Seaborne distributed unmanned aerial vehicle monitoring system based on adaptive adjustment

Abstract

The invention relates to the technical field of unmanned aerial vehicle monitoring systems, and provides a maritime distributed unmanned aerial vehicle monitoring system based on adaptive adjustment, which comprises a maritime monitoring task management terminal, an unmanned aerial vehicle control terminal, an unmanned aerial vehicle base station terminal, a monitoring process analysis terminal and an adaptive adjustment terminal, the maritime monitoring task management terminal is used for receiving and managing maritime monitoring tasks; the unmanned aerial vehicle control terminal is used for controlling the unmanned aerial vehicle according to the marine monitoring task; the unmanned aerial vehicle base station terminal is used for parking and overhauling the unmanned aerial vehicle; the monitoring process analysis terminal is used for acquiring monitoring information from the unmanned aerial vehicle and analyzing the monitoring information to generate monitoring analysis information; the adaptive adjustment terminal is used for generating adaptive adjustment information for the unmanned aerial vehicle executing the task according to the monitoring analysis information; the adaptive adjustment information is used for driving the unmanned aerial vehicle control terminal to adjust and control the unmanned aerial vehicle executing the task. The method has the effect of improving the monitoring efficiency of the unmanned aerial vehicle for monitoring the offshore area by the system.

Description

Technical Field

[0001] The present invention relates to the technical field of unmanned aerial vehicle (UAV) monitoring systems, and particularly to an adaptive-adjustment-based marine distributed UAV monitoring system. Background Art

[0002] The UAV monitoring network system is a comprehensive network system designed to use UAVs for monitoring, data collection, and transmission. This system can be widely applied in fields such as marine monitoring, agricultural monitoring, urban management, and environmental protection. The marine UAV monitoring network system is a comprehensive monitoring system specifically designed for the marine environment, using UAVs to perform real-time monitoring, data collection, and transmission of sea areas. This system is mainly used for tasks such as marine safety, environmental monitoring, resource management, and search and rescue.

[0003] Many UAV monitoring network systems have been developed. After a large amount of retrieval and reference, it is found that the existing UAV monitoring network systems are those disclosed in, for example, CN111290425A, CN106814752A, CN112995894A, EP4095637A1, US10716292B1, and JP2019040321A. These UAV monitoring network systems generally include: a monitoring task management terminal, a UAV control terminal, and a UAV data analysis terminal. The monitoring task management terminal is used to manage and issue UAV monitoring tasks. The UAV control terminal is used to control the UAV to the corresponding monitoring area to perform monitoring tasks according to the UAV monitoring tasks. The UAV data analysis terminal is used to analyze the video data captured by the UAV during the monitoring tasks and output analysis information. Due to the relatively single monitoring method of the above UAV monitoring network systems, it is not conducive to monitoring large areas, and more time is required to perform tasks, resulting in the defect of reduced UAV monitoring efficiency. Summary of the Invention

[0004] The object of the present invention is to propose an adaptive-adjustment-based marine distributed UAV monitoring system in view of the deficiencies of the above UAV monitoring network systems.

[0005] The present invention adopts the following technical solutions:

[0006] An offshore distributed UAV monitoring system based on adaptive adjustment, comprising an offshore monitoring task management terminal, a UAV control terminal, a UAV base station terminal, a monitoring process analysis terminal and an adaptive adjustment terminal; the offshore monitoring task management terminal is used for receiving and managing offshore monitoring tasks; the UAV control terminal is used for controlling the UAV according to the offshore monitoring tasks; the UAV base station terminal is used for parking and maintaining the UAV; the monitoring process analysis terminal is used for obtaining and analyzing the monitoring information from the UAV to generate monitoring analysis information; the adaptive adjustment terminal is used for generating adaptive adjustment information for the UAV performing tasks according to the monitoring analysis information; the adaptive adjustment information is used to drive the UAV control terminal to adjust and control the UAV performing tasks;

[0007] The offshore monitoring task management terminal includes a monitoring task receiving module, a task fitness analysis module and a monitoring task distribution module; the monitoring task receiving module is used for receiving all the monitoring tasks input by the administrator; the task fitness analysis module is used for calculating the task fitness between the monitoring tasks and all the UAVs; the monitoring task distribution module is used for distributing the monitoring tasks to the corresponding UAVs according to the task fitness.

