Multi-uav cooperative positioning and target allocation method

Abstract

The application belongs to the technical field of unmanned aerial vehicle, and particularly relates to a multi-unmanned aerial vehicle cooperative positioning and target distribution method, which solves the technical problems of poor positioning accuracy and high cost of the existing multi-unmanned aerial vehicle formation method, and the method is as follows: in the multi-unmanned aerial vehicle formation, only one master control unmanned aerial vehicle is equipped with a laser range finder, high-precision three-dimensional positioning of multiple targets is realized through laser ranging combined with an image pixel proportion calculation method, global optimal target distribution is completed by using a Hungarian algorithm, and finally target coordinates are broadcast to other members of the formation. The application reduces the hardware cost and maintenance cost of the entire unmanned aerial vehicle formation, fuses the absolute accuracy of laser and the relative proportionality of vision, and obtains three-dimensional coordinates of all targets by using laser ranging only once. The fixed point iteration method ensures high convergence accuracy in the earth height calculation, a Euclidean distance cost matrix is constructed, the Hungarian algorithm is used for global optimal solution, and the shortest total flight range is ensured.

Description

Technical Field

[0001] This invention belongs to the field of aircraft technology, and particularly relates to the field of unmanned aerial vehicle (UAV) technology, specifically a method for multi-UAV cooperative positioning and target allocation. Background Technology

[0002] With the rapid development of small drone technology, low-altitude drone activities are becoming increasingly frequent. In multi-drone collaborative missions and control scenarios, it is necessary to quickly locate multiple aerial targets and rationally allocate mission resources. Existing technical solutions have the following main problems:

[0003] (1) The cost of multi-drone full configuration scheme is high: Existing cooperative positioning schemes usually require each drone in the formation to be equipped with a laser rangefinder or high-precision inertial navigation equipment, which is costly and heavy, and is not conducive to small drone platforms.

[0004] (2) Limited positioning accuracy of single unit: When relying solely on GPS or monocular images for target positioning, the distance estimation error is large, especially in the height direction, making it difficult to meet the accuracy requirements of actual tasks.

[0005] (3) Lack of optimization in target allocation: Existing solutions mostly use the principle of proximity or preset rules to allocate targets, which fails to minimize the overall cost (such as total flight distance or time) at the system level, resulting in low mission efficiency.

[0006] (4) Lack of information sharing mechanism: In multi-machine collaborative scenarios, each machine is independently positioned and there is a lack of an effective target coordinate broadcasting mechanism, resulting in waste of resources due to repeated positioning.

[0007] Therefore, there is an urgent need for a low-cost, high-precision, and engineerable method for multi-UAV cooperative localization and target allocation to solve the above-mentioned technical problems. Summary of the Invention

[0008] To overcome the technical problems of poor positioning accuracy and high cost in existing multi-UAV formation methods, this invention provides a multi-UAV cooperative positioning and target allocation method.

[0009] This invention provides a method for multi-UAV cooperative localization and target allocation, comprising the following steps:

[0010] S1. System Initialization and Role Setting: Assume the total number of drones in the drone formation is N, and M targets need to be assigned. One drone in the formation is designated as the master drone, and the rest are designated as cooperative drones. The master drone is equipped with a dual-light pod with laser rangefinding function, which is used for target positioning and task assignment. The cooperative drones are equipped with data link communication equipment, which is used to receive broadcast information.

[0011] S2. The main control drone selects a reference target within its formation's field of view. Perform laser ranging to obtain the distance between the main control UAV and the reference target. radial distance between Simultaneously, it collects data including reference targets through its dual-light pod. The current frame image of the dual-light pod and other targets within the formation's field of view is used to record the roll angle output by the pod attitude sensor at the moment of laser ranging. Pitch angle Yaw angle And the GPS location coordinates of the main control drone ( , , ), to obtain the reference target Three-dimensional coordinate vector in the ENU coordinate system ;

[0012] S3. In the current frame image, the pixel bounding boxes of each target are obtained using a target detection algorithm, and a reference target is set. The area of ​​the pixel bounding box is , No. One goal The area of ​​the pixel bounding box is Then refer to the target Corresponding pixel size and the pixel size of the other targets They are respectively:

