Method and system for sharing global situation information of isomorphic unmanned aerial vehicle

Abstract

The invention discloses an isomorphic unmanned aerial vehicle global situation information sharing method and system, and the method comprises the steps: constructing a rasterized dynamic situation map, and initializing the rasterized dynamic situation map; issuing and planning to-be-searched area information and target information through the situation map, and synchronously updating the situation information to other unmanned aerial vehicles in the cluster; the unmanned aerial vehicle performs target characteristic matching and updates a situation area in the situation map; planning a cluster unmanned aerial vehicle flight path according to the updated situation map, and allocating the unmanned aerial vehicles to execute a tracking task and a region search task; and in the task execution process of the unmanned aerial vehicle, distributed situation map targets are added, updated and deleted. According to the invention, global real-time co-construction and sharing of situation information are realized, perception delay caused by forwarding of the situation information in a centralized architecture is avoided, the ability of the unmanned aerial vehicle cluster to perceive the scene situation more rapidly is realized, and the unmanned aerial vehicle cluster is assisted to realize autonomous rapid formation and autonomous task decision in a task area.

Description

Technical Field

[0001] The present invention belongs to the field of three-dimensional situation co-construction and sharing, and specifically provides a method and system for sharing global situation information of homogeneous unmanned aerial vehicles. Background Art

[0002] With the rapid development of unmanned technology in recent years, the number of drone swarms has expanded rapidly. In the long run, the ability of large-scale drone swarms to quickly form and make action decisions in complex environments is the key to realizing the autonomous planning, autonomous formation and autonomous navigation capabilities of drone swarms in complex environments. Among them, the real-time sharing of drone swarm situation information is an important factor in improving the high autonomy and high mobility of drone swarms. Fast and effective situation information sharing methods can effectively help drone swarms to quickly form and make action decisions, thereby better completing target tasks.

[0003] In the UAV swarm formation mission, as the swarm detection range expands and the mission progresses, the global three-dimensional situation information will evolve rapidly. The UAV swarm needs to perceive the situation information changes in real time and synchronize the dynamic information to all UAVs in the swarm. Existing situation information sharing methods usually require ground terminals as information relays. When the ground terminal is disconnected or disconnected, the UAV swarm loses the situation sharing capability. Synchronizing the transmission and reception of data between UAV swarms can effectively solve the problem of centralized data storage. In addition, in the scenario of building large-scale UAV swarms, due to the large number of UAV swarms, all swarm UAVs are connected to the ground terminal at the same time, resulting in high data synchronization and transmission overhead, and due to scenario restrictions, there is often wireless signal interference, which further increases the difficulty of sharing global situation information. Summary of the invention

[0004] The purpose of the present invention is to overcome the shortcomings of the current centralized data sharing mode of drone clusters and the real-time and reliability of data sharing, and to provide a method and system for sharing global situation information of homogeneous drones, which comprehensively considers terrain data, target data, search area information and drone dynamic data, and establishes a situation map that updates the situation awareness information of drone clusters in real time, so as to better evaluate the current scene situation information, improve the real-time planning and dynamic decision-making capabilities of drone clusters, and realize accurate capture of scene situation.

[0005] The technical solution to achieve the purpose of the present invention is:

[0006] A method for sharing global situation information of homogeneous unmanned aerial vehicles, comprising:

[0007] S101, constructing a rasterized dynamic situation map and initializing it;

[0008] S102, sending the planned search area information and target information through the situation map, and synchronously updating the situation information to other drones in the cluster;

[0009] S103, the UAV performs target feature matching and updates the situation area in the situation map;

[0010] S104, planning the flight path of the cluster UAVs according to the situation map updated in step 103, and assigning UAVs to perform tracking tasks and area search tasks;

[0011] S105, while the UAV is executing the mission, the distributed situation map targets are added, updated and deleted.

[0012] Furthermore, the situation map is constructed based on a grid coordinate table and a target characteristic table. The grid coordinate table constructs a gridded scene map with meters as length and width according to the scene accuracy requirements, takes the grid ID as the primary key, and stores the grid number, grid center point longitude coordinates, grid center point dimensional coordinates and grid center point altitude information. The target characteristic table takes the target type as the primary key, and stores the target situation information, including situation level, target pitch angle, target deflection angle and target situation awareness radius.

[0013] Furthermore, the search area information includes three-dimensional vertex coordinates of the search area, area type, area ID, area priority and area group number information, and the target information includes target type, target ID, target longitude and latitude, target altitude and target group number information.