[0008] Optionally, the UAV control terminal includes a task execution control module, an emergency control module and an adjustment control module; the task execution control module is used for controlling the corresponding UAV to fly to the corresponding monitoring area to perform monitoring operations according to the monitoring tasks from the monitoring task distribution module; the emergency control module is used for performing emergency control on the UAV performing tasks; the adjustment control module is used for adjusting and controlling the UAV performing tasks according to the adaptive adjustment information.

[0009] Optionally, the monitoring process analysis terminal includes a monitoring area adjustment analysis module, a monitoring information analysis module, an emergency recall analysis module and a monitoring analysis information generation module; the monitoring area adjustment analysis module is used for calculating the monitoring area adjustment index of the corresponding UAV's monitoring area according to the monitoring object density parameter in the monitoring information such as the task level of the monitoring task and the climate parameter in the weather information; the monitoring information analysis module is used for recording and analyzing the monitoring information to generate monitoring live information; the emergency recall analysis module is used for calculating the recall index according to the status information of the UAV, the climate parameter in the weather information and the task level of the monitoring task; the monitoring analysis information generation module is used for packing and sorting the monitoring area adjustment index, the monitoring live information and the recall index into the corresponding monitoring analysis information.

[0010] Optionally, the adaptive adjustment terminal includes a monitoring area adjustment information generation module, an emergency recall information generation module, an adaptive adjustment information integration module, and an information sending module; the monitoring area adjustment information generation module is configured to generate corresponding monitoring area adjustment information according to the monitoring area adjustment index; the emergency recall information generation module is configured to generate corresponding emergency recall information according to the recall index; the adaptive adjustment information integration module is configured to integrate the monitoring area adjustment information and the emergency recall information into corresponding adaptive adjustment information; the information sending module is configured to send the adaptive adjustment information to the drone control terminal.

[0011] Optionally, the task adaptability analysis module includes a monitoring task information reading sub-module, a drone information reading sub-module, and a task adaptability calculation sub-module; the monitoring task information reading sub-module is configured to read the monitoring task information of all monitoring tasks; the monitoring task information includes task content, task route, task area, and task level; the drone information reading sub-module is configured to read the airframe information of all drones in the drone base terminal; the airframe information includes aircraft age, executed tasks, power parameters, and maintenance records; the task adaptability calculation sub-module is configured to calculate the respective task adaptabilities of the monitoring tasks for different drones according to the monitoring task information and the airframe information.

[0012] Optionally, the monitoring area adjustment analysis module includes a monitoring density score calculation sub-module, a task level score calculation sub-module, a meteorological condition score calculation sub-module, and a monitoring area adjustment index calculation sub-module; the monitoring density score calculation sub-module is configured to calculate the monitoring density score according to the monitoring object density parameter; the task level score calculation sub-module is configured to calculate the task level score according to the task level; the meteorological condition score calculation sub-module is configured to calculate the meteorological condition score according to the weather information; the monitoring area adjustment index calculation sub-module is configured to calculate the monitoring area adjustment index according to the monitoring density score, the task level score, and the meteorological condition score.

[0013] A method for monitoring marine distributed drones based on adaptive adjustment, which is applied to a marine distributed drone monitoring system as described above. The method for monitoring marine distributed drones based on adaptive adjustment includes:

[0014] S1, receiving and managing marine monitoring tasks;

[0015] S2, controlling the drones according to the marine monitoring tasks;

[0016] S3, obtaining and analyzing the monitoring information from the drones to generate monitoring analysis information;

[0017] S4, generating adaptive adjustment information for the drones executing tasks according to the monitoring analysis information.

