Water surface platform and AUV communication method, system, program and device based on unmanned aerial vehicle relay and storage medium

Abstract

The invention relates to a method, a system, a program and equipment for communication between a water surface platform and an AUV (Autonomous Underwater Vehicle) based on an unmanned aerial vehicle relay and a storage medium, and belongs to the technical field of underwater communication and unmanned system collaboration. When the AUV needs to communicate, the unmanned aerial vehicle flies over an initial water area of the AUV to establish an initial communication link; an integrated communication benefit function value is calculated by measuring the original signal strength, and the function comprehensively evaluates the link benefit between the unmanned aerial vehicle and the AUV and the radio frequency link benefit between the unmanned aerial vehicle and the water surface platform; dynamically optimizing the hovering position of the unmanned aerial vehicle by adopting a gradient rising algorithm through generating test points in multiple directions, estimating the gradient and adaptively adjusting the step length so as to maximize the benefit function; and when the gradient modulus length, the position updating amount or the benefit improvement value is lower than a corresponding threshold value, determining convergence, and keeping the unmanned aerial vehicle at the optimal position for stable data relay. According to the method, the influence of sea condition fluctuation and earth curvature is effectively overcome, the reliability and stability of a communication link are remarkably improved, and the working radius of the AUV is expanded.

Description

Technical Field

[0001] This invention belongs to the field of underwater communication and unmanned system collaboration technology, specifically relating to a communication method, system, program, device and storage medium between a surface platform and an AUV based on UAV relay. Background Technology

[0002] The undulations of the sea surface waves can cause the AUV antenna to shake violently and may be submerged by the waves, resulting in drastic fluctuations in signal strength, momentary interruptions, and high bit error rates, making the communication link extremely unstable. Due to the curvature of the earth, a stable line-of-sight communication path cannot be maintained between surface ships and low-profile AUVs that are only floating on the surface, and the signal transmission capability drops sharply.

[0003] Communication "blind spots" and dynamic coverage issues arise, as oceans may present obstacles between surface platforms and AUVs, leading to degraded communication quality. This invention proposes a novel process and communication logic, hardware and system architecture, and UAV control strategy to address these problems. Summary of the Invention

[0004] The purpose of this invention is to provide a communication method, system, program, device, and storage medium between a surface platform and an AUV based on UAV relay.

[0005] The objective of this invention is achieved through the following technical solution:

[0006] A communication method between a surface platform and an AUV based on UAV relay includes the following steps:

[0007] Step 1: Obtain the initial target area coordinates of the AUV, the initial position coordinates of the UAV, and the current position coordinates of the UAV, and establish a stable initial communication link between the UAV and the AUV. Through the initial communication link, the UAV measures the original signal strength at its current position coordinates.

[0008] Step 2: Calculate the comprehensive communication benefit function value at the current moment based on the original signal strength measurement value at the current moment.

[0009] Step 3: Optimize the UAV's position based on its current location coordinates and the current comprehensive communication benefit function value to obtain the gradient magnitude of the updated UAV location coordinates and comprehensive communication benefit function value.

[0010] Step 4: Based on the gradient magnitude of the updated UAV position coordinates and the integrated communication benefit function value, determine whether the UAV position coordinate optimization has converged. If so, end the position optimization, output the updated UAV position coordinates, and execute Step 5; otherwise, use the updated UAV position coordinates as the new current position coordinates and return to Step 2.

[0011] Step 5: Determine if there is an external communication termination command. If so, the UAV stops relaying, ascends, and returns to the surface platform. Otherwise, the UAV hovers at the updated UAV position coordinates, continues to perform data relay tasks, and maintains low-frequency UAV position optimization to ensure stable communication links and communication quality.

