An isomorphic unmanned aerial vehicle global situation information sharing method and system

Abstract

The application discloses a kind of isomorphic unmanned plane global situation information sharing method and system, the method includes: constructing grid dynamic situation map, and initialization;Through situation map, planning region information to be searched and target information are issued, and situation information is simultaneously updated to other unmanned planes in cluster;Unmanned plane carries out target characteristic matching, and updates situation area in situation map;According to the updated situation map, the flight path of cluster unmanned plane is planned, and unmanned plane is executed tracking task and regional search task is distributed;During the task execution of unmanned plane, distributed situation map target is added, updated and deleted.The application realizes global real-time co-construction and sharing of situation information, avoids the perception delay caused by situation information forwarding in centralized architecture, realizes the more rapid perception ability of unmanned plane cluster to scene situation, and has the function of assisting unmanned plane cluster to realize autonomous rapid formation and autonomous task decision in task area.

Description

TECHNICAL FIELD

[0001] The application belongs to the field of three-dimensional situation co-construction and sharing, and particularly relates to a homogeneous unmanned aerial vehicle global situation information sharing method and system. BACKGROUND

[0002] With the rapid development of unmanned technology in recent years, the number of unmanned aerial vehicle clusters is rapidly expanding. In the long term, the rapid formation and action decision-making ability of large-scale unmanned aerial vehicle clusters in complex environments is the key to realizing the autonomous planning, autonomous formation and autonomous navigation ability of unmanned aerial vehicle clusters in complex environments. Real-time sharing of situation information of unmanned aerial vehicle clusters is an important factor for improving the high autonomy and high mobility of unmanned aerial vehicle clusters. A fast and effective situation information sharing method can effectively help the unmanned aerial vehicle cluster to realize rapid formation and action decision-making, so as to better complete the target task.

[0003] In the task of unmanned aerial vehicle cluster formation, with the expansion of the cluster detection range and the advancement of the task process, the global three-dimensional situation information will evolve rapidly. The unmanned aerial vehicle cluster needs to perceive the situation information change in real time and synchronize the dynamic information to all unmanned aerial vehicles in the cluster. The existing situation information sharing method usually needs a ground terminal as an information relay. After the ground terminal is offline or disconnected, the unmanned aerial vehicle cluster loses the ability of situation sharing. The realization of data reception and transmission synchronization between unmanned aerial vehicle clusters can effectively solve the problem of centralized data storage. In addition, in the large-scale unmanned aerial vehicle cluster construction scene, due to the large number of unmanned aerial vehicle clusters, connecting the ground terminal simultaneously by all cluster unmanned aerial vehicles results in large data synchronization and transmission overhead. Moreover, due to the scene restriction, there are often wireless signal interference situations, which further increases the difficulty of global situation information sharing. SUMMARY

[0004] The purpose of the present application is to overcome the deficiencies of the current centralized data sharing method of unmanned aerial vehicle clusters and the real-time and reliability of data sharing, and to provide a homogeneous unmanned aerial vehicle global situation information sharing method and system. The method and system comprehensively consider terrain data, target data, search area information and unmanned aerial vehicle dynamic data, establish a situation map of real-time updated situation awareness information of unmanned aerial vehicle clusters, so as to better evaluate the current scene situation information, improve the real-time planning and dynamic decision-making ability of unmanned aerial vehicle clusters, and realize accurate capture of scene situation.

[0005] The technical solution for realizing the purpose of the present application is as follows:

[0006] A homogeneous unmanned aerial vehicle global situation information sharing method, comprising:

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

[0008] S102, the planning area information to be searched and target information are issued through the situation map, and the situation information is updated synchronously to other unmanned aerial vehicles in the cluster;

[0009] S103, the unmanned aerial vehicle performs target characteristic matching, and updates the situation area in the situation map;

[0010] S104, the flight path of the cluster unmanned aerial vehicle is planned according to the situation map updated in step 103, and the unmanned aerial vehicle is assigned to perform a tracking task and a region search task;

[0011] S105, during the execution of the task by the unmanned aerial vehicle, the target is added, updated and deleted in the distributed situation map.

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

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

[0014] Further, in S103, the unmanned aerial vehicle matches the target pitch angle, target yaw angle and target situation awareness radius in the target characteristic table according to the target type, constructs a pyramid-shaped target awareness area T a with the target point as the vertex, and updates the situation map.