[0013] ,

[0014] ,

[0015] Based on the pinhole camera model, the imaging size of the target in the current frame image. Compared with the actual physical size of the target and target distance The following proportional relationship exists between them:

[0016] ,

[0017] in The focal length of the pinhole camera;

[0018] Then, refer to the target The imaging sizes of the remaining targets are as follows:

[0019] ,

[0020] ,

[0021] Assuming all targets have the same physical size, and In this case, we get:

[0022] ,

[0023] Then the main control drone and the first One goal radial distance The estimation formula is:

[0024] ,

[0025] in, , and Reference targets The bounding box's pixel width and height; For the first One goal The pixel size in the current frame image. , and The first One goal The bounding box's pixel width and height;

[0026] based on , obtained the One goal The three-dimensional coordinate vector in the ENU coordinate system is:

[0027] ,

[0028] in, The dual-light pod of the main control drone is aligned with the first One goal The unit direction vector of the camera coordinate system at that time. Through the first One goal R is the pod attitude rotation matrix corresponding to the current frame image, calculated by inversely using the pixel coordinates and camera parameters in the current frame image.

[0029] S4, the first One goal The three-dimensional coordinate vectors in the ENU coordinate system are converted to ECEF coordinates, and then the ECEF coordinates are converted to WGS-84 geodetic coordinates.

[0030] S5, will Targets are assigned to For a drone, the sub-steps are as follows:

[0031] S51. Calculation of cost matrix elements:

[0032] Cost matrix elements Indicates the first A drone flew to the The Euclidean distance cost for each target, where... , , Calculated using the following formula:

[0033] ,

[0034] in, For the first The current ECEF coordinates of the drone are obtained and reported in real time by each cooperating drone via GPS, and then aggregated to the main control drone via data link. Let J be the ECEF coordinates of the j-th target, which are calculated by steps S2 to S4.

[0035] S52. Objective Function and Constraints:

[0036] With minimizing the total flight distance of the formation as the objective function, the formula is:

[0037] ,

[0038] in, To assign decision variables, Indicates the target Assigned to drones The constraints are:

[0039] ,

[0040] ,

[0041] ;

[0042] S53. Solve using the Hungarian algorithm. The sub-steps are as follows:

[0043] S531, the cost matrix Subtract the minimum value of each row from the array to ensure that each row contains at least one zero element.

[0044] S532, The cost matrix after processing S531 Subtract the minimum value from each column so that each column has at least one zero element;

[0045] S533. Find the set of independent zero elements, that is, elements that are not in the same row but in the same column. If N independent zeros are found, the optimal allocation is obtained.

[0046] S534. If there are fewer than N independent zeros, cover all zero elements with the minimum number of straight lines, update the matrix, that is, subtract the minimum uncovered value from the uncovered elements, add back the double-covered elements, and repeat step S533 until N independent zeros are found.

[0047] The Hungarian algorithm outputs the optimal allocation matrix. ,in, Indicates the target Optimal allocation to drones The optimal total cost is:

[0048] ;

[0049] S6. The master drone sends a broadcast data packet containing the target allocation information corresponding to each cooperating drone to all members of the formation via a one-way broadcast through a data link. The broadcast data packet includes the target number. Target latitude WGS-84 Target WGS-84 longitude Target Earth High and the corresponding drone number assignment After receiving the broadcast, each coordinating drone independently plans and executes its flight mission according to the assigned WGS-84 geodetic coordinates; the coordinating drones do not need to reply for confirmation, and the master drone assumes the broadcast was successful.

[0050] In this invention, only the master drone in the formation is equipped with a high-precision laser rangefinder and a dual-light pod, while the remaining large number of cooperating drones are only equipped with data link communication equipment and low-cost visible light pods. This breaks the traditional high-cost model that requires each drone to be equipped with a laser rangefinder. The cooperating drones do not need expensive ranging equipment and can perform tasks solely based on vision and broadcast commands, thereby reducing the hardware cost and maintenance cost of the entire drone formation.

[0051] This invention combines the absolute precision of laser with the relative proportionality of vision, allowing the acquisition of the three-dimensional coordinates of all targets using only a single laser ranging measurement. Utilizing the same frame of image avoids motion errors caused by time-sharing measurements of multiple targets, ensuring the relative consistency of the spatial positions of targets at the same moment.