[0012] Furthermore, the comprehensive communication benefit function value at the current moment described in step 2... The specific calculation methods include:

[0013]

[0014]

[0015]

[0016]

[0017]

[0018]

[0019]

[0020]

[0021] in, All are weighting coefficients. To improve the efficiency of communication links between drones and AUVs, For the benefit of radio frequency links between drones and surface platforms, Signal strength factor For link stability factor, For the current moment The signal strength after first-order low-pass filtering at that time, These represent the upper and lower limits of the signal strength required for the communication module to function properly. These are the filter coefficients. For the current moment The original signal strength measurement value at that time, For the previous moment The signal strength after first-order low-pass filtering at that time, This represents the standard deviation of the signal strength after first-order low-pass filtering over a historical period. As a stability threshold, This is the link capacity factor. For sight distance factor, This represents the signal-to-noise ratio of the link between the UAV and the surface platform, as measured by the UAV at the current moment. For the target signal-to-noise ratio, This represents the obstacle penalty coefficient.

[0022] Furthermore, step 3, optimizing the drone's position, specifically includes the following steps:

[0023] Step 3.1: Using the current position coordinates of the UAV Centered on, along Each direction generates a test point. ;

[0024]

[0025] in, For the test point index, To test the step size, For the first A unit vector in the opposite direction.

[0026] Step 3.2: Instruct the drone to briefly fly to each test point in sequence. It can quickly calculate the comprehensive communication benefit value of the test point and perform gradient estimation.

[0027] Step 3.3: The UAV moves along the gradient direction and calculates the updated UAV position coordinates. ;

[0028]

[0029] in, To ensure the new location is within a reasonably limited search space Projection operator within, For adaptive step size, For the gradient of comprehensive benefit values, It is a very small positive number.

[0030] Furthermore, the conditions for determining whether the UAV position coordinate optimization has converged specifically include at least one of the following conditions:

[0031] The direction of movement is uncertain due to the gradient magnitude being too small. ;

[0032] The position update was too small, resulting in the drone barely moving. ;

[0033] The overall benefit value has shown only slight improvement over several cycles: ;

[0034] in, These are the gradient magnitude threshold, the position update threshold, and the comprehensive benefit improvement threshold, respectively.

[0035] A communication system for a surface platform and an AUV based on UAV relay includes a positioning module, an AUV communication module, a radio frequency communication module, a signal strength measurement module, a data fusion and processing module, an optimization module, and a UAV communication module.

[0036] The positioning module is used to obtain the initial target area coordinates of the AUV, the initial position coordinates of the UAV, and the current position coordinates of the UAV.

[0037] The AUV communication module, radio frequency communication module, and UAV communication module are all used to establish the initial communication link;

[0038] The signal strength measurement module is used to measure the original signal strength;

[0039] The data fusion and processing module is used to calculate the value of the comprehensive communication benefit function and the gradient magnitude of the comprehensive communication benefit function at the current moment.

[0040] The optimization module is used to optimize the drone's position.

[0041] A computer device includes a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the method described above.

[0042] A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the above-described method.

[0043] A computer program product includes computer instructions that, when executed by a processor, implement the steps of the above-described method.

[0044] The beneficial effects of this invention are as follows:

[0045] This invention utilizes unmanned aerial vehicles (UAVs) for communication relay. When an AUV needs to surface for communication, the surface platform launches the UAV to search the target sea area, while the AUV raises its communication mast. Once the AUV is located, the UAV hovers above it, acting as a communication relay. After the relay is complete, the AUV retracts its mast and submerges, while the UAV returns to the platform. This improves the reliability and stability of the communication link, extends the effective operating radius of the AUV, ensures the AUV's mission stealth and operational continuity, and achieves system-level energy optimization and enhanced mission endurance. Attached Figure Description

[0046] Figure 1 This is a schematic diagram of a drone relay communication system according to an embodiment of the present invention.

[0047] Figure 2 This is the global flowchart of the present invention. Detailed Implementation

[0048] The present invention will now be further described with reference to the accompanying drawings.

[0049] refer to Figure 2 A communication method between a surface platform and an AUV based on UAV relay includes the following steps:

[0050] Step 1: Obtain the initial target area coordinates of the AUV, the initial position coordinates of the UAV, and the current position coordinates of the UAV, and establish a stable initial communication link between the UAV and the AUV. Through the initial communication link, the UAV measures the original signal strength at its current position coordinates.

[0051] Step 2: Calculate the comprehensive communication benefit function value at the current moment based on the original signal strength measurement value at the current moment.

