SAR) detection payloads. The band width of the visible light detection payload is w = 40 km, and the band width of the SAR detection payload is w = 30 km. When conducting reconnaissance, the W-type UAV generally has three detection modes, namely side-view band scan, downward-view circular scan, and downward-view band scan, such as Figure 2 As shown in the figure, the gray area is the scanning area. Figure 2 The side-view strip scan shown in (a) is to fix the side angle of the reconnaissance payload on the UAV and image the strip area on one side of the UAV's flight direction. The effective detection range is represented by the strip scan width H. Figure 2 The downward-looking circular scan shown in (b) means that the reconnaissance payload of the UAV can rotate 360 ​​degrees and form an image in a circular area with the projection point of the reconnaissance payload as the center. The effective detection range is represented by the detection radius of the circular area. Figure 2The downward-looking swath scan shown in (c) fixes the drone's reconnaissance payload, allowing it to image the strip directly below. The effective detection range is also represented by the swath width, H. Specifically, the Red Army's W-type drone flies in a straight line, performing downward-looking swath scan detection and synthetic aperture radar detection based on its carried visible light detection payload and synthetic aperture radar detection payload, respectively.

[0054] In a specific embodiment, a minimum number of drone sorties model is constructed based on the area to be scanned by multiple drones and the positions of ground fixed targets in the area to be scanned, including:

[0055] According to the speed and flight time of the W-type UAV equipped by the red side, it can be obtained that the detection length of the UAV is as long as 600km, and the detection length is represented by L. Taking into account the scanning method and detection width of the W-type UAV, it is concluded that the W-type UAV can scan a rectangular area with a length of 600km and a width of 30km. And because the UAV adopts a straight-line flight method when performing reconnaissance missions. The cruising altitude of the UAV h1 = 30km, and the air defense altitude of the blue side's air defense firepower unit h2 = 25km, so when constructing the minimum number of UAV sorties model, there is no need to consider whether the UAV is threatened by the air defense firepower unit. It is only necessary to consider the position distribution of the 15 basic fixed ground positions of the blue side that need to be reconnaissanced, and it is required to use the least number of W-type UAVs to conduct reconnaissance on these 15 basic positions of the blue side. The distribution of basic position targets is as follows: Figure 3 As shown, the “×” mark in the figure indicates the location of the basic position target.

[0056] According to the above background conditions, the area to be scanned by multiple UAVs is a rectangular area of ​​600km and 30km in width. The position distribution of 15 basic position targets in the area to be scanned is as follows: Figure 3 As shown in Figure 2, on this basis, considering that the distance between the basic positions of the blue side does not exceed the scanning length of the drone, the cruising path length can be ignored, and the drone cruising path is simplified into a rectangular strip with a fixed width. According to the requirement of covering 15 basic position targets with a minimum number of rectangular strips, a drone minimum sortie model is constructed, as shown in Figure 2. Figure 4 As shown in the figure, the rectangular bars corresponding to different UAV cruising paths have the same fixed width, and the rectangular bars can overlap with each other.

[0057] In one embodiment, a minimum number of drone sorties model is solved using a branch and bound algorithm and a combinatorial optimization algorithm to obtain the minimum number of drone sorties required to conduct reconnaissance of all ground fixed targets in the area to be scanned, including:

[0058] Step 1: Prerequisites. Download the code compiler (PyCharm) required to solve the minimum number of drone sorties model.

[0059] Step 2: Initialization. Pre-import the function modules corresponding to the branch and bounds algorithm and the combinatorial optimization algorithm into the code compiler and initialize the code compiler. Specifically, import the coordinates of 15 basic blue team positions and define width as the drone's scan width, T as the number of required iterations, Result as the container for storing feasible results, and Q as the container for storing the optimal solution.

[0060] Step 3: Branch and define. According to the branch and define algorithm, a function model corresponding to the minimum number of drone sorties model is established. The change mode of the rectangular bar connecting any two basic position targets in the function model is analyzed to obtain the situation where the rectangular bar connecting any two basic position targets covers other basic position targets and store them in the feasible result set. The feasible result set contains feasible solutions with different coverage of basic position targets. Among them, the change mode of the rectangular bar connecting any two basic position targets in the function model is as follows: Figure 5 As shown, it includes the maximum distance the rectangular bar can be translated upward, the maximum distance the rectangular bar can be translated downward, the maximum angle the rectangular bar can be rotated counterclockwise, and the maximum angle the rectangular bar can be rotated clockwise.