[0052] The fixed-point iterative method ensures high convergence accuracy in geodetic height calculation (reaching...). (Radius), ensuring absolute accuracy of coordinates during long-distance flight.

[0053] This invention transforms the allocation problem into a linear assignment problem, constructs an Euclidean distance cost matrix, and employs the Hungarian algorithm for global optimization. This ensures the shortest total flight distance for the formation, saving overall fuel / electricity consumption and increasing the coverage of a single mission. Each aircraft is assigned one target, and each target is assigned only once, eliminating resource conflicts and task omissions, and ensuring orderly mission execution.

[0054] Preferably, the sub-step of step S2 is as follows:

[0055] S21. The unit direction vector of the pod's optical axis in the camera coordinate system is:

[0056] ;

[0057] S22, Roll angle collected in real time by the pod attitude sensor Pitch angle and yaw angle Construct the pod attitude rotation matrix R according to the ZYX Euler angle order, and transform the camera coordinate system vector to the ENU coordinate system to obtain:

[0058] ,

[0059] The basic rotation matrices are:

[0060] ,

[0061] ,

[0062] ,

[0063] S23. Using the current position of the main control UAV as the origin, calculate the three-dimensional coordinate vector of the reference target in the ENU coordinate system. for:

[0064] ,

[0065] in, Here is the attitude rotation matrix. Let be the unit direction vector of the pod's optical axis in the camera coordinate system. The radial distance between the master-controlled UAV and the reference target. The form is [ , , ] T , To reference the eastward offset of the target relative to the main control UAV, To reference the northward offset of the target relative to the main control UAV, This is the azimuth offset of the reference target relative to the main control UAV.

[0066] Preferably, the sub-step of step S4 is as follows:

[0067] S41, based on the GPS location of the main control drone ( , , Let ENU be the origin, and convert it to ECEF coordinates. , , The ellipsoidal parameters for WGS-84 geodetic coordinates are as follows: semi-major axis reciprocal of flatness First eccentricity The formula for calculating the ECEF coordinates of the current position of the main control UAV is:

[0068] ,

[0069] in, ,

[0070] ,

[0071] ,

[0072] No. One goal The ECEF coordinates are obtained by superimposing the ENU offset on the ECEF coordinates of the current position of the main control UAV:

[0073] ,

[0074] in, For the transformation matrix,

[0075] ,

[0076] S42, by the One goal The calculation of ECEF coordinates into WGS-84 geodetic coordinates uses a fixed-point iteration method, and its sub-steps are as follows:

[0077] S421. Calculate geodetic longitude :

[0078] ,

[0079] S422, Calculate the equatorial projected distance :

[0080] ,

[0081] S423, Iterative calculation of geodetic latitude The initial value of the iteration is set to Iterate and update according to the following formula until the difference between two adjacent iterations is less than 1. radian:

[0082] ,

[0083] ,

[0084] S424, Calculate Earth Height :

[0085] ,

[0086] ,

[0087] Finally, the number was obtained One goal WGS-84 geodetic coordinates ( , , This gives us the latitude, longitude, and altitude.

[0088] The technical solution provided by this invention has the following technical effects compared with the prior art:

[0089] I. Significantly reduced hardware costs: Only one dual-light pod with laser rangefinding function is needed in the drone formation (configured on the main control drone), and the remaining cooperating drones are equipped with data link communication equipment, reducing the overall hardware cost of the system by about 60% to 75%.

[0090] II. Achieving high-precision positioning of multiple targets: for targets directly measured by laser. The positioning error is better than 2m (ENU synthesis, 90th percentile). The positioning error for assumed targets of the same size is about 41-60m on average under the current noise level, which can meet the mission accuracy requirements of UAV swarm management.

[0091] III. Globally Optimal Task Allocation: The Hungarian algorithm guarantees the minimization of the total flight distance of the formation, reducing the total cost by an average of 15% to 30% compared to the proximity principle.

[0092] IV. Simple engineering implementation and good real-time performance: The core of the algorithm consists of matrix operations and linear programming, with low computational load, and can run in real time on an embedded flight control computer, meeting the rapid response requirements of mission-oriented UAVs.