[0052] The current time comprehensive communication efficiency function value The specific calculation methods include:

[0053]

[0054]

[0055]

[0056]

[0057]

[0058]

[0059]

[0060]

[0061] in, All are weighting coefficients. To improve the efficiency of communication links between drones and AUVs, For the benefit of radio frequency links between drones and surface platforms, Signal strength factor For link stability factor, For the current moment The signal strength after first-order low-pass filtering at that time, These represent the upper and lower limits of the signal strength required for the communication module to function properly. These are the filter coefficients. For the current moment The original signal strength measurement value at that time, For the previous moment The signal strength after first-order low-pass filtering at that time, This represents the standard deviation of the signal strength after first-order low-pass filtering over a historical period. As a stability threshold, This is the link capacity factor. For sight distance factor, This represents the signal-to-noise ratio of the link between the UAV and the surface platform, as measured by the UAV at the current moment. For the target signal-to-noise ratio, This represents the obstacle penalty coefficient.

[0062] Step 3: Optimize the UAV's position based on its current location coordinates and the current comprehensive communication benefit function value to obtain the gradient magnitude of the updated UAV location coordinates and comprehensive communication benefit function value.

[0063] The optimization of the drone's position specifically includes the following steps:

[0064] Step 3.1: Using the current position coordinates of the UAV Centered on, along Each direction generates a test point. ;

[0065]

[0066] in, For the test point index, To test the step size, For the first A unit vector in the opposite direction.

[0067] Step 3.2: Instruct the drone to briefly fly to each test point in sequence. And quickly calculate the comprehensive communication benefit value of the test point, and perform gradient estimation;

[0068] Step 3.3: The UAV moves along the gradient direction and calculates the updated UAV position coordinates. ;

[0069]

[0070] in, To ensure the new location is within a reasonably limited search space Projection operator within, For adaptive step size, For the gradient of comprehensive benefit values, It is a very small positive number.

[0071] Step 4: Based on the gradient magnitude of the updated UAV position coordinates and the integrated communication benefit function value, determine whether the UAV position coordinate optimization has converged. If so, end the position optimization, output the updated UAV position coordinates, and execute Step 5; otherwise, use the updated UAV position coordinates as the new current position coordinates and return to Step 2.

[0072] The conditions for determining whether the UAV position coordinate optimization has converged specifically include at least one of the following conditions:

[0073] The direction of movement is uncertain due to the gradient magnitude being too small. ;

[0074] The position update was too small, resulting in the drone barely moving. ;

[0075] The overall benefit value has shown only slight improvement over several cycles: ;

[0076] in, These are the gradient magnitude threshold, the position update threshold, and the comprehensive benefit improvement threshold, respectively.

[0077] Step 5: Determine if there is an external communication termination command. If so, the UAV stops relaying, ascends, and returns to the surface platform. Otherwise, the UAV hovers at the updated UAV position coordinates, continues to perform data relay tasks, and maintains low-frequency UAV position optimization to ensure stable communication links and communication quality.

[0078] Example

[0079] refer to Figure 1 A communication system for a surface platform and an AUV based on UAV relay includes a positioning module, an AUV communication module, a radio frequency communication module, a signal strength measurement module, a data fusion and processing module, an optimization module, and a UAV communication module.

[0080] The positioning module is used to obtain the initial target area coordinates of the AUV, the initial position coordinates of the UAV, and the current position coordinates of the UAV.

[0081] The AUV communication module, radio frequency communication module, and UAV communication module are all used to establish the initial communication link.

[0082] The signal strength measurement module is used to measure the original signal strength.

[0083] The data fusion and processing module is used to calculate the value of the comprehensive communication benefit function and the gradient magnitude of the comprehensive communication benefit function at the current moment.

[0084] The optimization module is used to optimize the drone's position.

[0085] refer to Figure 2 The surface support platform operates in distant sea areas, while the AUV performs tasks underwater. When the AUV needs communication, it surfaces near the water and deploys a retractable communication mast. A drone carrying a relay communication pod flies over the AUV, establishing an aerial relay communication link between the AUV and the surface support platform—a link between the AUV, the drone, and the mothership.

[0086] Summoning and initial positioning.