[0018] The beneficial effects achieved by the present invention are as follows:

[0019] 1. The settings of the maritime monitoring task management terminal, the UAV control terminal, the UAV base station terminal, the monitoring process analysis terminal, and the adaptive adjustment terminal realize the multi-in-one UAV maritime monitoring function through the management, distribution, execution of monitoring tasks, and the adaptive adjustment of the UAV monitoring process, which is conducive to enriching the monitoring methods of the system, improving the monitoring accuracy and quality of the system for sea areas, and thus conducive to improving the UAV monitoring efficiency of the system for maritime areas;

[0020] 2. The settings of the monitoring task receiving module, the task adaptability analysis module, and the monitoring task distribution module improve the accuracy of task distribution by deepening the management and distribution of all monitoring tasks, so that the corresponding UAVs can complete the corresponding monitoring tasks more accurately and better, and thus conducive to improving the UAV monitoring efficiency of the system for maritime areas;

[0021] 3. The settings of the task execution control module, the emergency control module, and the adjustment control module are conducive to improving the accuracy of UAV control by independently implementing the three control functions of task execution control, emergency control, and adjustment control, so that the corresponding monitoring tasks can be completed more smoothly, accurately, and efficiently, and thus conducive to improving the UAV monitoring efficiency of the system for maritime areas;

[0022] 4. The settings of the monitoring area adjustment analysis module, the monitoring information analysis module, the emergency recall analysis module, and the monitoring analysis information generation module further enrich the analysis functions of the system through the monitoring area adjustment analysis, the monitoring information analysis, and the emergency recall analysis, making the monitoring area adjustment index, the emergency recall information, and the adaptive adjustment information more accurate, and thus conducive to improving the UAV monitoring efficiency of the system for maritime areas;

[0023] 5. The settings of the monitoring task information reading sub-module, the UAV information reading sub-module, and the task adaptability calculation sub-module, combined with the task adaptability calculation algorithm, calculate the task adaptabilities of different UAVs for monitoring tasks through the monitoring task information and the airframe information, improve the accuracy and calculation efficiency of the task adaptability, and further conducive to improving the accuracy and efficiency of the monitoring task distribution process, and thus conducive to further improving the UAV monitoring efficiency of the system for maritime areas;

[0024] 6. The settings of the monitoring density score calculation sub-module, task level score calculation sub-module, meteorological condition score calculation sub-module, and monitoring area adjustment index calculation sub-module cooperate with the monitoring density score algorithm, task level score algorithm, meteorological condition score algorithm, and monitoring area adjustment index algorithm. Calculate the monitoring density score through the monitoring object density parameter, calculate the task level score through the task level, calculate the meteorological condition score through the weather information, and calculate the monitoring area adjustment index through the monitoring density score, task level score, and meteorological condition score. This improves the accuracy and calculation efficiency of the monitoring area adjustment index, thereby improving the accuracy of the monitoring area adjustment information and facilitating a significant improvement in the UAV monitoring efficiency of the system for monitoring the maritime area.

[0025] 7. The settings of the status score calculation sub-module, climate risk score calculation sub-module, task urgency score calculation sub-module, and recall index calculation sub-module cooperate with the status score algorithm, climate risk score algorithm, task urgency score algorithm, and recall index algorithm. Calculate the status score through the UAV's status information, calculate the climate risk score of the area monitored by the UAV through the climate information, calculate the task urgency score through the task content and task level, and integrate the status score, climate risk score, and task urgency score into the corresponding recall index. This improves the accuracy and calculation efficiency of the recall index, thereby facilitating an improvement in the accuracy of the emergency recall information and the UAV monitoring efficiency of the system for monitoring the maritime area.

[0026] To enable a further understanding of the features and technical content of the present invention, please refer to the following detailed description of the present invention and the attached drawings. However, the provided drawings are only for reference and illustration, and are not used to limit the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 It is a schematic diagram of the overall structure of the present invention;

[0028] Figure 2 It is a schematic diagram of the structure of the task adaptability analysis module in the present invention;

[0029] Figure 3 It is a schematic diagram of the structure of the monitoring area adjustment analysis module in the present invention;

[0030] Figure 4 It is a schematic diagram of the method flow of a method for maritime distributed UAV monitoring based on adaptive adjustment in the present invention;