[0015] Further, the conical situation area T a is:

[0016]

[0017] Wherein, (B, L, H) represents the longitude and latitude and altitude of the target, r represents the situation awareness radius, θ represents the target yaw angle, represents the target pitch angle, T a represents the set of four vertices of the pyramid-shaped area.

[0018] Further, the target addition in step S105 specifically includes:

[0019] Step 5.1, the longitude and latitude coordinates (B, L) of the geographical location of the UAV and the central meridian longitude L0 are obtained by Gauss direct transformation to obtain the Gauss plane coordinates (x, y), and the height H of the UAV is introduced to form a three-dimensional coordinate space:

[0020]

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

[0022] Step 5.2, according to the photoelectric pod pixel (p x , p y ), the camera focal length f and the space coordinates (x c , y c , z c ) of the center point of the UAV, the two-dimensional space coordinates (x' c , y c ') corresponding to each pixel point on the image are determined:

[0023]

[0024] wherein c x , c y represent the offset of the image on the horizontal and vertical coordinate axes;

[0025] Step 5.3, according to the two-dimensional space coordinates (x' c , y c ') corresponding to each pixel point, the camera center coordinates are obtained to determine the actual position coordinates (x', y') in the Gauss plane corresponding to the pixel point:

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

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

[0028] Step 5.4, the actual position Gauss coordinates are obtained by Gauss inverse transformation to obtain the longitude and latitude coordinates (B', L') of the enemy target, and the target type is added to the situation map, and the situation area in the cluster UAV situation map is updated repeatedly.

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

[0030]

[0031] wherein B f is the bottom latitude calculated according to 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, real-time reading of known tracking target information in the situation map, and matching the nearest situation target according to the secant formula:

[0034]

[0035] wherein (B1, L1) represents the longitude and latitude information of the unmanned aerial vehicle, (B i , L i ) represents the longitude and latitude of the target stored in the situation map, and r represents the radius of the earth;

[0036] Step 6.2, obtaining the target longitude and latitude coordinates (B', L') according to step S105, obtaining the updated target sensing area T a ' according to step S103, replacing the target information in the situation map with the updated coordinates and situation area, and synchronizing to the cluster unmanned aerial vehicle.

[0037] Further, the situation map target deletion in step S105 specifically includes: during the tracking of the target, the unmanned aerial vehicle dynamically tracks the target in real time, after the tracking task is completed, the small cluster head unmanned aerial vehicle plans a path to the end unmanned aerial vehicle target point based on the situation map, obtains the target coordinate point according to the target information in the situation map, obtains the target area image using the light point pod, 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 homogeneous unmanned aerial vehicle global situation information sharing system, comprising:

[0039] A dynamic situation map construction unit for constructing a grid-based dynamic situation map and initializing;

[0040] An interaction unit for issuing planning information of a to-be-searched area and target information through the situation map, simultaneously updating the situation information to other unmanned aerial vehicles in the cluster, and matching the target characteristics by the unmanned aerial vehicle and updating the situation area in the situation map;

[0041] A task allocation unit for planning the flight path of the cluster unmanned aerial vehicle according to the updated situation map, and allocating the unmanned aerial vehicle to execute the tracking task and the area search task.

[0042] The situation map processing unit adds, updates and deletes the situation map target during the execution of the task of the unmanned aerial vehicle.

[0043] Compared with the prior art, the method has the advantages that: the method is based on the situation information sharing in the cooperative task of the unmanned aerial vehicle cluster, constructs a decentralized situation map in the unmanned aerial vehicle cluster, and integrates the situation target adding, updating and deleting functions, so that the unmanned aerial vehicle cluster can obtain the latest situation information in real time through the situation map; the method overcomes the shortcoming of the traditional method that needs to construct a data communication center on the ground as a relay, realizes the co-construction and sharing of the global situation information of the unmanned aerial vehicle cluster, has high anti-interference capability, can effectively help the unmanned aerial vehicle cluster to avoid dangerous areas and reduce the risk of encountering complex obstacles and collisions according to the real-time situation information provided by the situation map, and provides accurate situation intelligence to support the autonomous planning of the unmanned aerial vehicle cluster; the isomorphic unmanned aerial vehicle global situation information sharing method can provide fast, real-time and effective auxiliary decision-making data for the autonomous game and autonomous navigation of the unmanned aerial vehicle cluster. BRIEF DESCRIPTION OF DRAWINGS

