Communication relay configuration method, program product and electronic device for inspection unmanned aerial vehicle

Abstract

This disclosure provides a communication relay configuration method, program product, and electronic device for inspection drones, relating to the field of wireless communication technology. The method includes: collecting terrain information of the drone's inspection area and establishing a three-dimensional model based on the terrain information; determining the first signal coverage space of the ground communication station in the three-dimensional model based on information from the drone's ground communication station; determining the drone's inspection path in the three-dimensional model; if there is a non-communication path outside the first signal coverage space in the inspection path, generating an initial relay scheme that satisfies basic communication constraints based on the non-communication path; constructing an optimization function based on the communication quality and deployment cost of the relay scheme; and iteratively optimizing the initial relay scheme using the optimization function under basic communication constraints to obtain the final relay scheme for configuring the relay station. This disclosure solves the communication blind spot problem in the drone inspection process, achieving high communication quality and low deployment cost.

Description

Technical Field

[0001] This disclosure relates to the field of wireless communication technology, and more specifically, to communication relay configuration methods, program products, and electronic devices for inspection drones. Background Technology

[0002] In the operation and maintenance of large-scale projects such as hydropower stations, the use of drones for inspection has advantages such as high efficiency, safety, and comprehensiveness. For example, drones can be controlled to conduct routine inspections of hydropower station dams, ancillary facilities, and the surrounding geographical environment. Their inspection range is large, enabling the timely detection of potential geological disasters or environmental anomalies.

[0003] However, the complex terrain of hydropower stations and their surrounding areas, with numerous mountains and gullies, can affect the communication quality of drones, leading to communication blind spots. This could cause drones to lose ground control during inspections, preventing them from transmitting inspection data properly, and even resulting in safety accidents such as drone loss of contact or crashes. Summary of the Invention

[0004] This disclosure provides a communication relay configuration method, program product, and electronic device for inspection drones, to at least partially solve the technical problem of communication blind spots for drones caused by complex terrain.

[0005] According to a first aspect of this disclosure, a communication relay configuration method for an inspection drone is provided. The method includes: collecting terrain information of the inspection area of ​​the drone; establishing a three-dimensional model based on the terrain information; the inspection area includes a hydropower station and its surrounding area; determining a first signal coverage space of the ground communication station in the three-dimensional model based on information from the drone's ground communication station; determining the drone's inspection path in the three-dimensional model; if there is a non-communication path outside the first signal coverage space in the inspection path, generating an initial relay scheme that satisfies basic communication constraints based on the non-communication path; the basic communication constraint is that a second signal coverage space corresponding to the relay scheme includes the non-communication path; constructing an optimization function based on the communication quality and deployment cost of the relay scheme; and iteratively optimizing the initial relay scheme using the optimization function under the basic communication constraints to obtain a final relay scheme, thereby configuring a relay station for drone communication according to the final relay scheme.

[0006] According to a second aspect of this disclosure, a communication relay configuration device for an inspection drone is provided. The device includes: a terrain information processing module configured to collect terrain information of the inspection area of ​​the drone and establish a three-dimensional model based on the terrain information; the inspection area includes a hydropower station and its surrounding area; a first signal coverage space determination module configured to determine a first signal coverage space of the ground communication station in the three-dimensional model based on information from the drone's ground communication station; an initial relay scheme determination module configured to determine the inspection path of the drone in the three-dimensional model, and if there is a non-communication path outside the first signal coverage space in the inspection path, generate an initial relay scheme that satisfies basic communication constraints based on the non-communication path; the basic communication constraint is that a second signal coverage space corresponding to the relay scheme includes the non-communication path; an optimization function construction module configured to construct an optimization function based on the communication quality and deployment cost of the relay scheme; and a final relay scheme determination module configured to iteratively optimize the initial relay scheme using the optimization function under the basic communication constraints to obtain a final relay scheme, and configure relay stations for drone communication according to the final relay scheme.

[0007] According to a third aspect of this disclosure, a computer program product is provided, including a computer program that, when executed by a processor, implements the method of the first aspect described above and possible implementations thereof.

[0008] According to a fourth aspect of this disclosure, an electronic device is provided, comprising: a processor; and a memory for storing executable instructions of the processor; wherein the processor is configured to perform the method of the first aspect and possible implementations thereof by executing the executable instructions.

[0009] The technical solution disclosed herein has the following beneficial effects: On the one hand, by performing 3D modeling and signal coverage analysis of the terrain information of the hydropower station and its surrounding area, the impact of terrain on UAV communication can be predicted relatively accurately, and communication-free paths can be identified. Based on this fundamental communication constraint of covering communication-free paths, an initial relay scheme is generated and iteratively optimized to ensure that the final relay station configuration can solve the communication blind spot problem during UAV inspections and guarantee communication quality. On the other hand, an optimization function is constructed by considering factors such as communication quality and deployment cost. This optimization function is then used to iteratively optimize the relay scheme, enabling the final relay scheme to achieve high communication quality and low deployment cost, meeting the actual needs of the project. Attached Figure Description