[0061] Step 4: Deduplication. In the branch and bound step, since the change mode after the connection of two basic position targets is considered at the beginning, all two basic position targets are considered, so there will be There are many situations, and there may be duplicates in these situations. For example, the rectangle formed by points B1 and B2 can cover points B1, B2, B3, B4, and B5, and the rectangle formed by points B4 and B5 can also cover points B1, B2, B3, B4, and B5. Therefore, when there are feasible solutions in the feasible result set that contain the same points, they need to be deleted and only one is retained. In other words, the feasible result set needs to be deduplicated to obtain a deduplicated feasible result set.

[0062] Step 5: Combinatorial optimization solution. After deduplication in step 4, all feasible solutions (also called available modules) in the feasible result set after deduplication can be obtained. Some modules contain repeated points, so they need to be optimized. Considering that the feasible solutions are all discrete modules, a combinatorial optimization algorithm is used to solve and obtain the minimum number of drone sorties. Combinatorial optimization algorithm refers to an algorithm that finds the optimal solution among a finite number of feasible solutions. It can be for continuous variables or discrete variables. The specific solution steps of combinatorial optimization are as follows: Figure 6 As shown, including:

[0063] (a) Sort all available modules to avoid duplication when combining them;

[0064] (b) Search for available modules that are not in the optimal solution container Q, that is, search for unused modules;

[0065] (c) comparing the available modules that are not in the optimal solution container with the available modules contained in the container;

[0066] (d) Determine whether the available modules not in the optimal solution container are better than the available modules in the optimal solution container (i.e., determine whether the available modules not in the optimal solution container can cover the new target point, or whether fewer modules are used when the number of covered target points is the same). If so, store the available modules not in the optimal solution container in the optimal solution container and perform deduplication. If not, return to step (b) and continue searching for available modules not in the optimal solution container Q.

[0067] (e) Determine the target point coverage of all available modules after deduplication processing stored in the current optimal solution container. If it is determined that all available modules after deduplication processing can cover 15 target points, then record the number of available modules at this time and combine them together as the optimal solution output; if it is determined that all available modules after deduplication processing do not cover 15 target points, return to step (b);

[0068] (f) Determine whether the preset number of iterations has been reached. If it has, terminate the optimization and return to the optimal solution. Otherwise, return to step (b). The purpose of setting the number of iterations is that the larger the number of iterations, the closer the optimization will be to the optimal solution.

[0069] By solving the above-mentioned model of minimum number of drone sorties, the optimal solution is obtained as follows: Figure 7 As shown, it can be seen that the Red Army needs at least 4 W-type drones to conduct detection and reconnaissance of the 15 targets that need to be reconnaissanced.

[0070] In a specific embodiment, an air defense range within the area to be scanned is obtained, and an optimal drone release point model is constructed based on the air defense range and the drone cruising path corresponding to the minimum number of drone sorties. By solving the optimal drone release point model, the optimal release point for drone release within the area to be scanned is obtained, including:

[0071] First, the air defense range in the area to be scanned is obtained, and the optimal drone release point model is constructed based on the air defense range and the drone cruising path corresponding to the minimum number of drone sorties. Specifically, since the red side's W-type drone uses a straight-line flight method to conduct detection, a large carrier aircraft is required to carry the W-type drone to one end of the drone's cruising path and release it on the center line of the cruising path. Considering that the target to be reconnaissance is equipped with an air defense firepower unit and has air defense capabilities, the air defense altitude is 25km, the air defense range radius is 160km, and the flight altitude of the large carrier aircraft is 7km, so the large aircraft needs to release the W-type drone outside the strike range of the air defense firepower unit F to ensure its own safety. The starting point of the large carrier aircraft is the airport R, and the coordinates of the blue side's 45 reserve positions are shown in Table 1. The blue side's air defense firepower unit maneuvers between 15 basic positions and 45 reserve positions to ensure that it can defend 5 key cities. According to the air defense range of the air defense firepower unit, the overall defense range of the blue side's position can be obtained, as shown in Figure 8 As shown, Figure 8 The middle circle represents the air defense range boundary of the air defense firepower unit. L1, L2, L3, and L4 represent the cruising paths of the minimum four required W-type drones. Large carrier aircraft need to deploy W-type drones beyond the air defense range boundary to ensure the smooth progress of the Red Army's reconnaissance mission.