[0031] Figure 5 It is a schematic diagram of the structure of the emergency recall analysis module in another embodiment of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0032] The following are specific embodiments to illustrate the implementation manners of the present invention. Those skilled in the art can understand the advantages and effects of the present invention from the content disclosed in this specification. The present invention can be implemented or applied through other different specific embodiments, and various details in this specification can also be modified and changed based on different viewpoints and applications without departing from the spirit of the present invention. Additionally, the drawings of the present invention are only for simple schematic illustration and are not drawn according to actual sizes, which is hereby stated in advance. The following embodiments will further detail the related technical content of the present invention, but the disclosed content is not used to limit the protection scope of the present invention.

[0033] Embodiment 1: This embodiment provides a maritime distributed UAV monitoring system based on adaptive adjustment. As shown in Figure 1 , a maritime distributed UAV monitoring system based on adaptive adjustment includes a maritime monitoring task management terminal, a UAV control terminal, a UAV base station terminal, a monitoring process analysis terminal, and an adaptive adjustment terminal; the maritime monitoring task management terminal is used to receive and manage maritime monitoring tasks; the UAV control terminal is used to control the UAV according to the maritime monitoring tasks; the UAV base station terminal is used to park and maintain the UAV; the monitoring process analysis terminal is used to obtain the monitoring information from the UAV and perform analysis to generate monitoring analysis information; the adaptive adjustment terminal is used to generate adaptive adjustment information for the UAV performing tasks according to the monitoring analysis information; the adaptive adjustment information is used to drive the UAV control terminal to perform adjustment control on the UAV performing tasks;

[0034] The maritime monitoring task management terminal includes a monitoring task receiving module, a task fitness analysis module, and a monitoring task distribution module; the monitoring task receiving module is used to receive all the monitoring tasks input by the administrator; the task fitness analysis module is used to calculate the task fitness between the monitoring tasks and all the UAVs; the monitoring task distribution module is used to distribute the monitoring tasks to the corresponding UAVs according to the task fitness.

[0035] Optionally, the UAV control terminal includes a task execution control module, an emergency control module, and an adjustment control module; the task execution control module is used to control the corresponding UAV to fly to the corresponding monitoring area to perform monitoring operations according to the monitoring tasks from the monitoring task distribution module; the emergency control module is used to perform emergency control on the UAV performing tasks; the adjustment control module is used to perform adjustment control on the UAV performing tasks according to the adaptive adjustment information.

[0036] Optionally, the monitoring process analysis terminal includes a monitoring area adjustment analysis module, a monitoring information analysis module, an emergency recall analysis module, and a monitoring analysis information generation module; the monitoring area adjustment analysis module is used to calculate the monitoring area adjustment index of the corresponding UAV's monitoring area according to the monitoring object density parameter in the monitoring information such as the task level of the monitoring task and the climate parameter in the weather information; the monitoring information analysis module is used to record and analyze the monitoring information to generate monitoring live information; the emergency recall analysis module is used to calculate the recall index according to the UAV's status information, the climate parameter in the weather information, and the task level of the monitoring task; the monitoring analysis information generation module is used to package and organize the monitoring area adjustment index, the monitoring live information, and the recall index into the corresponding monitoring analysis information.

[0037] Optionally, the adaptive adjustment terminal includes a monitoring area adjustment information generation module, an emergency recall information generation module, an adaptive adjustment information integration module, and an information sending module; the monitoring area adjustment information generation module is used to generate the corresponding monitoring area adjustment information according to the monitoring area adjustment index; the emergency recall information generation module is used to generate the corresponding emergency recall information according to the recall index; the adaptive adjustment information integration module is used to integrate the monitoring area adjustment information and the emergency recall information into the corresponding adaptive adjustment information; the information sending module is used to send the adaptive adjustment information to the UAV control terminal.