[0010] Figure 1 A flowchart illustrating a communication relay configuration method for an inspection drone according to one embodiment of this disclosure is shown. Figure 2 This diagram illustrates an inspection area according to one embodiment of the present disclosure. Figure 3 A schematic diagram of the inspection area and inspection path in one embodiment of this disclosure is shown. Figure 4 A flowchart illustrating an iterative optimization relay scheme in one embodiment of this disclosure is shown. Figure 5 This diagram illustrates a flowchart of segmented determination of optimization function values ​​in one embodiment of the present disclosure; Figure 6 A flowchart illustrating the updating inspection path in one embodiment of this disclosure is shown; Figure 7 A schematic diagram of a communication relay configuration device for an inspection drone according to one embodiment of the present disclosure is shown. Figure 8 A schematic diagram of an electronic device according to one embodiment of the present disclosure is shown. Detailed Implementation

[0011] Exemplary embodiments of this disclosure will be described more fully below with reference to the accompanying drawings.

[0012] The accompanying drawings are schematic illustrations of this disclosure and are not necessarily drawn to scale. Some block diagrams shown in the drawings may be functional entities and do not necessarily correspond to physically or logically independent entities. These functional entities may be implemented in software, in hardware modules or integrated circuits, or in networks, processors, or microcontrollers. Implementations can be carried out in various forms and should not be construed as limited to the examples set forth herein. The features, structures, or characteristics described in this disclosure can be combined in any suitable manner in one or more embodiments. Numerous specific details are provided in the following description to give a full description of the technical solutions of this disclosure. However, those skilled in the art will recognize that one or more specific details may be omitted in implementing the technical solutions of this disclosure, or other methods, components, apparatuses, steps, etc., may be used to replace one or more specific details.

[0013] This disclosure provides a communication relay configuration method for an inspection drone. Figure 1 An exemplary flow of the method is shown, including the following steps: S110 collects terrain information of the drone inspection area and builds a 3D model based on the terrain information; the inspection area includes the hydropower station and its surrounding area. S120, based on information from the UAV ground communication station, determines the first signal coverage space of the ground communication station in the three-dimensional model; S130, determine the inspection path of the UAV in the 3D model. If there is a non-communication path outside the first signal coverage space in the inspection path, generate an initial relay scheme that satisfies the basic communication constraints based on the non-communication path. The basic communication constraints are: the second signal coverage space corresponding to the relay scheme contains the non-communication path. S140, construct an optimization function based on the communication quality and deployment cost of the relay scheme; S150, under basic communication constraints, uses an optimization function to iteratively optimize the initial relay scheme to obtain the final relay scheme, and configures the relay station for UAV communication according to the final relay scheme.

[0014] Based on the above methods, on the one hand, by performing 3D modeling and signal coverage analysis of the terrain information of the hydropower station and its surrounding area, the impact of terrain on UAV communication can be predicted relatively accurately, and communication-free paths can be identified. Taking the fundamental communication constraint of covering communication-free paths as a premise, an initial relay scheme is generated and iteratively optimized to ensure that the finally configured relay station can solve the communication blind spot problem during UAV inspections and guarantee communication quality. On the other hand, an optimization function is constructed by comprehensively considering factors such as communication quality and deployment cost. This optimization function is then used to iteratively optimize the relay scheme, enabling the final relay scheme to achieve high communication quality and low deployment cost, meeting the actual needs of the project.

[0015] The following describes, in conjunction with one or more embodiments and related accompanying drawings, Figure 1 Each step in the process will be explained in detail.

[0016] refer to Figure 1 In step S110, terrain information of the UAV inspection area is collected, and a three-dimensional model is established based on the terrain information; the inspection area includes the hydropower station and surrounding areas.

[0017] Among these methods, drones can be used to photograph hydropower stations and surrounding areas to obtain terrain information. Figure 2 A schematic diagram of the drone's inspection area is shown, including the hydropower station and surrounding area. Considering the existence of communication blind spots for the drone in the surrounding area, methods such as designing the initial shooting path and deploying temporary relay stations can be used to ensure the drone completes its initial shooting and obtains complete terrain information. Terrain information can include images or videos of the inspection area, as well as data such as elevation, slope, aspect, geological type (e.g., rocky areas, soil areas, water areas), and obstacle distribution (e.g., trees, buildings, mountain protrusions) at different points within the inspection area.

[0018] A 3D model is a three-dimensional digital model constructed using 3D modeling technology that can realistically reproduce the terrain undulations, obstacle distribution, and other features of the inspection area. It can also be used to simulate signal propagation paths and coverage areas, and may include 3D point cloud models. For example, drones can capture aerial images or videos of the inspection area, and can also combine this with LiDAR technology to accurately measure key data such as terrain elevation and slope, compensating for the limitations of aerial photography. Furthermore, it can acquire existing geographic information data and geological survey data of the inspection area, integrating multi-source data to form comprehensive terrain information. After data acquisition, the terrain information undergoes preprocessing, including data denoising, outlier removal, and data standardization, to remove invalid and interfering data and ensure data reliability. Then, a 3D model is built based on the preprocessed terrain information. The terrain information can be imported into 3D modeling software, and the software's terrain modeling function can be used to recreate the terrain undulations, obstacle distribution, geological type distribution, and other features of the inspection area. During the modeling process, we can focus on key terrain features that affect UAV communication, such as the height and slope of mountains, the depth and width of gullies, and the location and height of large obstacles. We can set up high-density point clouds for these terrain features to ensure that the constructed 3D model can fully reflect the impact of these terrain features on signal propagation.