[0014] Furthermore, in S103, the UAV matches the target pitch angle, target deflection angle and target situation awareness radius in the target characteristic table according to the target type, and constructs a pyramidal target perception area T with the target point as the vertex. a , and update the situation map.

[0015] Furthermore, the cone-shaped potential region T a for:

[0016]

[0017] Where (B, L, H) represents the latitude, longitude and altitude of the target, r represents the situational awareness radius, and θ represents the target deflection angle. represents the target pitch angle, T a A set of four vertices representing a pyramid-shaped region.

[0018] Furthermore, the adding of the situation map target in step S105 specifically includes:

[0019] Step 5.1, the longitude and latitude coordinates (B, L) of the drone's geographic location and the longitude of the central meridian L0 are transformed into Gaussian plane coordinates (x, y) by Gaussian forward transformation, and the drone's height H is introduced to form a three-dimensional coordinate space:

[0020]

[0021] Where, l = L-L0, is the radius of curvature, t = tan(B), η 2 =e 2 cos 2 (B) a is the major semi-axis of the ellipsoid, b is the minor semi-axis, and X is the meridian arc length;

[0022] Step 5.2, according to the pixel of the UAV optoelectronic pod (p x ,p y ), the focal length of the camera f and the spatial coordinates of the center point of the drone (x c ,y c ,z c ), determine the two-dimensional space coordinates (x' c ,y c '):

[0023]

[0024] where c x 、c y Represents the offset of the image on the horizontal and vertical axes;

[0025] Step 5.3, according to the two-dimensional space coordinates (x' c ,y c '), the camera center coordinates are used to find the coordinates (x', y') of the actual position of the pixel point in the Gaussian plane:

[0026] x'=x+x c 'p x

[0027] y'=y+y c 'p y

[0028] Step 5.4, obtain the longitude and latitude coordinates (B', L') of the enemy target by inverse Gaussian transformation of the actual position Gaussian coordinates, add the target type to the situation map, and repeat step S103 to update the situation area in the swarm drone situation map.

[0029] Furthermore, the latitude and longitude coordinates (B', L') are:

[0030]

[0031] Among them, B f is the latitude of the nadir calculated from the meridian arc length, t f =tan(B f ) are all constants.

[0032] Further, the situation map updating in step S105 specifically includes:

[0033] Step 6.1, read the known tracking target information in the situation map in real time, and match the closest situation target according to the haversine formula:

[0034]

[0035] Among them, (B1, L1) represents the latitude and longitude information of the drone, (B i ,L i ) represents the target latitude and longitude stored in the situation map, and r represents the radius of the earth;

[0036] Step 6.2, according to step S105, obtain the target longitude and latitude coordinates (B', L'), and according to step S103, obtain the updated target perception area T a ', replace the target information in the situation map with the updated coordinates and situation area and synchronize them to the cluster drones.

[0037] Furthermore, the situation map target deletion in step S105 specifically includes: during the target tracking process, the UAV dynamically tracks the target in real time. After the tracking task is completed, the small cluster head UAV plans a path to the end UAV target point based on the situation map, obtains the target coordinate point according to the target information in the situation map, uses the light spot pod to obtain the target area image and uses the target detection algorithm to identify the target. If the target is identified, the situation target information in the situation map is retained. If the target is not identified, the situation target information is deleted from the situation map.

[0038] A global situation information sharing system for homogeneous unmanned aerial vehicles, comprising:

[0039] A dynamic situation map construction unit is used to construct a rasterized dynamic situation map and initialize it;

[0040] The interactive unit sends the planned search area information and target information through the situation map, and simultaneously updates the situation information to other drones in the cluster. The drones match the target characteristics and update the situation area in the situation map.

[0041] The task allocation unit plans the flight path of the cluster UAVs based on the updated situation map and allocates UAVs to perform tracking tasks and area search tasks;

[0042] The situation map processing unit adds, updates and deletes situation map targets while the UAV is performing its mission.

[0043] Compared with the prior art, the beneficial effects of the present invention are as follows: the method of the present invention takes the situation information sharing in the collaborative task of the drone cluster as the background, constructs a decentralized situation map in the drone cluster, integrates the situation target adding, updating and deleting functions, and ensures that the cluster drones can obtain the latest situation information in real time through the situation map; the method overcomes the disadvantage that the traditional method needs to build a data communication center on the ground side as a relay, realizes the co-construction and sharing of global situation information by the drone cluster, and has efficient anti-interference ability. At the same time, the real-time situation information provided by the situation map can effectively help the drone cluster avoid dangerous areas and reduce the risks of encountering complex obstacles and collisions, and at the same time provide accurate situation intelligence to support the drone cluster to carry out autonomous planning. The isomorphic drone global situation information sharing method can provide fast, real-time and effective auxiliary decision-making data for the drone cluster to realize autonomous game and autonomous navigation. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 The present invention is a flowchart of a specific implementation method of the global situation information sharing method of homogeneous UAVs based on situation maps. DETAILED DESCRIPTION

[0045] The specific implementation of the present invention is described below in conjunction with the accompanying drawings so that those skilled in the art can better understand the present invention. It should be noted that in the following description, when the detailed description of known functions and designs may dilute the main content of the present invention, these descriptions will be omitted here.