[0044] Figure 1 The specific embodiment flowchart of the isomorphic unmanned aerial vehicle global situation information sharing method based on the situation map of the present application is shown. DETAILED DESCRIPTION

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

[0046] The present application proposes an isomorphic unmanned aerial vehicle global situation information sharing method, which constructs a situation map based on a rasterized three-dimensional map to realize centralized management of situation information, realizes global sharing of scene situation based on the situation map, and realizes real-time updating of the detected target and the search area and construction of a decentralized data updating mode on the basis of traditional situation awareness, and can be used to assist the unmanned aerial vehicle cluster to realize autonomous formation and autonomous decision-making in the task airspace. Figure 1 As shown in the figure, the specific steps of the isomorphic unmanned aerial vehicle global situation information sharing method based on the situation map of the present application include:

[0047] S101: Situation map construction.

[0048] First, according to the actual search area and target information situation initialization situation map grid coordinate table and target characteristics table, grid coordinate table storage according to the combat demand to m long and wide grid map, grid coordinate table with grid ID as the primary key, storage grid number, grid center point longitude coordinate, grid center point dimension coordinate and grid center point elevation information, target characteristics table with target type as the primary key, storage target situation level, target pitch angle, target deflection angle and target situation awareness radius.

[0049] S102: Situation information is issued.

[0050] In the task planning stage, the ground terminal issues planning search area information and the found target information through the situation map, and the situation map synchronously updates the situation information to other unmanned aerial vehicles in the cluster. The search area information includes the three-dimensional vertex coordinates of the region, the region type, the region ID, the region priority and the region group number information. The found target information includes the target type, the target ID, the target longitude and latitude, the target height and the target group number information.

[0051] S103: Situation information processing.

[0052] After the global situation information is issued to the unmanned aerial vehicle, the unmanned aerial vehicle matches the target characteristics target pitch angle, target deflection angle and target situation awareness radius according to the target type in the situation map, constructs a pyramid target awareness region T a with the target point as the vertex, and updates the situation map:

[0053]

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

[0055] S104: Situation task planning.

[0056] The unmanned aerial vehicle cluster distributes and implements the unmanned aerial vehicle cluster formation to execute the task according to the target and situation region information stored in the situation map, plans the flight path of the cluster unmanned aerial vehicle according to the updated situation map in step 103, and dispatches the unmanned aerial vehicle to execute the tracking task and the region search task

[0057] S105: Situation target addition.

[0058] During the flight to the arrival stage, the optical-electric pod of the cluster unmanned aerial vehicle captures the ground image in real time, identifies the target coordinates and the target type according to the captured ground image, adds the target to the situation map, and the situation map synchronously synchronizes the newly added situation target to all unmanned aerial vehicles in the cluster.

[0059] Based on the geographical longitude and latitude coordinates of the location of the unmanned aerial vehicle, the imaging information of the photoelectric pod carried by the unmanned aerial vehicle is converted into target longitude and latitude information through Gaussian transformation to complete the situation target addition, specifically including:

[0060] Firstly, the longitude and latitude coordinates (B, L) of the geographical location of the unmanned aerial vehicle and the central meridian longitude L0 are obtained through Gaussian positive transformation to obtain the Gaussian plane coordinates (x, y), and the height H of the unmanned aerial vehicle is introduced to form a three-dimensional coordinate space:

[0061]

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

[0063] Then, according to the photoelectric pod pixel (p x , p y ), the camera focal length f and the space coordinates (x c , y c , z c ) of the center point of the unmanned aerial vehicle, the two-dimensional space coordinates corresponding to each pixel point on the image are determined:

[0064]

[0065] Wherein c x , c y represent the offset of the image on the horizontal and vertical coordinate axes;

[0066] Then, according to the pixel point coordinates and the camera center coordinates, the coordinates of the actual position in the Gaussian plane corresponding to the pixel point are calculated:

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

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

[0069] Finally, the actual position Gaussian coordinates are obtained through Gaussian inverse transformation to obtain the longitude and latitude coordinates (B', L') of the enemy target and the identified target type, and the situation map is added to the situation map, and the situation area in the cluster unmanned aerial vehicle situation map is updated repeatedly:

[0070]

[0071] wherein B f is the bottom latitude calculated reversely according to the meridian arc length, t f = tan(B f ), all are constants.