[0093] V. High scalability: The method described in this invention is applicable to a general scenario where N UAVs target M targets. By expanding the dimensions of the cost matrix, it can be directly adapted to different formation sizes. Attached Figure Description

[0094] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0095] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0096] Figure 1 This is an overall flowchart of a multi-UAV cooperative localization and target allocation method according to a certain embodiment of the present invention;

[0097] Figure 2 This is a coordinate system transformation diagram of a multi-UAV cooperative localization and target allocation method according to a certain embodiment of the present invention;

[0098] Figure 3 This is a schematic diagram illustrating the principle of distance calculation based on the assumption of equal dimensions in a certain embodiment of the present invention;

[0099] Figure 4 This is a schematic diagram of the target allocation cost matrix in a certain embodiment of the present invention;

[0100] Figure 5 This is a schematic diagram of the Hungarian algorithm in a certain embodiment of the present invention;

[0101] Figure 6 This is a Monte Carlo simulation positioning error analysis diagram in a certain embodiment of the present invention. Detailed Implementation

[0102] To better understand the above-mentioned objectives, features, and advantages of the present invention, the solutions of the present invention will be further described below. It should be noted that, unless otherwise specified, the embodiments of the present invention and the features thereof can be combined with each other.

[0103] Many specific details are set forth in the following description in order to provide a full understanding of the invention, but the invention may also be practiced in other ways different from those described herein; obviously, the embodiments in the specification are only some embodiments of the invention, and not all embodiments.

[0104] The specific embodiments of the present invention will now be described in detail with reference to the accompanying drawings.

[0105] In one embodiment, such as Figure 1 As shown, a multi-UAV cooperative localization and target allocation method is disclosed, including the following steps:

[0106] S1. System Initialization and Role Setting: Assume the total number of drones in the drone formation is N, and M targets need to be assigned. One drone in the formation is designated as the master drone, and the rest are designated as cooperative drones. The master drone is equipped with a dual-light pod with laser rangefinding function, which is used for target positioning and task assignment. The cooperative drones are equipped with data link communication equipment, which is used to receive broadcast information.

[0107] S2. The main control drone selects a reference target within its formation's field of view. Perform laser ranging to obtain the distance between the main control UAV and the reference target. radial distance between Simultaneously, it collects data including reference targets through its dual-light pod. The current frame image of the dual-light pod and other targets within the formation's field of view is used to record the roll angle output by the pod attitude sensor at the moment of laser ranging. Pitch angle Yaw angle And the GPS location coordinates of the main control drone ( , , ), to obtain the reference target Three-dimensional coordinate vector in the ENU coordinate system Its sub-steps are:

[0108] S21. The unit direction vector of the pod's optical axis in the camera coordinate system is:

[0109] ;

[0110] S22, Roll angle collected in real time by the pod attitude sensor Pitch angle and yaw angle Construct the pod attitude rotation matrix R according to the ZYX Euler angle order, and transform the camera coordinate system vector to the ENU coordinate system to obtain:

[0111] ,

[0112] The basic rotation matrices are:

[0113] ,

[0114] ,

[0115] ,

[0116] The transformation relationships between S23, camera coordinate system, ENU coordinate system, ECEF coordinate system and WGS-84 geodetic coordinate system are as follows: Figure 2As shown. Taking the current position of the main control UAV as the origin, the three-dimensional coordinate vector of the reference target in the ENU coordinate system is calculated. for:

[0117] ,

[0118] in, Here is the attitude rotation matrix. Let be the unit direction vector of the pod's optical axis in the camera coordinate system. The radial distance between the master-controlled UAV and the reference target. The form is [ , , ] T , To reference the eastward offset of the target relative to the main control UAV, To reference the northward offset of the target relative to the main control UAV, This is the azimuth offset of the reference target relative to the main control UAV.