[0038] Optionally, in combination with Figure 2 As shown, the task fitness analysis module includes a monitoring task information reading sub-module, a UAV information reading sub-module, and a task fitness calculation sub-module; the monitoring task information reading sub-module is used to read the monitoring task information of all monitoring tasks; the monitoring task information includes task content, task route, task area, and task level; the UAV information reading sub-module is used to read the body information of all UAVs in the UAV base station terminal; the body information includes aircraft age, executed tasks, power parameters, and maintenance records; the task fitness calculation sub-module is used to calculate the task fitness of the monitoring task for different UAVs according to the monitoring task information and the body information.

[0039] Specifically, when the task fitness calculation sub-module works, the following formula is satisfied:

[0040]

[0041]

[0042] Among them, E i represents the task fitness of the current task and the i-th UAV; CM i , RM i , AMi and PM i respectively represent the matching scores of the current task with the task content, task route, task area, and task level of the i-th drone;

[0043] f(U b ) represents a score selection function based on the comparison between the current task content and the b-th historical task content in the historical task records of the i-th drone; B represents the total number of historical tasks with the same task content as the current task among all the historical tasks of the i-th drone; U b represents the comparison between the current task content and the b-th historical task content in the historical task records of the i-th drone; U b =0 indicates that the comparison between the current task content and the b-th historical task content in the historical task records of the i-th drone is different; U b =1 indicates that the comparison between the current task content and the b-th historical task content in the historical task records of the i-th drone is the same;

[0044] e 1i and e 2i respectively represent the remaining power and flight energy efficiency of the i-th drone; the flight energy efficiency refers to the total distance flown by the drone when it runs out of power; L represents the task route distance of the current task; overlap(S area , s areas ) represents the overlapping area between the task area of the current task and the historical flight area of the i-th drone; S area represents the task area of the current task; s areas represents the historical flight area of the i-th drone;

[0045] β1 and β2 respectively represent different score conversion coefficients, which are set by the administrator according to experience. The higher the current task level, the larger β1 and β2 are. For example, when the current task level is level 2, β1 and β2 are 1 and 1.5 respectively; when the current task level is level 3, β1 and β2 are 1.5 and 2 respectively; the task level of each task is preset by the administrator or the task publisher; Y i represents the age of the i-th drone; MAX age represents the maximum age among all drones; N i represents the number of repairs of the i-th drone; MAX n represents the maximum allowable maintenance total, which is set by the administrator according to experience; the monitoring task distribution module sends the current task to the drone with the highest task adaptability.

[0046] Optionally, combined with Figure 3As shown, the monitoring area adjustment and analysis module includes a monitoring density score calculation sub-module, a task level score calculation sub-module, a meteorological condition score calculation sub-module, and a monitoring area adjustment index calculation sub-module; the monitoring density score calculation sub-module is used to calculate the monitoring density score according to the monitoring object density parameter; the task level score calculation sub-module is used to calculate the task level score according to the task level; the meteorological condition score calculation sub-module is used to calculate the meteorological condition score according to the weather information; the monitoring area adjustment index calculation sub-module is used to calculate the monitoring area adjustment index according to the monitoring density score, the task level score, and the meteorological condition score.

[0047] Specifically, when the monitoring density score calculation sub-module, the task level score calculation sub-module, the meteorological condition score calculation sub-module, and the monitoring area adjustment index calculation sub-module are working, they respectively satisfy the following formulas:

[0048]

[0049] A I = w1×f(D1) + w2×f(D2) + w3×f(D3);