[0019] Continue to refer to Figure 1 In step S120, the first signal coverage space of the ground communication station is determined in the three-dimensional model based on the information of the UAV ground communication station.

[0020] The ground communication station is a communication point for the drone located on the ground. It can send control commands to the inspection drone and receive inspection data. Information about the ground communication station includes, but is not limited to, station location, communication power, signal frequency, antenna gain, and communication distance. Typically, the ground communication station can be deployed in a location with an open view and no significant obstructions at the hydropower station. For example, refer to... Figure 2 As shown, a ground communication station 201 can be deployed in an open area on the top of the hydropower station dam. The first signal coverage space refers to the area that the communication signal of the ground communication station can reach, and the communication quality between the UAV and the ground communication station in this area can meet the basic requirements of normal UAV inspection (such as signal strength reaching a certain level and bit error rate below a certain level). In this embodiment, the first signal coverage space is determined and represented in a three-dimensional model to facilitate the subsequent determination of the relay scheme through the three-dimensional model.

[0021] For example, firstly, information about the ground communication station is acquired, including its location (latitude, longitude, and elevation), communication power, signal frequency, antenna gain, and communication distance. These parameters can be determined based on the equipment specifications of the ground communication station and the actual inspection needs of the hydropower station. Then, based on the 3D model, a signal coverage simulation algorithm is used to calculate the propagation range of the signal emitted by the ground communication station within the inspection area, thereby determining the first signal coverage space. In specific calculations, the impact of terrain features on signal propagation in the inspection area can be considered. For example, obstacles such as mountains and tall buildings can obstruct the signal, causing signal attenuation or interruption. During the simulation, the attenuation of the signal under different terrain conditions needs to be calculated to determine the effective propagation range of the signal. Simultaneously, considering the minimum communication quality requirements for normal UAV inspection, indicators such as signal strength threshold and bit error rate threshold are set, and the spatial range in the 3D model that meets these indicators is determined as the first signal coverage space. The range of the first signal coverage space can be marked in the 3D model to provide a basis for subsequent inspection path analysis and determination of non-communication paths.

[0022] Continue to refer to Figure 1 In step S130, the inspection path of the UAV is determined in the three-dimensional model. If there is a non-communication path outside the first signal coverage space in the inspection path, an initial relay scheme that satisfies the basic communication constraints is generated based on the non-communication path. The basic communication constraints are: the second signal coverage space corresponding to the relay scheme contains the non-communication path.

[0023] The inspection path can be a pre-planned drone flight path that can cover all inspection targets within the inspection area (such as dam monitoring points, auxiliary facility monitoring points, key geological monitoring points in the surrounding area, etc.). Figure 3 A schematic diagram of the inspection area and inspection route is shown. The dotted line in the diagram represents inspection route 202, which starts from ground communication station 201, passes through the dam, the surrounding main mountains and rivers, and finally returns to ground communication station 201.

[0024] If the entire inspection path is within the first signal coverage area, it means that the ground communication station can meet the communication needs of the UAV during its flight along the inspection path, and no relay station is required. If the entire inspection path is not within the first signal coverage area, the portion of the inspection path outside the first signal coverage area is called the no-communication path. This means that when the UAV is flying along the inspection path and is in the no-communication path segment, the communication quality with the ground communication station is poor or non-existent. In this case, a relay station is required.

[0025] In the aforementioned basic communication constraints, the relay scheme can refer to the initial relay scheme or any relay scheme in subsequent iterative optimization processes. The second signal coverage space corresponding to the relay scheme refers to the space that the communication signal of the relay station in the relay scheme can reach. The communication quality between the UAV and the relay station within the second signal coverage space can meet the basic requirements of normal UAV inspection. An initial relay scheme that satisfies the basic communication constraints is generated based on the absence of a communication path. The initial relay scheme is a preliminary relay configuration scheme, which may include the relay location (i.e., the deployment location of the relay station), the communication parameters of the relay station (such as communication power, signal frequency, antenna direction, etc.), etc.