[0046] The present invention proposes a method for sharing global situation information of homogeneous UAVs, which constructs a situation map based on a rasterized three-dimensional map to realize centralized management of situation information, and the UAV cluster realizes global sharing of scene situation based on the situation map. On the basis of traditional situation awareness, the detection target and search area are updated in real time and a decentralized data update method is constructed. At the same time, it can be used to assist the UAV cluster in realizing autonomous formation and autonomous decision-making in the mission airspace; Figure 1 As shown, the specific steps of the method for sharing global situation information of homogeneous UAVs based on situation maps of the present invention include:

[0047] S101: Situation map construction.

[0048] First, the situation map grid coordinate table and target characteristic table are initialized according to the actual situation of the area to be searched and the target information. The grid coordinate table stores the rasterized map with length and width in meters according to combat requirements. The grid coordinate table uses the grid ID as the primary key to store the grid number, the longitude coordinates of the grid center point, the dimensional coordinates of the grid center point, and the altitude information of the grid center point. The target characteristic table uses the target type as the primary key to store the target situation level, target pitch angle, target deflection angle, and target situation awareness radius.

[0049] S102: Situation information is issued.

[0050] In the mission planning stage, the ground terminal sends the planned search area information and the identified target information through the situation map. At the same time, the situation map will synchronously update the situation information to other drones in the cluster. The search area information includes the three-dimensional vertex coordinates of the area, the area type, the area ID, the area priority and the area group number information. The identified target information includes the target type, target ID, target longitude and latitude, target altitude and target group number information.

[0051] S103: Situation information processing.

[0052] After the global situation information is sent to the UAV, the UAV matches the target characteristics (target pitch angle, target deflection angle, and target situation awareness radius) according to the target type in the situation map, and constructs a pyramid-shaped target perception area T with the target point as the vertex. a , and update the situation map:

[0053]

[0054] Where (B, L, H) represents the latitude, longitude and altitude of the target, r represents the target situation awareness radius, and θ represents the target deflection angle. represents the target pitch angle, T a Represents the set of four vertices of the pyramid-shaped target perception area.

[0055] S104: Situation mission planning.

[0056] The UAV cluster allocates the UAV cluster grouping execution task according to the target and situation area information stored in the situation map, plans the flight path of the cluster UAV according to the situation map updated in step 103, and dispatches the UAV to perform the tracking task and the area search task.

[0057] S105: Situation target added.

[0058] During the flight to arrival phase, the optoelectronic pod of the cluster drone captures ground images in real time, identifies target coordinates and target type based on the captured ground images, and adds the target to the situation map. The situation map then synchronizes the newly added situation targets to all drones in the cluster.

[0059] Based on the geographic longitude and latitude coordinates of the drone's location and the imaging information of the optoelectronic pod carried by the drone, the target longitude and latitude information is calculated through Gaussian transformation to complete the addition of situational targets, including:

[0060] First, the longitude and latitude coordinates (B, L) of the drone’s geographic location and the longitude of the central meridian L0 are transformed into Gaussian plane coordinates (x, y) through Gaussian forward transformation, and the drone’s height H is introduced to form a three-dimensional coordinate space:

[0061]

[0062] Where l = L-L0, is the radius of curvature, t = tan(B), η 2 =e 2 cos 2 (B), a is the major semi-axis of the ellipsoid, b is the minor semi-axis, and X is the meridian arc length;

[0063] Next, according to the pixel of the UAV optoelectronic pod (p x ,p y ), the focal length of the camera f and the spatial coordinates of the center point of the drone (x c ,y c ,z c ) Determine the two-dimensional space coordinates corresponding to each pixel point on the image:

[0064]

[0065] where c x ,c y Represents the offset of the image on the horizontal and vertical axes;

[0066] Then, based on the pixel coordinates and the camera center coordinates, the coordinates of the actual position of the pixel in the Gaussian plane are calculated:

[0067] x'=x+x c 'p x

[0068] y'=y+y c 'p y

[0069] Finally, the actual position Gaussian coordinates are transformed through the inverse Gaussian transform to obtain the longitude and latitude coordinates (B', L') of the enemy target and the identified target type, and added to the situation map, and step 3 is repeated to update the situation area in the swarm drone situation map:

[0070]

[0071] Among them, B f is the latitude of the base point calculated from the arc length of the meridian, t f =tan(B f ), are constants.