[0072] S106: Situation target update.

[0073] In the process of implementing the tracking task, the unmanned aerial vehicle dynamically tracks the strike 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] Firstly, the known enemy target information in the situation map is read, and the nearest enemy target is matched according to the secant formula:

[0075]

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

[0077] Then, the target longitude and latitude coordinates (B', L') are obtained according to the method in S105, the updated target situation area T a ' is obtained according to the method in S103, the target information in the situation map is replaced with the updated coordinates and situation area, and is synchronized to the cluster unmanned aerial vehicle.

[0078] S107: Situation target deletion.

[0079] In the process of implementing the tracking target, the unmanned aerial vehicle dynamically tracks the target in real time, and after the tracking task is completed, the tracking and identification effect of the end unmanned aerial vehicle is actively evaluated by the small cluster head unmanned aerial vehicle, and the situation target information in the situation map is deleted. The specific method is that the small cluster head unmanned aerial vehicle plans a path to the target point of the end unmanned aerial vehicle based on the situation map, obtains the target coordinate point according to the target information in the situation map, uses the light point pod to obtain the target area image, and uses the two-order target detection algorithm based on classification R-CNN series to identify the target. If the target is identified, the situation target information in the situation map is retained, and if the target is not identified, the situation target information and the situation area information are deleted from the situation map.

[0080] The method of the present application realizes centralized management of situation information by constructing a situation map on the basis of a gridded three-dimensional map, and the unmanned aerial vehicle can realize rapid perception and processing of scene situation changes through the situation map, and specifically includes distributed target adding, target deleting and target updating functions; the situation map proposed by the present application realizes real-time provision of situation awareness information of each unit in the task area to the entire unmanned aerial vehicle cluster by using distributed data transmission, realizes global real-time co-construction and sharing of situation information, avoids the perception delay caused by the forwarding of situation information in the centralized architecture, realizes more rapid perception ability of the unmanned aerial vehicle cluster to the scene situation, and has the functions of assisting the unmanned aerial vehicle cluster to realize autonomous rapid formation and autonomous task decision in the task area.

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

[0082] A dynamic situation map construction unit is configured to construct a gridded dynamic situation map and initialize;

[0083] An interaction unit is configured to issue planning to-be-searched region information and target information through the situation map, and simultaneously update the situation information to other unmanned aerial vehicles in the cluster, the unmanned aerial vehicle performs target characteristic matching, and updates the situation region in the situation map;

[0084] A task allocation unit is configured to plan a flight path of the unmanned aerial vehicle cluster according to the updated situation map, and allocate the unmanned aerial vehicle to perform a tracking task and a region search task;

[0085] A situation map processing unit is configured to perform target adding, updating and deleting of the situation map during the execution of the task by the unmanned aerial vehicle.

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

[0087] The above specific embodiments can be adjusted in different ways by those skilled in the art without departing from the principles and purposes of the present application, the protection scope of the present application is subject to the claims and is not limited by the above specific embodiments, and each implementation scheme within the scope is subject to the constraints of the present application.

Claims

1. A method for sharing global situational information of homogeneous unmanned aerial vehicles (UAVs), characterized in that, include: S101, Construct and initialize a gridded dynamic situation map; S102 distributes information on the planned search area and target information through the situation map, and simultaneously updates the situation information to other drones in the cluster. S103, the UAV performs target characteristic matching and updates the situation area in the situation map; S104, Based on the situation map updated in step 103, plan the flight path of the cluster of UAVs and assign UAVs to perform tracking tasks and area search tasks. S105, during the UAV's mission, performs the addition, updating, and deletion of targets on a distributed situational awareness map.

2. The method for sharing global situational information of isomorphic unmanned aerial vehicles according to claim 1, characterized in that, 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 the length and width according to the scene accuracy requirements. It uses the grid ID as the primary key and stores the grid number, the longitude coordinates of the grid center point, the latitude 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 and stores the target situation information, including the situation level, the target pitch angle, the target yaw angle, and the target situation awareness radius.