[0026] For example, the inspection path is imported into a 3D model and overlaid with the first signal coverage space for analysis to determine whether the inspection path is completely within the first signal coverage space. If the entire inspection path is within the first signal coverage space, it means that the UAV can directly establish stable communication with the ground communication station throughout the inspection process, without the need to configure a relay station. If some segments of the inspection path are outside the first signal coverage space, these segments are considered non-communication paths, requiring the configuration of a relay station to resolve their communication issues. Once a non-communication path is identified, an initial relay scheme that meets basic communication constraints is generated based on the distribution characteristics, length, and terrain conditions of the non-communication path. When determining the initial relay scheme, a second signal coverage space is constructed by deploying relay stations to ensure that this space completely covers the non-communication path, enabling indirect communication between the UAV and the ground communication station. For example, the spatial distribution of the non-communication path is analyzed to determine its starting point, ending point, direction, and surrounding terrain features, selecting suitable areas for relay station deployment (such as areas with flat terrain, no obvious obstructions, and easy equipment installation and maintenance). Based on the length of the no-communication path and the signal propagation distance, the number of relay stations is initially determined. For example, for a short no-communication path, one relay station can achieve coverage, while for a longer or more complex no-communication path, multiple relay stations can be deployed to form relay communication. The specific deployment location and communication parameters of each relay station are determined, and this information is integrated to form an initial relay scheme, ensuring that the second signal coverage space corresponding to this scheme can completely cover the no-communication path and meet the basic communication constraints.

[0027] Continue to refer to Figure 1 In step S140, an optimization function is constructed based on the communication quality and deployment cost of the relay scheme.

[0028] Communication quality refers to the stability and reliability of communication between the UAV and the ground communication station (direct communication or indirect communication through relay stations) during the inspection process, which can be quantitatively characterized by indicators such as signal strength, bit error rate, transmission rate, and communication latency. Deployment cost refers to the cost required to implement the relay scheme, which may include the purchase cost of relay station equipment, installation and construction costs, subsequent operation and maintenance costs, and site occupancy costs. The optimization function is a function that quantitatively evaluates the merits of the relay scheme. By comprehensively considering both communication quality and deployment cost, an evaluation index that balances the relationship between the two is constructed, providing a basis for the iterative optimization of the relay scheme.

[0029] For example, the input parameters of the optimization function can be determined first, namely the communication quality and deployment cost of the relay scheme. Communication quality can be comprehensively measured by multiple indicators (such as average signal strength, maximum bit error rate, minimum transmission rate, etc.), and deployment cost can be obtained by summing the costs of relay station equipment purchase, installation, and maintenance. Based on the actual needs of the project, the weights of communication quality and deployment cost in the optimization function are determined. The weights can be set in conjunction with the hydropower station's inspection priority and cost budget. If the hydropower station has high requirements for the stability of inspection communication, the weight of communication quality can be increased; if the hydropower station has strict cost control requirements, the weight of deployment cost can be appropriately increased. Finally, an optimization function is constructed based on the input parameters and weights. This function needs to be able to quantify the advantages and disadvantages of the relay scheme. For example, a higher optimization function value indicates better overall performance of the relay scheme, i.e., higher communication quality and lower deployment cost, thus providing a clear objective for subsequent iterative optimization of the relay scheme.

[0030] Continue to refer to Figure 1 In step S150, under the basic communication constraints, the initial relay scheme is iteratively optimized using an optimization function to obtain the final relay scheme, so as to configure the relay station for UAV communication according to the final relay scheme.

[0031] For example, the constraints of iterative optimization, namely the basic communication constraints, can be clearly defined to ensure that during the iterative optimization process, the second signal coverage space corresponding to all optimized relay schemes can completely include the communication-free path, ensuring that no communication blind spots occur. Subsequently, the initial relay scheme is substituted into the optimization function to calculate the optimization function value of the initial scheme, which serves as the initial benchmark for iterative optimization.

[0032] The iterative optimization process is as follows: The parameters of the initial relay scheme are gradually adjusted, including the number of relay stations, their deployment locations, and communication parameters. Each adjustment yields a new relay scheme. For each new relay scheme, it is first verified whether it meets the basic communication constraints. If not, the scheme is abandoned, and the parameters are adjusted further. If it meets the constraints, the optimization function value of the scheme is calculated and compared with the current optimal optimization function value. If the optimization function value of the new scheme is higher than the current optimal value, the scheme is adopted as the new optimal scheme, and iteration continues. If the optimization function value of the new scheme is lower than or equal to the current optimal value, the scheme is abandoned, and the parameters are adjusted again, and iteration continues.

[0033] The iterative process continues until the preset iteration termination conditions are met (such as the number of iterations reaching a preset threshold, the optimized function value stabilizing, or the optimized function value reaching a preset target value). At this point, the current optimal relay scheme is the final relay scheme. Finally, according to the final relay scheme, the relay stations are actually deployed and configured, including the installation and debugging of the relay station equipment and the setting of communication parameters, to ensure that the relay stations can work normally, achieve signal coverage without communication paths during UAV inspections, and ensure stable communication between the UAV and the ground communication station.

[0034] In one implementation, reference Figure 4 As shown, the above-mentioned iterative optimization of the initial relay scheme using an optimization function to obtain the final relay scheme includes the following steps: S410: Perform communication simulation on the initial relay scheme, determine the communication quality of the initial relay scheme based on the communication simulation results, and obtain the deployment cost of the initial relay scheme. S420: Substitute the communication quality and deployment cost corresponding to the initial relay scheme into the optimization function to calculate the optimization function value corresponding to the initial relay scheme. S430, with the goal of maximizing the optimization function value, iteratively optimizes the initial relay scheme; S440: When the first preset condition is met, the current optimized relay scheme is determined as the final relay scheme.