[0072] Table 1 Coordinates of the reserve positions

[0073]

[0074] Then, by solving the optimal drone release point model, the two intersection points between the air defense range boundary and the drone cruising path are determined, and the intersection point closest to the flight starting point of the large carrier aircraft is taken as the optimal release point.

[0075] When there are no obstacles between the optimal drop point and the flight starting point of the large carrier aircraft, the large carrier aircraft will directly fly to the optimal drop point to release the drone; when there are obstacles between the optimal drop point and the flight starting point of the large carrier aircraft, the shortest path between the optimal drop point and the flight starting point of the large carrier aircraft is solved according to the Dijkstra algorithm, and the large carrier aircraft will fly to the optimal drop point along the shortest path to release the drone. Figure 8As shown, the intersection of the three cruising paths L2, L3, and L4 with the left side of the air defense range boundary can be directly used as the optimal release point. A large carrier aircraft, departing from Airport R, can fly directly to the optimal release point to release the drone. However, the straight line from the intersection of the cruising path L1 with the air defense range boundary to Airport R will be blocked by other Blue defensive positions along the way, so the optimal release point for the drone on L1 needs to be analyzed. First, the obstacle is abstracted, approximated with a polygon, and the obstacle itself is replaced by its convex hull. The vertices, starting points, and endpoints of all obstacles are connected pairwise. Finally, the Dijkstra algorithm is used to find the shortest path between two points without crossing any obstacles. The large carrier aircraft, departing from Airport R, flies along the shortest path to the optimal release point to release the drone.

[0076] It should be understood that although Figure 1 The steps in the flowchart are shown in sequence as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified in this document, there is no strict order restriction for the execution of these steps, and these steps can be executed in other orders. In addition, Figure 1 At least part of the steps may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least part of the sub-steps or stages of other steps.

[0077] In one embodiment, a device for rapidly reconnaissance of ground fixed targets by multiple UAVs is provided, comprising: a minimum UAV sortie calculation module, an optimal placement point calculation module, and a ground fixed target reconnaissance module, wherein:

[0078] The minimum number of drone sorties calculation module is used to build a minimum number of drone sorties model based on the area to be scanned by multiple drones and the positions of ground fixed targets in the area to be scanned. The minimum number of drone sorties model is solved using a branch and bound algorithm and a combinatorial optimization algorithm to obtain the minimum number of drone sorties required to conduct reconnaissance of all ground fixed targets in the area to be scanned.

[0079] The optimal release point calculation module is used to obtain the air defense range within the area to be scanned, build the optimal drone release point model based on the air defense range and the drone cruising path corresponding to the minimum number of drone sorties, and obtain the optimal release point for drone release in the area to be scanned by solving the optimal drone release point model;

[0080] The ground fixed target reconnaissance module is used to dispatch large carrier aircraft to release the calculated minimum number of drones over the optimal release point, and complete the reconnaissance of all ground fixed targets in the area to be scanned based on the released drones.

[0081] Regarding the specific definition of the device for rapid reconnaissance of ground fixed targets by multiple UAVs, please refer to the definition of the method for rapid reconnaissance of ground fixed targets by multiple UAVs above, and will not be repeated here. The various modules in the above-mentioned device for rapid reconnaissance of ground fixed targets by multiple UAVs can be implemented in whole or in part by software, hardware, or a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the computer device in hardware form, or can be stored in the memory of the computer device in software form, so that the processor can call and execute the operations corresponding to the above modules.

[0082] In one embodiment, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as follows: Figure 9 As shown. The computer device includes a processor, memory, network interface, display screen and input device connected via a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external terminal via a network connection. When the computer program is executed by the processor, a method for rapid reconnaissance of ground fixed targets by multiple UAVs is implemented. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or a button, trackball or touchpad provided on the computer device housing, or an external keyboard, touchpad or mouse.

[0083] Those skilled in the art will understand that Figure 9 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0084] In one embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0085] Based on the scanning area of ​​multiple drones and the positions of ground fixed targets in the scanning area, a minimum drone sortie model is constructed. The minimum drone sortie model is solved using a branch and bound algorithm and a combinatorial optimization algorithm to obtain the minimum number of drone sorties required to scout all ground fixed targets in the scanning area.