[0050] Among them, f(D1) represents the monitoring density score calculation function based on the monitoring density; D1 represents the monitoring density, that is, the ship density in the monitoring area, which can be but is not limited to: the number of ships per hectare of sea area; e represents the natural constant e; the larger D1 is, the smaller the monitoring density score is; f(D2) represents the task level score calculation function based on the task level; D2 represents the task level, and the task level of each task is preset by the administrator, and the administrator can be but is not limited to setting it according to the area and flight duration of the task; the larger D2 is, the smaller the task level score is; f(D3) represents the meteorological condition score calculation function based on the meteorological condition; D3 represents the meteorological condition of the corresponding monitoring area; W ref and W current respectively represent the reference wind speed and the average wind speed on the day of the corresponding monitoring area, and the reference wind speed is set by the administrator according to experience; V ref and V current respectively represent the reference visibility and the average visibility on the day of the corresponding monitoring area, and the reference visibility is set by the administrator according to experience; A I represents the monitoring area adjustment index; w1, w2, and w3 respectively represent different score weight coefficients, all set by the administrator according to experience, w1 + w2 + w3 = 1, generally, w1 = 0.4, w2 = 0.4, w3 = 0.2; when A I < α1, the monitoring area adjustment information generation module generates monitoring area adjustment information for indicating to shrink the current UAV monitoring area. In order to stabilize the situation of the monitored sea area, the system can be but is not limited to: taking measures such as dispatching additional UAVs; when AI When it is > α1, the monitoring area adjustment information generation module generates monitoring area adjustment information for indicating an enlarged current UAV monitoring area; the change amounts for both reduction and enlargement are 20% of the original monitoring area; when A I = α1, the monitoring area adjustment information generation module generates monitoring area adjustment information for indicating maintaining the current UAV monitoring area; α1 represents an adjustment threshold, which is set by the administrator according to experience.

[0051] A method for maritime distributed UAV monitoring based on adaptive adjustment is applied to a maritime distributed UAV monitoring system as described above, and in combination with Figure 4 as shown, the method for maritime distributed UAV monitoring based on adaptive adjustment includes:

[0052] S1, receiving and managing maritime monitoring tasks;

[0053] S2, controlling the UAV according to the maritime monitoring tasks;

[0054] S3, obtaining and analyzing the monitoring information from the UAV to generate monitoring analysis information;

[0055] S4, generating adaptive adjustment information for the UAVs performing tasks according to the monitoring analysis information.

[0056] In summary, the settings of the above system achieve the multi-in-one UAV maritime monitoring function through the management, distribution, execution of monitoring tasks and the adaptive adjustment of the UAV monitoring process, which is conducive to enriching the monitoring methods of the system and improving the monitoring accuracy and quality of the system for sea areas; by deepening the management and distribution of all monitoring tasks, the accuracy of task distribution is improved, so that the corresponding UAVs can complete the corresponding monitoring tasks more accurately and better; by independently implementing the three control functions of task execution control, emergency control and adjustment control, it is conducive to improving the accuracy of UAV control, so as to complete the corresponding monitoring tasks more smoothly, accurately and efficiently; by further enriching the analysis functions of the system through monitoring area adjustment analysis, monitoring information analysis and emergency recall analysis, the monitoring area adjustment index, emergency recall information and adaptive adjustment information are made more accurate; by calculating the task adaptation degrees of different UAVs for monitoring tasks through monitoring task information and airframe information, the accuracy and calculation efficiency of task adaptation degrees are improved, which is conducive to improving the accuracy and efficiency of the monitoring task distribution process; by calculating the monitoring density score through the monitoring object density parameter, calculating the task level score through the task level, calculating the meteorological condition score through the weather information, and calculating the monitoring area adjustment index through the monitoring density score, task level score and meteorological condition score, the accuracy and calculation efficiency of the monitoring area adjustment index are improved, thereby improving the accuracy of the monitoring area adjustment information, which is conducive to greatly improving the UAV monitoring efficiency of the system for monitoring sea areas.

[0057] Embodiment 2: This embodiment includes all the contents of Embodiment 1 and provides a maritime distributed UAV monitoring system based on adaptive adjustment. In this embodiment, due to the particularity of maritime monitoring tasks, in the case of a UAV crashing into the sea, it is difficult to salvage the UAV and the salvage cost is relatively high. Moreover, due to the seawater, even if the salvage is successful, the monitored data is easily damaged. Therefore, the purpose of designing the emergency recall analysis module is to balance the choice between completing the task and emergency recall, so that the UAV can complete the task as much as possible and be urgently recalled when there is a risk of the UAV crashing into the sea.

[0058] Combined with Figure 5 As shown, the emergency recall analysis module includes a status score calculation sub-module, a climate risk score calculation sub-module, a task emergency score calculation sub-module and a recall index calculation sub-module. The status score calculation sub-module is used to calculate the status score according to the status information of the UAV; the climate risk score calculation sub-module is used to calculate the climate risk score of the area monitored by the UAV according to the climate information; the task emergency score calculation sub-module is used to calculate the task emergency score according to the task content and task level; the recall index calculation sub-module is used to integrate the status score, climate risk score and task emergency score into the corresponding recall index.