[0035] Communication simulation refers to simulating the communication process between a UAV and relay stations and ground communication stations during inspections using simulation software, based on a 3D model and relay scheme parameters, to obtain communication simulation results, which may include key data such as communication quality. The first preset condition refers to the termination condition of the iterative optimization, which can be set according to actual engineering needs, including but not limited to reaching a preset number of iterations, convergence of the optimization function value, and reaching a preset optimal target value.

[0036] In one implementation, the optimization function is: (1) Where Opt() represents the optimization function; w1, w2, and w3 represent the weights in the optimization function; relay k Represents relay scheme k; route i Indicates the reference point i on the inspection path; signal(route) i relay k ) represents the communication quality of reference point i under relay scheme k; min(signal(route) i relay k )) represents the minimum communication quality of each reference point under relay scheme k; cost(relay) k ) represents the deployment cost of relay scheme k. In one implementation, reference points can be uniformly determined along the inspection path, such as selecting a reference point at regular intervals. The number of reference points can be determined based on the length of the inspection path and the complexity of the terrain. The longer the inspection path and the more complex the terrain, the more reference points are needed to ensure a comprehensive reflection of the communication situation along the inspection path. In one implementation, weights can be set based on experience or specific engineering requirements. Formula (1) integrates three aspects of information, including: the sum of communication quality of each reference point to ensure that the relay scheme has a better overall communication quality; the minimum communication quality of each reference point to focus on the communication quality of the weakest signal point in the relay scheme and ensure that the communication quality of the weakest point reaches a certain level; and the deployment cost to ensure that the relay scheme has a low or appropriate cost.

[0037] It should be noted that formula (1) can be used to calculate the optimization function value of any relay scheme, such as when k=0, relay k The initial relay scheme is represented by formula (1), which can be used to calculate the optimization function value of the initial relay scheme.

[0038] The goal of iterative optimization is to maximize the optimization function value, which means continuously improving the optimization function value by adjusting the parameters of the relay scheme to achieve the optimal balance between communication quality and deployment cost. Specific adjustment methods include: adjusting the deployment location of relay stations (e.g., moving relay stations to areas with better signal propagation and lower installation costs), increasing or decreasing the number of relay stations (e.g., reducing redundant relay stations to lower costs, or increasing relay stations to improve communication quality), and adjusting the communication parameters of the relay stations (e.g., optimizing communication power and signal frequency to reduce energy consumption and cost while ensuring communication quality). Each parameter adjustment yields a new relay scheme. The steps of communication simulation and optimization function value calculation are repeated, and the optimization function value of the new scheme is compared with the current optimal scheme. The optimal scheme is retained. This iterative optimization process continues until the first preset condition is met. For example, if the preset number of iterations is 50, the iteration is terminated when the number of iterations reaches 50, and the current optimized relay scheme is determined as the final relay scheme; if the preset stability threshold of the optimization function value is 0.01, when the difference of the optimization function value obtained in 5 consecutive iterations is less than 0.01, it indicates that the optimization function value tends to be stable, the iteration is terminated, and the final relay scheme is determined.

[0039] Based on the above methods, communication quality data of the relay scheme can be accurately obtained through communication simulation, ensuring the accuracy of the optimization function value calculation. Iterating with the goal of maximizing the optimization function value makes the optimization process more targeted and effectively improves the overall performance of the final relay scheme. By setting a first preset condition, the iterative optimization process is controllable and can be terminated, avoiding the inefficiency caused by unlimited iteration, while ensuring that the final relay scheme can stably meet the requirements of communication quality and cost control.

[0040] In one implementation, the above-mentioned method of substituting the communication quality and deployment cost corresponding to the initial relay scheme into the optimization function to calculate the optimization function value corresponding to the initial relay scheme includes the following steps: Based on the terrain features of the relay locations in the initial relay plan, determine the terrain evaluation value of the initial relay plan; terrain features include height, flatness, and geological type; The communication quality, deployment cost, and terrain evaluation value of the initial relay scheme are input into the optimization function to determine the optimization function value corresponding to the initial relay scheme.

[0041] Topographic features refer to the geographical and geological characteristics of the relay location, including altitude (such as the elevation of the relay location, which affects the signal propagation range), flatness (i.e., the levelness of the ground at the relay location, which affects the installation difficulty of the relay station equipment), and geological type (the geological conditions of the relay location, which affect the stability and operation and maintenance costs of the relay station). Other topographic features may also be included. The topographic evaluation value is used to quantify whether the relay location in the relay scheme is suitable for deploying a relay station, characterizing the degree of influence of the topographic features of the relay location on the installation, operation and maintenance, and signal propagation of the relay station. The higher the topographic evaluation value, the more suitable the terrain is for deploying the relay station.

[0042] For example, scores corresponding to different geological types can be pre-set, with higher scores assigned to geological types more suitable for relay station deployment. The scores for altitude, flatness, and geological type of each relay location are standardized and then combined using weighted methods to obtain a terrain evaluation value. This terrain evaluation value is then incorporated into the optimization function, in addition to communication quality and deployment cost, to calculate the optimization function value of the relay scheme.