[0086] Obtain the air defense range within the area to be scanned, build an optimal drone release point model based on the air defense range and the drone cruising path corresponding to the minimum number of drone sorties, and obtain the optimal drone release point within the area to be scanned by solving the optimal drone release point model;

[0087] Send a large carrier aircraft to release the calculated minimum number of drones over the optimal release point, and complete the reconnaissance of all ground fixed targets in the area to be scanned based on the released drones.

[0088] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0089] The above-described embodiments merely represent several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that a person skilled in the art could make various modifications and improvements without departing from the spirit of the present application, all of which fall within the scope of protection of the present application. Therefore, the scope of protection of the present patent application shall be determined by the appended claims.

Claims

1. A method for rapid reconnaissance of ground fixed targets by multiple UAVs, characterized in that: The method comprises: Based on the area to be scanned by multiple drones and the positions of ground fixed targets in the area to be scanned, a minimum drone sortie model is constructed. The minimum drone sortie model is solved using a branch and bound algorithm and a combinatorial optimization algorithm to obtain the minimum number of drone sorties required to scout all ground fixed targets in the area to be scanned; Obtaining an air defense range within the area to be scanned, building an optimal drone release point model based on the air defense range and the drone cruising path corresponding to the minimum number of drone sorties, and obtaining an optimal drone release point for drone release within the area to be scanned by solving the optimal drone release point model; Dispatching a large carrier aircraft to release the calculated minimum number of drone sorties over the optimal release point, and completing the reconnaissance of all ground fixed targets in the area to be scanned based on the released drones; The minimum number of drone sorties model is solved by a branch and bound algorithm and a combinatorial optimization algorithm to obtain the minimum number of drone sorties required to conduct reconnaissance of all ground fixed targets in the area to be scanned, including: A function model corresponding to the minimum number of drone sorties model is established according to a branch and bound algorithm, and a variation pattern of a rectangular bar connecting any two fixed ground targets in the function model is analyzed to obtain a situation where a rectangular bar connecting any two fixed ground targets covers other fixed ground targets and store the results in a feasible result set; When there is a duplication in the feasible result set where the rectangular strip connecting any two ground fixed objects covers other ground fixed objects, performing deduplication processing on the feasible result set to obtain a deduplicated feasible result set; All feasible solutions in the feasible result set after deduplication are combined and optimized according to a combination optimization algorithm to obtain an optimal solution, which represents the minimum number of drone sorties required to conduct reconnaissance on all ground fixed targets in the area to be scanned.

2. The method according to claim 1, characterized in that When the UAV performs a reconnaissance mission in the area to be scanned, it flies in a straight line and performs downward scanning detection and synthetic aperture radar detection according to the visible light detection payload and synthetic aperture radar detection payload carried by it.

3. The method according to claim 2, characterized in that Based on the scanning area of ​​multiple drones and the positions of ground fixed targets in the scanning area, a minimum number of drone sorties model is constructed, including: According to the scanning area of ​​multiple UAVs and the positions of ground fixed targets within the scanning area, the UAV cruising paths are simplified into rectangular strips with fixed width. Based on the requirement that a minimum number of rectangular strips should cover all ground fixed targets, a minimum number of UAV sorties model is constructed. The rectangular strips corresponding to the cruising paths of different UAVs have the same fixed width and can overlap with each other.

4. The method according to claim 1, wherein The change mode of the rectangular bar connecting any two ground fixed targets in the function model includes: the maximum distance the rectangular bar moves upward, the maximum distance the rectangular bar moves downward, the maximum angle the rectangular bar rotates counterclockwise, and the maximum angle the rectangular bar rotates clockwise.

5. The method according to claim 1, characterized in that All feasible solutions in the feasible result set after deduplication are combined and optimized according to a combination optimization algorithm to obtain the optimal solution, including: Sorting and searching all feasible solutions in the deduplicated feasible result set according to the combinatorial optimization algorithm, and comparing the searched feasible solutions that are not in the optimal solution container with the feasible solutions in the optimal solution container; when the feasible solution that is not in the optimal solution container is better than the feasible solution in the optimal solution container, storing the feasible solution that is not in the optimal solution container in the optimal solution container and performing deduplication processing; otherwise, continuing to search for other feasible solutions that are not in the optimal solution container; The coverage degree of ground fixed targets of all the feasible solutions after deduplication processing stored in the current optimal solution container is judged. When it is judged that all the feasible solutions after deduplication processing do not cover all ground fixed targets, continue to search for other feasible solutions that are not in the current optimal solution container; when it is judged that all the feasible solutions after deduplication processing can cover all ground fixed targets, all the feasible solutions after deduplication processing stored in the current optimal solution container are recorded and combined together as the optimal solution output.