[0119] S3. In the current frame image, the pixel bounding boxes of each target are obtained using a target detection algorithm, and a reference target is set. The area of ​​the pixel bounding box is , No. One goal The area of ​​the pixel bounding box is Then refer to the target Corresponding pixel size and the pixel size of the other targets They are respectively:

[0120] ,

[0121] ,

[0122] Based on the pinhole camera model, the imaging size of the target in the current frame image. Compared with the actual physical size of the target and target distance The following proportional relationship exists between them:

[0123] ,

[0124] in The focal length of the pinhole camera;

[0125] Then, refer to the target The imaging sizes of the remaining targets are as follows:

[0126] ,

[0127] ,

[0128] like Figure 3 As shown, in the same frame image, the reference target With other targets The ratio of the image size to the distance is equal to the ratio of the image size to the distance. Assume all targets have the same physical size, and In this case, we get:

[0129] ,

[0130] Then the main control drone and the first One goal radial distance The estimation formula is:

[0131] ,

[0132] in, , and Reference targets The bounding box's pixel width and height; For the first One goal The pixel size in the current frame image. , and The first One goal The bounding box's pixel width and height;

[0133] based on , obtained the One goal The three-dimensional coordinate vector in the ENU coordinate system is:

[0134] ,

[0135] in, The dual-light pod of the main control drone is aligned with the first One goal The unit direction vector of the camera coordinate system at that time. Through the first One goal R is the pod attitude rotation matrix corresponding to the current frame image, calculated by inversely using the pixel coordinates and camera parameters in the current frame image.

[0136] S4, the first One goal The process involves converting a 3D coordinate vector in the ENU coordinate system to ECEF coordinates, and then converting the ECEF coordinates to WGS-84 geodetic coordinates. The sub-steps are as follows:

[0137] S41, based on the GPS location of the main control drone ( , , Let ENU be the origin, and convert it to ECEF coordinates. , , The ellipsoidal parameters for WGS-84 geodetic coordinates are as follows: semi-major axis reciprocal of flatness First eccentricity The formula for calculating the ECEF coordinates of the current position of the main control UAV is:

[0138] ,

[0139] in, ,

[0140] ,

[0141] ,

[0142] No. One goal The ECEF coordinates are obtained by superimposing the ENU offset on the ECEF coordinates of the current position of the main control UAV:

[0143] ,

[0144] in, For the transformation matrix,

[0145] ,

[0146] S42, by the One goal The calculation of ECEF coordinates into WGS-84 geodetic coordinates uses a fixed-point iteration method, and its sub-steps are as follows:

[0147] S421. Calculate geodetic longitude :

[0148] ,

[0149] S422, Calculate the equatorial projected distance :

[0150] ,

[0151] S423, Iterative calculation of geodetic latitude The initial value of the iteration is set to Iterate and update according to the following formula until the difference between two adjacent iterations is less than 1. radian:

[0152] ,

[0153] ,

[0154] S424, Calculate Earth Height :

[0155] ,

[0156] ,

[0157] Finally, the number was obtained One goal WGS-84 geodetic coordinates ( , , This gives us the latitude, longitude, and altitude.

[0158] S5, will Targets are assigned to For a drone, the sub-steps are as follows:

[0159] S51. Calculation of cost matrix elements:

[0160] Cost matrix elements Indicates the first A drone flew to the The Euclidean distance cost for each target, where... , In a specific embodiment, there are four drones and four targets, i.e., N=4 and M=4. Figure 4 As shown, a 4×4 cost matrix is ​​calculated based on the ECEF coordinates of each UAV and the target. for:

[0161] ,

[0162] in, For the first The current ECEF coordinates of the drone are obtained and reported in real time by each cooperating drone via GPS, and then aggregated to the main control drone via data link. Let J be the ECEF coordinates of the j-th target, which are calculated by steps S2 to S4.

[0163] S52. Objective Function and Constraints:

[0164] With minimizing the total flight distance of the formation as the objective function, the formula is:

[0165] ,

[0166] in, To assign decision variables, Indicates the target Assigned to drones The constraints are:

[0167] ,

[0168] ,

[0169] ;

[0170] S53, such as Figure 5 As shown, the Hungarian algorithm is used to process the cost matrix. The solution process involves the following sub-steps:

[0171] S531, the cost matrix Subtract the minimum value of each row from the array to ensure that each row contains at least one zero element.