[0043] In one implementation, the optimization function is: (2) Where Opt() represents the optimization function; w1, w2, w3, w4, and w5 represent the weights in the optimization function; relay k Let k represent the relay scheme, relay k,j Represents the relay position j in relay scheme k; route i Indicates the reference point i on the inspection path; signal(route) i relay k ) represents the communication quality of reference point i under relay scheme k; min(signal(route) i relay k )) represents the minimum communication quality of each reference point under relay scheme k; cost(relay) k ) represents the deployment cost of relay scheme k; dev(signal(route) i relay k )) represents the communication quality deviation of each reference point under relay scheme k, to ensure that the communication quality deviation between different reference points is not too large and to avoid communication jitter; terran(relay) k,j ) represents the terrain evaluation value of relay location j under relay scheme k.

[0044] By iteratively optimizing the relay scheme using the optimization function that includes terrain evaluation values, the factor of terrain adaptability is added to the consideration of communication quality and deployment cost. This ensures that the final relay scheme achieves the goals of high communication quality, low deployment cost, and good terrain adaptability, thereby meeting higher practical engineering needs.

[0045] In one implementation, reference Figure 5 As shown, the method also includes the following steps: S510 divides the inspection area into multiple sub-areas based on the inspection targets within the inspection area, with different sub-areas having different inspection targets. S520: Divide relay scheme k into multiple relay segments according to multiple sub-regions, and determine the weight of each relay segment according to the inspection target corresponding to each relay segment. S530 uses the weight corresponding to each relay segment and calculates the optimization function value of each relay segment based on the optimization function. The optimization function value of relay scheme k is obtained by combining the optimization function values ​​of each relay segment.

[0046] In this context, "inspection target" refers to the object that needs to be focused on during the inspection process. "Sub-region" refers to a subdivided area into which the entire inspection area is divided based on different inspection targets. Each sub-region corresponds to one type or category of inspection targets, and the importance and communication requirements of different sub-regions may differ. "Relay segment" refers to multiple sub-segments into which relay scheme k is divided based on the sub-region division. Specifically, all relay locations within each sub-region of relay scheme k, along with the non-communication paths that need to be covered within that sub-region, constitute a relay segment. Each relay segment is responsible for signal coverage of the non-communication paths within its corresponding sub-region, ensuring that UAVs can establish stable communication with ground communication stations through the relay stations within that sub-region during inspections. Therefore, each relay segment consists of one or more relay stations within the corresponding sub-region. The number and deployment locations of relay stations are determined based on the distribution of non-communication paths and terrain conditions within the sub-region. The weight corresponding to a relay segment refers to a parameter set based on the importance and requirements of the inspection targets in each sub-region, used to adjust the optimization priority of the corresponding relay segment in that sub-region. For example, if the geological conditions in a certain sub-region are poor, making it difficult to install relay stations, the weight corresponding to the deployment cost item (e.g., w3) can be set to be greater than the weight corresponding to the communication quality item (e.g., w1, w2). If the inspection targets in a certain sub-region are of high importance and require good communication quality, the weight corresponding to the communication quality item can be set to be greater than the weight corresponding to the deployment cost item.

[0047] For example, all relay stations deployed in a certain sub-region in relay scheme k, along with the non-communication paths that need to be covered within that sub-region, can be combined into a relay segment. That is, one sub-region corresponds to one relay segment, ensuring that the coverage of each relay segment is completely limited to the corresponding sub-region and is only responsible for signal coverage of the non-communication paths within that sub-region. For instance, if one relay station is deployed in the main body of the dam sub-region, responsible for covering one non-communication path within that sub-region, then this one relay station and one non-communication path together constitute the main body of the dam relay segment; if two relay stations are deployed in the mountain sub-region, responsible for covering three non-communication paths within that sub-region, then these two relay stations and three non-communication paths together constitute the mountain relay segment.

[0048] Then, determine the weight corresponding to each relay segment. Differentiated settings can be made based on factors such as the importance of the inspection target, communication requirements, and terrain conditions of the sub-region corresponding to each relay segment, ensuring that the optimization process prioritizes the needs of important sub-regions. For example, if the inspection target of a sub-region corresponding to a relay segment is of high importance (such as the main dam relay segment, corresponding to the dam structure safety inspection target), it indicates strict requirements for communication quality. It is necessary to ensure stable communication signals, no data transmission delay, and no data loss when the UAV inspects this sub-region. Therefore, when setting the weight of this relay segment, the focus should be on increasing the weight of communication quality-related indicators (i.e., w1 and w2 in the optimization function) and decreasing the weight of deployment cost-related indicators (i.e., w3 in the optimization function). This ensures that the optimization process prioritizes the communication quality of this relay segment, even if it means a slight increase in deployment cost. For example, it can be determined that weights w1 and w2 are greater than w3. If a sub-region corresponding to a relay segment has a medium-importance inspection target, considering the complex terrain conditions (such as relay segments on steep slopes with poor geological conditions and steep mountains), the installation of relay stations is difficult and costly, and subsequent operation and maintenance are inconvenient. Therefore, deployment cost becomes a core consideration. When setting the weight of this relay segment, the weight of deployment cost-related indicators (w3) should be increased, while the weight of communication quality-related indicators (w1, w2) should be appropriately reduced. This ensures that deployment cost is prioritized during the optimization process. Under the premise of meeting basic communication constraints (coverage without communication paths), the purchase, installation, and operation and maintenance costs of relay stations should be minimized as much as possible, such as when it can be determined that weights w1 and w2 are less than w3. The sum of the weights corresponding to each relay segment can be set to 1, or other fixed values ​​can be set according to actual needs. After the weights are set, the weight value of each relay segment is recorded for subsequent calculation of the optimization function value.