[0059] When the state score calculation sub-module, climate risk score calculation sub-module, task urgency score calculation sub-module, and recall index calculation sub-module are working, they respectively satisfy the following equations:

[0060]

[0061] η = lg(100 - R + 1);

[0062]

[0063] Z I = g1 × f(H1) + g2 × f(H2) - g3 × f(H3);

[0064] Among them, f(H1) represents the state score calculation function based on the remaining power of the drone; H1 represents the real-time remaining power of the drone; η represents the remaining power adjustment coefficient; R represents the maximum capacity of the battery corresponding to the drone, and the maximum capacity is 100 when the battery leaves the factory, and it becomes smaller as the number of years and usage times of the battery increase; f(H2) represents the climate risk score calculation function based on the climate situation; H2 represents the climate situation in the monitoring area of the drone; W ref and W current respectively represent the reference wind speed and average wind speed on the day in the corresponding monitoring area; V ref and V current respectively represent the reference visibility and average visibility on the day in the corresponding monitoring area; J ref and J current respectively represent the reference precipitation and average precipitation on the day in the corresponding monitoring area; J ref is set by the administrator according to experience; f(H3) represents the task urgency score calculation function based on the task urgency; H3 represents the task urgency; represents the average monitoring duration when each drone in the monitoring area corresponding to the current task performs the monitoring task; D2 represents the task level; Z I represents the recall index of the corresponding drone during the task execution; g1, g2, and g3 respectively represent different index value conversion coefficients, which are all set by the administrator according to experience. Generally, g1 = 0.5, g2 = 0.5, g3 = 1; when Z I ≥ α2, the emergency recall information generation module generates emergency recall information indicating that the drone needs to be recalled; α2 represents the recall threshold, which is set by the administrator according to experience.

[0065] In summary, the setting of the status score calculation sub-module, climate risk score calculation sub-module, task urgency score calculation sub-module, and recall index calculation sub-module, in conjunction with the status score algorithm, climate risk score algorithm, task urgency score algorithm, and recall index algorithm, calculates the status score through the status information of the UAV, calculates the climate risk score of the area monitored by the UAV through the climate information, calculates the task urgency score through the task content and task level, and integrates the status score, climate risk score, and task urgency score into the corresponding recall index, thereby improving the accuracy and calculation efficiency of the recall index, which is conducive to improving the accuracy of the emergency recall information and the UAV monitoring efficiency of the system for monitoring the maritime area.

[0066] The content disclosed above is only the preferred feasible embodiment of the present invention, and does not limit the protection scope of the present invention. Therefore, all equivalent technical changes made by using the content of the specification and drawings of the present invention are included in the protection scope of the present invention. In addition, the elements therein can be updated with the development of technology.

Claims

1. A distributed marine drone monitoring system based on adaptive regulation, characterized in that: It includes a maritime monitoring task management terminal, a UAV control terminal, a UAV base station terminal, a monitoring process analysis terminal and an adaptive adjustment terminal; the maritime monitoring task management terminal is used to receive and manage maritime monitoring tasks; the UAV control terminal is used to control the UAV according to the maritime monitoring tasks; The drone base station terminal is used to park and repair drones; The monitoring process analysis terminal is used to obtain and analyze monitoring information from the drone to generate monitoring analysis information; The adaptive adjustment terminal is used to generate adaptive adjustment information for the UAV performing the task according to the monitoring and analysis information; The adaptive adjustment information is used to drive the UAV control terminal to adjust and control the UAV performing the mission; The maritime monitoring task management terminal includes a monitoring task receiving module, a task fitness analysis module and a monitoring task distribution module; the monitoring task receiving module is used to receive all monitoring tasks input by an administrator; the task fitness analysis module is used to calculate the task fitness of the monitoring task and all unmanned aerial vehicles; the monitoring task distribution module is used to distribute monitoring tasks to corresponding unmanned aerial vehicles according to the task fitness.