[0072] S106: Situation target update.

[0073] During the tracking mission, the drone dynamically tracks the target in real time, matches the target situation information according to the situation map, and updates the real-time target position and situation area to the situation map in real time:

[0074] First, read the known enemy target information in the situation map and match the nearest enemy target according to the haversine formula:

[0075]

[0076] Where (B1, L1) represents the latitude and longitude information of the drone, (B i ,L i ) represents the target latitude and longitude stored in the situation map, and r represents the radius of the earth;

[0077] Next, the target latitude and longitude coordinates (B', L') are obtained according to the method in S105, and the updated target situation area T is obtained according to the method in S103. a ', replace the target information in the situation map with the updated coordinates and situation area and synchronize them to the cluster drones.

[0078] S107: Situation target deletion.

[0079] During the target tracking process, the UAV dynamically tracks the target in real time. After the tracking task is completed, the small cluster head UAV is required to actively evaluate the tracking and identification effect of the end UAV and delete the situation target information in the situation map. The specific method is that the small cluster head UAV plans the path to the end UAV target point based on the situation map, obtains the target coordinate point according to the target information in the situation map, uses the light spot pod to obtain the target area image and uses the classification-based R-CNN series two-order target detection algorithm for target identification. If the target is identified, the situation target information in the situation map is retained. If the target is not identified, the situation target information and the situation area information are deleted from the situation map together.

[0080] The method of the present invention realizes centralized management of situation information by constructing a situation map based on a rasterized three-dimensional map. The unmanned aerial vehicle can realize rapid perception and processing of scene situation changes through the situation map, specifically including distributed target addition, target deletion and target update functions; the situation map proposed by the present invention utilizes distributed data transmission to provide the entire unmanned aerial vehicle cluster with situation awareness information of each unit in the mission area in real time, realizes global real-time co-construction and sharing of situation information, avoids perception delay caused by situation information forwarding in a centralized architecture, realizes the unmanned aerial vehicle cluster's faster perception capability of the scene situation, and has the ability to assist the unmanned aerial vehicle cluster in realizing autonomous rapid formation and autonomous task decision-making in the mission area.

[0081] A global situation information sharing system for homogeneous unmanned aerial vehicles, comprising:

[0082] A dynamic situation map construction unit is used to construct a rasterized dynamic situation map and initialize it;

[0083] The interactive unit sends the planned search area information and target information through the situation map, and simultaneously updates the situation information to other drones in the cluster. The drones match the target characteristics and update the situation area in the situation map.

[0084] The task allocation unit plans the flight path of the cluster UAVs based on the updated situation map and allocates UAVs to perform tracking tasks and area search tasks;

[0085] The situation map processing unit adds, updates and deletes situation map targets while the UAV is performing its mission.

[0086] The present invention innovatively constructs a global sharing method for three-dimensional situation information, and realizes global co-construction and sharing of situation information based on the situation map, so that the drone cluster can achieve more fine-grained control of scene situation information and realize autonomous formation optimization for faster scene changes.

[0087] The above-mentioned specific implementation can be partially adjusted in different ways by those skilled in the art without departing from the principle and purpose of the present invention. The protection scope of the present invention shall be based on the claims and shall not be limited by the above-mentioned specific implementation. Each implementation scheme within its scope shall be subject to the constraints of the present invention.

Claims

1. A method for sharing global situation information of homogeneous unmanned aerial vehicles, characterized in that: include: S101, constructing a rasterized dynamic situation map and initializing it; S102, sending the planned search area information and target information through the situation map, and synchronously updating the situation information to other drones in the cluster; S103, the UAV performs target feature matching and updates the situation area in the situation map; S104, planning the flight path of the cluster UAVs according to the situation map updated in step 103, and assigning UAVs to perform tracking tasks and area search tasks; S105, while the UAV is executing the mission, the distributed situation map targets are added, updated and deleted.

2. The method for sharing global situation information of homogeneous UAVs according to claim 1 is characterized in that: The situation map is constructed according to a grid coordinate table and a target characteristic table. The grid coordinate table constructs a gridded scene map with meters as length and width according to the scene accuracy requirements, takes the grid ID as the primary key, and stores the grid number, the longitude coordinates of the grid center point, the dimensional coordinates of the grid center point, and the altitude information of the grid center point. The target characteristic table takes the target type as the primary key, and stores the target situation information, including the situation level, the target pitch angle, the target deflection angle, and the target situation awareness radius.