[0049] Formula (1) is used to calculate the optimization function value for each relay segment, considering only the reference points and relay stations within the relay segment. Specifically, the reference points of the inspection path corresponding to the relay segment are extracted, and the communication quality of each reference point under the action of the relay segment is obtained through communication simulation. The sum and minimum communication quality of all reference points within the relay segment are calculated, and the deployment cost of all relay stations within the relay segment is calculated. These data are substituted into Formula (1) and combined with the weights w1, w2, and w3 set for the relay segment to calculate the optimization function value of the relay segment. After calculating the optimization function value of each relay segment, the optimization function value of the relay scheme k can be obtained by combining the optimization function values ​​of all relay segments through methods such as addition, weighting, and averaging.

[0050] Calculate the overall optimization function value of relay scheme k. Multiply the optimization function value (Opt_j) of each relay segment by its corresponding weight (w_segment_j) to obtain the weighted optimization function value of each relay segment. Then, sum the weighted optimization function values ​​of all relay segments to obtain the overall optimization function value of the entire relay scheme k. The calculation logic can be expressed as: Opt(relay_k) = ∑(w_segment_j × Opt_j), where w_segment_j is the weight of the j-th relay segment, and Opt_j is the optimization function value of the j-th relay segment.

[0051] Based on the above method, assigning differentiated weights to different relay segments allows for flexible adjustment of optimization priorities according to the inspection importance, communication needs, and terrain conditions of sub-regions. This prioritizes ensuring communication quality in areas corresponding to important inspection targets, while reasonably controlling costs in areas with complex terrain and high deployment costs. This regional optimization and differentiated adaptation improves the relevance and flexibility of the relay solution, making it more suitable for the actual operation and maintenance scenarios of large-scale projects such as hydropower stations. Furthermore, during iterative optimization, the relay solution optimization can be decomposed into the optimization of each relay segment, reducing the overall optimization difficulty and making the optimization process more precise and efficient.

[0052] In one implementation, the above-mentioned generation of an initial relay scheme that satisfies basic communication constraints based on the absence of a communication path includes the following steps: The area without a communication path is expanded into a first area, and a second area that meets the second preset condition is selected from the first area. In the second area, determine one or more relay locations, and form one or more initial relay schemes based on one or more relay locations; If multiple initial relay schemes are obtained, the optimal initial relay scheme is selected from them using an optimization function.

[0053] The first region can be formed by extending a certain area outward from the area without a communication path. The extension range is determined based on the signal propagation distance of the relay station and the terrain features. This provides sufficient selection space for the deployment of relay stations, ensuring that they can effectively cover the areas without communication paths. The second preset condition refers to the conditions for selecting suitable areas for relay station deployment, mainly including terrain conditions (such as flat terrain, no obvious obstructions, and moderate elevation), installation conditions (such as easy equipment transportation and installation, and available installation sites), and operation and maintenance conditions (such as easy equipment maintenance and battery replacement). Areas that meet the second preset condition within the first region are selected and designated as the second region. The second region can be a continuous area or include multiple separate areas.

[0054] For example, the extension range of the no-communication-path area can be determined based on the maximum signal propagation distance of the relay station and the terrain features of the no-communication-path area. For instance, if the maximum signal propagation distance of the relay station is 500 meters, the no-communication-path area can be extended 300-500 meters to each side to form a first region, ensuring that the relay stations deployed within this region can effectively cover the no-communication-path area. Subsequently, a comprehensive analysis of the terrain features within the first region is conducted, and regions meeting the second preset conditions are selected as the second region. During the selection process, regions with rugged terrain, tall obstacles, unstable geological conditions, or those where relay equipment cannot be transported or installed are excluded. Regions with flat terrain, no obvious obstructions, stable geology, and ease of installation and maintenance are retained to form the second region. If multiple regions meeting the conditions exist within the first region, multiple independent second regions can be formed.

[0055] For each second area, the number of relay locations within that area is determined based on its size, coverage requirements for areas without communication paths, and the signal propagation range of the relay stations. For example, for a smaller second area, one relay location at the area's center is sufficient to cover the corresponding area without communication paths. For larger second areas or areas with complex terrain, multiple relay locations can be evenly distributed within the area to ensure complete signal coverage. When determining relay locations, priority should be given to selecting points with moderate elevation, no obstructions, and easy installation, avoiding points in low-lying areas, areas prone to water accumulation, or areas obstructed by mountains. Subsequently, the determined relay locations within all second areas are combined to form one or more initial relay schemes: if only one relay location is determined for each second area, all relay locations are combined to form one initial relay scheme; if multiple relay locations are determined for some second areas, different relay locations are combined to form multiple initial relay schemes.