2. The adaptively regulated distributed unmanned aerial vehicle monitoring system at sea according to claim 1, characterized in that: The UAV control terminal includes a task execution control module, an emergency control module and an adjustment control module; the task execution control module is used to control the corresponding UAV to fly to the corresponding monitoring area to perform monitoring operations according to the monitoring task from the monitoring task distribution module; the emergency control module is used to perform emergency control on the UAV performing the task; The regulation control module is used to regulate and control the UAV performing the mission according to the adaptive regulation information.

3. The adaptively regulated distributed unmanned aerial vehicle monitoring system at sea according to claim 2, characterized in that: The monitoring process analysis terminal includes a monitoring area adjustment analysis module, a monitoring information analysis module, an emergency recall analysis module and a monitoring analysis information generation module; the monitoring area adjustment analysis module is used to calculate the monitoring area adjustment index of the monitoring area of ​​the corresponding drone according to the monitoring object density parameter in the monitoring information such as the task of the monitoring task and the climate parameter in the weather information; the monitoring information analysis module is used to record and analyze the monitoring information to generate real-time monitoring information; The emergency recall analysis module is used to calculate the recall index based on the status information of the drone, the climate parameters in the weather information and the task level of the monitoring task; the monitoring analysis information generation module is used to package the monitoring area adjustment index, the monitoring real-time information and the recall index into corresponding monitoring analysis information.

4. The adaptively regulated distributed unmanned aerial vehicle monitoring system at sea according to claim 3, characterized in that: The adaptive adjustment terminal includes a monitoring area adjustment information generation module, an emergency recall information generation module, an adaptive adjustment information integration module and an information sending module; the monitoring area adjustment information generation module is used to generate corresponding monitoring area adjustment information according to the monitoring area adjustment index; The emergency recall information generation module is used to generate corresponding emergency recall information according to the recall index; The adaptive adjustment information integration module is used to integrate the monitoring area adjustment information and the emergency recall information into corresponding adaptive adjustment information; the information sending module is used to send the adaptive adjustment information to the UAV control terminal.

5. The adaptively regulated distributed unmanned aerial vehicle monitoring system at sea according to claim 4, characterized in that: The task adaptability analysis module includes a monitoring task information reading submodule, a drone information reading submodule and a task adaptability calculation submodule; the monitoring task information reading submodule is used to read the monitoring task information of all monitoring tasks; the monitoring task information includes task content, task route, task area and task level; the drone information reading submodule is used to read the body information of all drones in the drone base station terminal; the body information includes age, executed tasks, power parameters, and maintenance records; the task adaptability calculation submodule is used to calculate the task adaptability of each monitoring task for different drones based on the monitoring task information and body information.

6. The adaptively regulated distributed unmanned aerial vehicle monitoring system at sea according to claim 5, characterized in that: The monitoring area adjustment analysis module includes a monitoring density score calculation submodule, a task level score calculation submodule, a meteorological condition score calculation submodule and a monitoring area adjustment index calculation submodule; the monitoring density score calculation submodule is used to calculate the monitoring density score according to the density parameter of the monitored object; the task level score calculation submodule is used to calculate the task level score according to the task level; the meteorological condition score calculation submodule is used to calculate the meteorological condition score according to weather information; the monitoring area adjustment index calculation submodule is used to calculate the monitoring area adjustment index according to the monitoring density score, the task level score and the meteorological condition score.

7. A method for monitoring a distributed unmanned aerial vehicle at sea based on adaptive adjustment, applied to a distributed unmanned aerial vehicle monitoring system at sea based on adaptive adjustment as claimed in claim 6, characterized in that: The method for monitoring distributed unmanned aerial vehicles at sea based on adaptive adjustment includes: S1, receives and manages maritime surveillance missions; S2, controls the UAV according to the maritime monitoring mission; S3, obtaining and analyzing monitoring information from the drone to generate monitoring analysis information; S4, generating adaptive adjustment information for the UAV performing the mission according to the monitoring and analysis information.

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