[0087] The drone is in standby mode on the mothership or at the designated location. The algorithm is activated when it receives an acoustic call signal from the AUV or a dispatch command from the mothership.

[0088] The algorithm analyzes the call signal to obtain the initial target area coordinates of the AUV. These coordinates can be the AUV's last known GPS location or its real-time location calculated by its inertial navigation.

[0089] Arrive and enter search mode.

[0090] The flight control system controls the drone to fly to the initial target area and hover at a preset initial altitude (e.g., 150 meters).

[0091] The drone activated its communication pod and entered active search mode to listen for the AUV's acoustic beacon.

[0092] Precise positioning and link establishment.

[0093] Once the acoustic signals of the AUV are captured, the algorithm estimates the AUV's position and distance relative to the UAV using signal arrival intensity or beamforming technology of the directional transducer array.

[0094] The path loss model for radio signal propagation is used:

[0095]

[0096] In the formula : at distance The signal strength measured at the location.

[0097] At reference distance The known signal strength at that location.

[0098] Path loss index, determined by the propagation environment, ranges from 2 to 6. Corresponding to the case of free space, when obstacles increase, The corresponding increase.

[0099] Shadowing fading follows a zero-mean Gaussian distribution. Shadowing fading occurs when radio waves encounter obstacles in their propagation path, creating a shadow region behind the obstacle where the signal strength is weaker.

[0100] Based on this information, the drone fine-tunes its horizontal position, hovering roughly directly above the AUV, and establishes a stable communication link with the AUV.

[0101] Dynamic optimization and position maintenance.

[0102] This step is a continuously running closed-loop control process. The algorithm periodically executes the following steps:

[0103] Optimal decision-making: In the first One optimization cycle, at the current position Centered on, along the preset A pair of orthogonal probing directions (Generating test points in 6 directions: east, west, south, north, up, and down)

[0104] In the formula The step size can be adjusted to test the limits. This serves as an index for trial points. For the first A unit vector in the opposite direction.

[0105] The drones flew briefly to each test point in turn. And quickly measure and calculate the benefit value at that point. Subsequently, gradient Estimated using the central difference method:

[0106]

[0107] In the formula, This represents the rate of change of the overall communication benefit value in the east-west direction. The difference between the overall communication efficiency values ​​of the East Point and the West Point. This represents the distance difference in the east-west direction. The difference between the overall communication efficiency values ​​of the south and north points. This represents the distance difference between the north and south directions. The difference between the overall communication efficiency values ​​of the upper and lower points. This represents the difference in distance between the vertical and horizontal directions.

[0108] After obtaining the gradient estimate, the UAV position is updated using the following formula:

[0109]

[0110] To prevent division by zero for a very small positive number, To ensure the new location is within a reasonably limited search space Projection operator within.

[0111] Adaptive step size The step size can be adaptively adjusted with each iteration to improve convergence and prevent oscillations.

[0112]

[0113] In the formula, Add a factor to the step size. This is a step size reduction factor. To allow an upper limit on the step size, This is the lower limit of the allowed step size.

[0114] Position preservation: When one of the following conditions is met, it can be determined that the algorithm has converged to a local optimum and exits the active optimization loop;

[0115] 1. Gradient magnitude is less than the threshold: .

[0116] 2. Insufficient location update amount: .

[0117] 3. Slight improvement in benefit value: This continues for several cycles.

[0118] In the formula, These are the gradient magnitude threshold, the position update threshold, and the comprehensive benefit improvement threshold, respectively.

[0119] Communication termination and return:

[0120] The algorithm exits the optimization loop when it receives a "communication end" signal from the AUV or when the link with the AUV is interrupted for an extended period of time.

[0121] The drone ascends to a higher altitude to strengthen its link with the mother ship and receive instructions to return or proceed to the next mission point.