[0172] S532, The cost matrix after processing S531 Subtract the minimum value from each column so that each column has at least one zero element;

[0173] S533. Find the set of independent zero elements, that is, elements that are not in the same row but in the same column. If N independent zeros are found, the optimal allocation is obtained.

[0174] S534. If there are fewer than N independent zeros, cover all zero elements with the minimum number of straight lines, update the matrix, that is, subtract the minimum uncovered value from the uncovered elements, add back the double-covered elements, and repeat step S533 until N independent zeros are found.

[0175] The Hungarian algorithm outputs the optimal allocation matrix. ,in, Indicates the target Optimal allocation to drones The optimal total cost is:

[0176] ;

[0177] In a specific embodiment, the optimal allocation matrix is ​​output using the Hungarian algorithm, and the solution process is as follows: Figure 5 As shown, the final optimal total cost is 325 meters.

[0178] S6. The master drone sends a broadcast data packet containing the target allocation information corresponding to each cooperating drone to all members of the formation via a one-way broadcast through a data link. The broadcast data packet includes the target number. Target latitude WGS-84 Target WGS-84 longitude Target Earth High and the corresponding drone number assignment After receiving the broadcast, each coordinating drone independently plans and executes its flight mission according to the assigned WGS-84 geodetic coordinates; the coordinating drones do not need to reply for confirmation, and the master drone assumes the broadcast was successful.

[0179] pass Figure 6 It can be concluded that: reference target Direct laser ranging yielded a positioning error of only 1.04m, significantly better than target estimation based on pixel ratio. Errors in other non-reference targets primarily stemmed from the accumulation of errors related to the equal-size assumption, pixel noise propagation, and attitude noise.

[0180] The above description is merely a specific embodiment of the present invention, enabling those skilled in the art to understand or implement the present invention. Although detailed descriptions have been provided with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments, and they should all be covered within the protection scope of the claims.

Claims

1. A method for multi-UAV cooperative localization and target allocation, characterized in that, Includes the following steps: S1. System Initialization and Role Setting: Assume the total number of drones in the drone formation is N, and M targets need to be assigned. One drone in the formation is designated as the master drone, and the rest are designated as cooperative drones. The master drone is equipped with a dual-light pod with laser rangefinding function, which is used for target positioning and task assignment. The cooperative drones are equipped with data link communication equipment, which is used to receive broadcast information. S2. The main control drone selects a reference target within its formation's field of view. Perform laser ranging to obtain the distance between the main control UAV and the reference target. radial distance between Simultaneously, it collects data including reference targets through its dual-light pod. The current frame image of the dual-light pod and other targets within the formation's field of view is used to record the roll angle output by the pod attitude sensor at the moment of laser ranging. Pitch angle Yaw angle And the GPS location coordinates of the main control drone ( , , ), to obtain the reference target Three-dimensional coordinate vector in the ENU coordinate system ; S3. In the current frame image, the pixel bounding boxes of each target are obtained using a target detection algorithm, and a reference target is set. The area of ​​the pixel bounding box is , No. One goal The area of ​​the pixel bounding box is Then refer to the target Corresponding pixel size and the pixel size of the other targets They are respectively: ， ， Based on the pinhole camera model, the imaging size of the target in the current frame image. Compared with the actual physical size of the target and target distance The following proportional relationship exists between them: ， in The focal length of the pinhole camera; Then, refer to the target The imaging sizes of the remaining targets are as follows: ， ， Assuming all targets have the same physical size, and In this case, we get: ， Then the main control drone and the first One goal radial distance The estimation formula is: ， in, , and Reference targets The bounding box's pixel width and height; For the first One goal The pixel size in the current frame image. , and The first One goal The bounding box's pixel width and height; based on , obtained the One goal The three-dimensional coordinate vector in the ENU coordinate system is: ， in, The dual-light pod of the main control drone is aligned with the first One goal The unit direction vector of the camera coordinate system at that time. Through the first One goal R is the pod attitude rotation matrix corresponding to the current frame image, calculated by inversely using the pixel coordinates and camera parameters in the current frame image. S4, the first One goal The three-dimensional coordinate vectors in the ENU coordinate system are converted to ECEF coordinates, and then the ECEF coordinates are converted to WGS-84 geodetic coordinates. S5, will Targets are assigned to For a drone, the sub-steps are as follows: S51. Calculation of cost matrix elements: Cost matrix elements Indicates the first A drone flew to the The Euclidean distance cost for each target, where... , , Calculated using the following formula: ， in, For the first The current ECEF coordinates of the drone are obtained and reported in real time by each cooperating drone via GPS, and then aggregated to the main control drone via data link. Let J be the ECEF coordinates of the j-th target, which are calculated by steps S2 to S4. S52. Objective Function and Constraints: With minimizing the total flight distance of the formation as the objective function, the formula is: ， in, To assign decision variables, Indicates the target Assigned to drones The constraints are: ， ， ； S53. Solve using the Hungarian algorithm. The sub-steps are as follows: S531, the cost matrix Subtract the minimum value of each row from the array to ensure that each row contains at least one zero element. S532, The cost matrix after processing S531 Subtract the minimum value from each column so that each column has at least one zero element; S533. Find the set of independent zero elements, that is, elements that are not in the same row but in the same column. If N independent zeros are found, the optimal allocation is obtained. S534. If there are fewer than N independent zeros, cover all zero elements with the minimum number of straight lines, update the matrix, that is, subtract the minimum uncovered value from the uncovered elements, add back the double-covered elements, and repeat step S533 until N independent zeros are found. The Hungarian algorithm outputs the optimal allocation matrix. ,in, Indicates the target Optimal allocation to drones The optimal total cost is: ； S6. The master drone sends a broadcast data packet containing the target allocation information corresponding to each cooperating drone to all members of the formation via a one-way broadcast through a data link. The broadcast data packet includes the target number. Target latitude WGS-84 Target WGS-84 longitude Target Earth High and the corresponding drone number assignment After receiving the broadcast, each coordinating drone independently plans and executes its flight mission according to the assigned WGS-84 geodetic coordinates; the coordinating drones do not need to reply for confirmation, and the master drone assumes the broadcast was successful.