6. The method according to claim 1, characterized in that Before solving the minimum number of UAV sorties model by using the branch and bound algorithm and the combinatorial optimization algorithm, the method further includes: A code compiler required for solving the minimum number of drone sorties model is downloaded in advance, function modules corresponding to the branch and bound algorithm and the combinatorial optimization algorithm are imported into the code compiler in advance, and the code compiler is initialized.

7. The method according to claim 1, characterized in that Obtaining an air defense range within the area to be scanned, building an optimal drone release point model based on the air defense range and the drone cruising path corresponding to the minimum number of drone sorties, and obtaining an optimal drone release point for drone release within the area to be scanned by solving the optimal drone release point model, including: Obtaining an air defense range within the area to be scanned, constructing an optimal drone release point model based on the air defense range and the drone cruise path corresponding to the minimum number of drone sorties, and solving the optimal drone release point model to determine two intersection points between the air defense range boundary and the drone cruise path, and selecting the intersection point closest to the flight starting point of the large carrier aircraft as the optimal release point; When there are no obstacles between the optimal delivery point and the flight starting point of the large carrier aircraft, the large carrier aircraft flies directly to the optimal delivery point to deliver the drone; when there are obstacles between the optimal delivery point and the flight starting point of the large carrier aircraft, the shortest path between the optimal delivery point and the flight starting point of the large carrier aircraft is solved according to the Dijkstra algorithm, and the large carrier aircraft flies along the shortest path to the optimal delivery point to deliver the drone.

8. The method according to claim 1, characterized in that Dispatching a large carrier aircraft to release the calculated minimum number of drone sorties over the optimal release point, and completing reconnaissance of all ground fixed targets in the area to be scanned based on the released drones, including: A large carrier aircraft is dispatched to release the calculated minimum number of drone sorties over the optimal release point, and the released drones are located on the center line of the drone cruising path, and reconnaissance of all ground fixed targets in the area to be scanned is completed based on the released drones.

9. A device for rapid reconnaissance of ground fixed targets by multiple UAVs, characterized in that: The device comprises: A minimum number of drone sorties calculation module is used to construct a minimum number of drone sorties model based on the area to be scanned by multiple drones and the positions of ground fixed targets in the area to be scanned. The minimum number of drone sorties model is solved using a branch and bound algorithm and a combinatorial optimization algorithm to obtain the minimum number of drone sorties required to conduct reconnaissance of all ground fixed targets in the area to be scanned. An optimal release point calculation module is used to obtain the air defense range within the area to be scanned, construct an optimal drone release point model based on the air defense range and the drone cruising path corresponding to the minimum number of drone sorties, and obtain the optimal release point for drone release within the area to be scanned by solving the optimal drone release point model; A ground fixed target reconnaissance module is used to dispatch a large carrier aircraft to release the calculated minimum number of drone sorties over the optimal release point, and complete the reconnaissance of all ground fixed targets in the area to be scanned based on the released drones; The minimum number of drone sorties model is solved by a branch and bound algorithm and a combinatorial optimization algorithm to obtain the minimum number of drone sorties required to conduct reconnaissance of all ground fixed targets in the area to be scanned, including: A function model corresponding to the minimum number of drone sorties model is established according to a branch and bound algorithm, and a variation pattern of a rectangular bar connecting any two fixed ground targets in the function model is analyzed to obtain a situation where a rectangular bar connecting any two fixed ground targets covers other fixed ground targets and store the results in a feasible result set; When there is a duplication in the feasible result set where the rectangular strip connecting any two ground fixed objects covers other ground fixed objects, performing deduplication processing on the feasible result set to obtain a deduplicated feasible result set; All feasible solutions in the feasible result set after deduplication are combined and optimized according to a combination optimization algorithm to obtain an optimal solution, which represents the minimum number of drone sorties required to conduct reconnaissance on all ground fixed targets in the area to be scanned.

10. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 8 are implemented.

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