3. The method for sharing global situation information of homogeneous UAVs according to claim 1 is characterized in that: The search area information includes the search area three-dimensional vertex coordinates, area type, area ID, area priority and area group number information, and the target information includes target type, target ID, target longitude and latitude, target altitude and target group number information.

4. The method for sharing global situation information of homogeneous UAVs according to claim 2 is characterized in that: In S103, the UAV matches the target pitch angle, target deflection angle and target situation awareness radius in the target characteristic table according to the target type, and constructs a pyramidal target perception area T with the target point as the vertex. a , and update the situation map.

5. The method for sharing global situation information of homogeneous unmanned aerial vehicles according to claim 4 is characterized in that: The cone potential area T a for: Where (B, L, H) represents the latitude, longitude and altitude of the target, r represents the situational awareness radius, and θ represents the target deflection angle. represents the target pitch angle, T a A set of four vertices representing a pyramid-shaped region.

6. The method for sharing global situation information of homogeneous UAVs according to claim 1, characterized in that: The adding of situation map target in step S105 specifically includes: Step 5.1, the longitude and latitude coordinates (B, L) of the drone's geographic location and the longitude of the central meridian L0 are transformed into Gaussian plane coordinates (x, y) by Gaussian forward transformation, and the drone's height H is introduced to form a three-dimensional coordinate space: Where, l = L-L0, is the radius of curvature, t = tan(B), η 2 =e 2 cos 2 (B) a is the major semi-axis of the ellipsoid, b is the minor semi-axis, and X is the meridian arc length; Step 5.2, according to the pixel of the UAV optoelectronic pod (p x ,p y ), the focal length of the camera f and the spatial coordinates of the center point of the drone (x c ,y c ,z c ), determine the two-dimensional space coordinates (x' c ,y c '): where c x 、c y Represents the offset of the image on the horizontal and vertical axes; Step 5.3, according to the two-dimensional space coordinates (x' c ,y c '), the camera center coordinates are used to find the coordinates (x', y') of the actual position of the pixel point in the Gaussian plane: x'=x+x c 'p x y'=y+y c 'p y Step 5.4, obtain the longitude and latitude coordinates (B', L') of the enemy target by inverse Gaussian transformation of the actual position Gaussian coordinates, add the target type to the situation map, and repeat step S103 to update the situation area in the swarm drone situation map.

7. The method for sharing global situation information of homogeneous UAVs according to claim 6 is characterized in that: The latitude and longitude coordinates (B', L') are: Among them, B f is the latitude of the nadir calculated from the meridian arc length, t f =tan(B f ) are all constants.

8. The method for sharing global situation information of homogeneous UAVs according to claim 6 is characterized in that: The situation map updating in step S105 specifically includes: Step 6.1, read the known tracking target information in the situation map in real time, and match the closest situation target according to the haversine formula: Among them, (V1,L1) represents the latitude and longitude information of the drone, (B i ,L i ) represents the target latitude and longitude stored in the situation map, and r represents the radius of the earth; Step 6.2, according to step S105, obtain the target longitude and latitude coordinates (B', L'), and according to step S103, obtain the updated target perception area T a ', replace the target information in the situation map with the updated coordinates and situation area and synchronize them to the cluster drones.

9. The method for sharing global situation information of homogeneous UAVs according to claim 1, characterized in that: The situation map target deletion in step S105 specifically includes: during the target tracking process, the UAV dynamically tracks the target in real time. After the tracking task is completed, the small cluster head UAV plans a path to the end UAV target point based on the situation map, obtains the target coordinate point according to the target information in the situation map, uses the light spot pod to obtain the target area image and uses the target detection algorithm to identify the target. If the target is identified, the situation target information in the situation map is retained. If the target is not identified, the situation target information is deleted from the situation map.

10. A homogeneous UAV global situation information sharing system implementing any of the methods described in claims 1-9, characterized in that: include: A dynamic situation map construction unit is used to construct a rasterized dynamic situation map and initialize it; The interactive unit sends the planned search area information and target information through the situation map, and simultaneously updates the situation information to other drones in the cluster. The drones match the target characteristics and update the situation area in the situation map. The task allocation unit plans the flight path of the cluster UAVs based on the updated situation map and allocates UAVs to perform tracking tasks and area search tasks; The situation map processing unit adds, updates and deletes situation map targets while the UAV is performing its mission.

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