3. The method for sharing global situational information of isomorphic unmanned aerial vehicles according to claim 1, characterized in that, The search area information includes the three-dimensional vertex coordinates of the search area, the area type, the area ID, the area priority, and the area group number. The target information includes the target type, the target ID, the target latitude and longitude, the target height, and the target group number.

4. The method for sharing global situational information of isomorphic UAVs according to claim 2, characterized in that, In S103, the UAV matches the target pitch angle, target yaw angle, and target situational 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 situational information of isomorphic UAVs according to claim 4, characterized in that, The pyramidal target sensing area T a for: Where (B,L,H) represent the target's latitude, longitude, and altitude, r represents the situational awareness radius, and θ represents the target's deflection angle. Indicates the target pitch angle.

6. The method for sharing global situational information of isomorphic unmanned aerial vehicles according to claim 1, characterized in that, Step S105, adding targets to the situation map, specifically includes: Step 5.1: Obtain Gaussian plane coordinates (x, y) from the latitude and longitude coordinates (B, L) of the UAV's geographical location and the central meridian longitude L0 through a Gaussian forward transform, and then incorporate these coordinates into the UAV's altitude H to construct a three-dimensional coordinate space. Where, l = L - L0, Let η be the radius of curvature, t = tan(B), and η be the tan(B). 2 =e 2 cos 2 (B), a is the major semi-axis of the ellipsoid of revolution, b is the minor semi-axis, and X is the arc length of the meridian; Step 5.2, based on the UAV's optoelectronic pod pixel count (p x ,p y ), the camera focal length f and the spatial coordinates (x, y) of the drone's center point c ,y c ,z c ), determine the two-dimensional spatial coordinates (x') of each pixel in the image. c ,y c '): Where c x c y This represents the offset of the image on the horizontal and vertical axes; Step 5.3, based on the two-dimensional spatial coordinates (x') of each pixel. c ,y c The coordinates (x', y') of the actual position of a pixel in the Gaussian plane are obtained from the camera center coordinates. x'=x+x c 'p x y'=y+y c 'p y Step 5.4: Obtain the latitude and longitude coordinates (B', L') of the enemy target by inverse Gaussian transformation of the actual position Gaussian coordinates. At the same time, add the target type to the situation map and repeat step S103 to update the situation area in the swarm UAV situation map.

7. The method for sharing global situational information of isomorphic unmanned aerial vehicles according to claim 6, characterized in that, The latitude and longitude coordinates (B) ' ,L ' )for: Among them, B f The latitude of the base point is calculated based on the arc length of the meridian. t f =tan(B f All of them are constants.

8. The method for sharing global situational information of isomorphic unmanned aerial vehicles according to claim 6, characterized in that, The situation map update in step S105 specifically includes: Step 6.1: Read the known tracking target information from the situation map in real time, and match the nearest situation target according to the semi-versus formula: Where (B1,L1) represents the latitude and longitude information of the UAV, (B i ,L i ) represents the target's latitude and longitude stored in the situation map, and r represents the Earth's radius; Step 6.2: Obtain the target's latitude and longitude coordinates (B', L') according to step S105, and obtain the updated target sensing area T according to step S103. a The system replaces the target information in the situation map with the updated coordinates and situation area, and synchronizes it to the cluster of drones.

9. The method for sharing global situational information of isomorphic unmanned aerial vehicles according to claim 1, characterized in that, The specific steps of deleting the target from the situation map in step S105 include: 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 target point of the end UAV based on the situation map, obtains the target coordinates based on 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 global situational information sharing system for isomorphic unmanned aerial vehicles (UAVs) implementing the method of any one of claims 1-9, characterized in that, include: The dynamic situation map construction unit is used to construct and initialize a rasterized dynamic situation map. The interactive unit distributes information on the planned search area and target information through the situation map, and simultaneously updates the situation information to other drones in the cluster. The drones then perform target characteristic matching and update the situation area in the situation map. The task allocation unit plans the flight path of the swarm of UAVs based on the updated situation map and assigns UAVs to perform tracking tasks and area search tasks. The situation map processing unit adds, updates, and deletes targets on the situation map during the UAV's mission.

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