2. The multi-UAV cooperative localization and target allocation method according to claim 1, characterized in that, The sub-steps of step S2 are: S21. The unit direction vector of the pod's optical axis in the camera coordinate system is: ； S22, Roll angle collected in real time by the pod attitude sensor Pitch angle and yaw angle Construct the pod attitude rotation matrix R according to the ZYX Euler angle order, and transform the camera coordinate system vector to the ENU coordinate system to obtain: ， The basic rotation matrices are: ， ， ， S23. Using the current position of the main control UAV as the origin, calculate the three-dimensional coordinate vector of the reference target in the ENU coordinate system. for: ， in, Here is the attitude rotation matrix. Let be the unit direction vector of the pod's optical axis in the camera coordinate system. The radial distance between the master-controlled UAV and the reference target. The form is [ , , ] T , To reference the eastward offset of the target relative to the main control UAV, To reference the northward offset of the target relative to the main control UAV, This is the azimuth offset of the reference target relative to the main control UAV.

3. The multi-UAV cooperative localization and target allocation method according to claim 1, characterized in that, The sub-steps of step S4 are as follows: S41, based on the GPS location of the main control drone ( , , Let ENU be the origin, and convert it to ECEF coordinates. , , The ellipsoidal parameters for WGS-84 geodetic coordinates are as follows: semi-major axis reciprocal of flatness First eccentricity The formula for calculating the ECEF coordinates of the current position of the main control UAV is: ， in, , ， ， No. One goal The ECEF coordinates are obtained by superimposing the ENU offset on the ECEF coordinates of the current position of the main control UAV: ， in, For the transformation matrix, ， S42, by the One goal The calculation of ECEF coordinates into WGS-84 geodetic coordinates uses a fixed-point iteration method, and its sub-steps are as follows: S421. Calculate geodetic longitude : ， S422, Calculate the equatorial projected distance : ， S423, Iterative calculation of geodetic latitude The initial value of the iteration is set to Iterate and update according to the following formula until the difference between two adjacent iterations is less than 1. radian: ， ， S424, Calculate Earth Height : ， ， Finally, the number was obtained One goal WGS-84 geodetic coordinates ( , , This gives us the latitude, longitude, and altitude.

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