[0122] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A communication method between a surface platform and an AUV based on UAV relay, characterized in that, Includes the following steps: Step 1: Obtain the initial target area coordinates of the AUV, the initial position coordinates of the UAV, and the current position coordinates of the UAV, and establish a stable initial communication link between the UAV and the AUV. Through the initial communication link, the UAV measures the raw signal strength at its current position coordinates. Step 2: Calculate the comprehensive communication benefit function value at the current moment based on the original signal strength measurement value at the current moment; Step 3: Based on the UAV's current position coordinates and the current comprehensive communication benefit function value, optimize the UAV's position to obtain the gradient magnitude of the updated UAV position coordinates and comprehensive communication benefit function value; Step 4: Based on the gradient magnitude of the updated UAV position coordinates and the integrated communication benefit function value, determine whether the UAV position coordinate optimization has converged. If so, end the position optimization, output the updated UAV position coordinates, and execute Step 5; otherwise, use the updated UAV position coordinates as the new current position coordinates and return to Step 2. Step 5: Determine if there is an external communication termination command. If so, the UAV stops relaying, ascends, and returns to the surface platform. Otherwise, the UAV hovers at the updated UAV position coordinates, continues to perform data relay tasks, and maintains low-frequency UAV position optimization to ensure stable communication links and communication quality.

2. The communication method between a surface platform and an AUV based on UAV relay according to claim 1, characterized in that, Step 2 describes the current time-integrated communication benefit function value. The specific calculation methods include: in, All are weighting coefficients. To improve the efficiency of communication links between drones and AUVs, For the benefit of radio frequency links between drones and surface platforms, Signal strength factor For link stability factor, For the current moment The signal strength after first-order low-pass filtering at that time, These represent the upper and lower limits of the signal strength required for the communication module to function properly. These are the filter coefficients. For the current moment The original signal strength measurement value at that time, For the previous moment The signal strength after first-order low-pass filtering at that time, This represents the standard deviation of the signal strength after first-order low-pass filtering over a historical period. As a stability threshold, This is the link capacity factor. For sight distance factor, This represents the signal-to-noise ratio of the link between the UAV and the surface platform, as measured by the UAV at the current moment. For the target signal-to-noise ratio, This represents the obstacle penalty coefficient.

3. The communication method between a surface platform and an AUV based on UAV relay according to claim 2, characterized in that, Step 3, optimizing the drone's position, specifically includes the following steps: Step 3.1: Using the current position coordinates of the UAV Centered on, along Each direction generates a test point. ; in, For the test point index, To test the step size, For the first A unit vector in the opposite direction; Step 3.2: Instruct the drone to briefly fly to each test point in sequence. And quickly calculate the comprehensive communication benefit value of the test point, and perform gradient estimation; Step 3.3: The UAV moves along the gradient direction and calculates the updated UAV position coordinates. ; in, To ensure the new location is within a reasonably limited search space Projection operator within, For adaptive step size, For the gradient of comprehensive benefit values, It is a very small positive number.

4. The communication method between a surface platform and an AUV based on UAV relay according to claim 3, characterized in that, The conditions for determining whether the UAV position coordinate optimization has converged specifically include at least one of the following conditions: The direction of movement is uncertain due to the gradient magnitude being too small. ; The position update was too small, resulting in the drone barely moving. ; The overall benefit value has shown only slight improvement over several cycles: ; in, These are the gradient magnitude threshold, the position update threshold, and the comprehensive benefit improvement threshold, respectively.

5. A communication system between a surface platform and an AUV based on unmanned aerial vehicle (UAV) relay, characterized in that: It includes a positioning module, an AUV communication module, a radio frequency communication module, a signal strength measurement module, a data fusion and processing module, an optimization module, and an unmanned aerial vehicle (UAV) communication module; The positioning module is used to obtain the initial target area coordinates of the AUV, the initial position coordinates of the UAV, and the current position coordinates of the UAV. The AUV communication module, radio frequency communication module, and UAV communication module are all used to establish the initial communication link; The signal strength measurement module is used to measure the original signal strength; The data fusion and processing module is used to calculate the value of the comprehensive communication benefit function and the gradient magnitude of the comprehensive communication benefit function at the current moment. The optimization module is used to optimize the drone's position.

6. A computer device comprising a memory, a processor, and a computer program stored in the memory, characterized in that: The processor executes the computer program to implement the steps of the method according to claims 1 to 5.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, it implements the steps of the method described in claims 1 to 5.

8. A computer program product comprising computer instructions, characterized in that: When the computer instructions are executed by the processor, they implement the steps of the method described in claims 1 to 5.

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