[0056] If multiple initial relay schemes are obtained, first verify whether each initial relay scheme satisfies the basic communication constraints (i.e., whether the second signal coverage space completely includes the no-communication path), and eliminate schemes that do not meet the constraints; for schemes that meet the constraints, substitute the communication quality (which can be obtained through simple signal coverage simulation) and deployment cost of each scheme into the optimization function, and calculate the optimization function value of each scheme; finally, select the scheme with the highest optimization function value as the final initial relay scheme, providing a basis for subsequent iterative optimization.

[0057] By expanding the first region and filtering the second region, the selection range of relay locations can be effectively narrowed, avoiding blind deployment of relay stations and improving the rationality of the initial relay scheme. Through filtering multiple initial relay schemes, the initial scheme with the best overall performance can be selected, laying a solid foundation for subsequent iterative optimization, reducing the number of iterations, and improving optimization efficiency.

[0058] In one implementation, determining one or more relay locations within the second area and forming one or more initial relay schemes based on the one or more relay locations includes the following steps: The second region is divided into multiple relay regions based on the relay communication distance and the distribution characteristics of the second region; Identify at least one relay location within each relay area; By combining relay locations within different relay areas, one or more initial relay schemes can be obtained.

[0059] The relay communication distance refers to the maximum distance at which a relay station can achieve stable communication, i.e., the maximum distance at which the relay station can transmit signals normally with ground communication stations and with UAVs. This distance is related to the relay station's communication power, signal frequency, antenna gain, and terrain features. The distribution characteristics of the second region refer to its spatial distribution, including its shape, size, location, and relative position to non-communication paths. A relay region is a sub-region divided from the second region according to the relay communication distance and distribution characteristics. Each relay region corresponds to a segment of non-communication path and is responsible for signal coverage of that segment.

[0060] For example, the relay communication distance can be determined based on the relay station's communication parameters and the terrain features of the inspection area. For instance, considering the relay station's communication power and terrain obstruction, a relay communication distance of 300 meters can be determined. Subsequently, the distribution characteristics of the second area are analyzed. If the second area is a continuous large area with a relatively long non-communication path, it is divided into multiple relay areas based on the relay communication distance. The range of each relay area does not exceed the relay communication distance, ensuring that the relay stations deployed within each relay area can effectively cover the corresponding non-communication path. If the second area consists of multiple independent small areas, each small area can be directly used as a relay area, corresponding to a non-communication path. During the division process, it is necessary to ensure that multiple relay areas can completely cover the corresponding non-communication path, and that the relay areas do not overlap or omit any areas.

[0061] For each relay area, at least one relay location is determined based on the area's terrain features and locations without communication paths. Specifically, priority is given to selecting locations within the relay area that are at moderate elevation, have no significant obstructions, and can provide maximum coverage of the corresponding locations without communication paths. If the relay area has complex terrain, multiple relay locations can be determined within the area to ensure complete signal coverage. For example, for a relay area with flat terrain, one relay location can be determined at the center of the area; for a relay area with rugged terrain and local obstructions, 2-3 relay locations can be determined at points at different elevations within the area to achieve comprehensive signal coverage.

[0062] At least one relay location is determined within each relay area. One relay location is selected from each relay area to form an initial relay scheme. If multiple relay locations are determined for some relay areas, different relay locations are combined to form multiple initial relay schemes. For example, with 3 relay areas and 2 relay locations determined for each area, 2 × 2 × 2 = 8 initial relay schemes can be formed. After combination, each scheme is verified to meet the basic communication constraints. Schemes that do not meet the constraints are eliminated, and schemes that meet the constraints are retained for subsequent screening.

[0063] By dividing the second region into relay areas, the deployment of relay locations can be more targeted, ensuring that each relay location accurately covers the corresponding non-communication path. By identifying and combining multiple relay locations within each relay area, more diverse initial relay schemes can be generated, providing more options for subsequent selection of the optimal initial scheme.

[0064] In one implementation, reference Figure 6 As shown, the method also includes the following steps: S610: When the inspection target of the UAV changes, a loss function is constructed based on the new inspection target, the final relay plan, and the inspection path. S620 uses a loss function to iteratively update the inspection path to obtain a new inspection path.

[0065] For example, the loss function is: (3) Where Loss() represents the loss function; α, β, and γ represent the weights of the loss function; route0 represents the initial inspection path, route m Indicates the inspection path m; route 0,i Represents the reference point i on the initial inspection path, route m,i Dis represents the reference point i on the inspection path m. m,i ,route 0,i The distance between reference point i on the initial inspection path and reference point i on the inspection path m is represented by ; target represents the new inspection target, dis(route) m `,target)` represents the distance between the inspection path `m` and the new inspection target; `relay` represents the distance between the inspection path `m` and the new inspection target. f Indicates the final relay scheme; signal(route) m,i, relay f ) represents the communication quality of reference point i on inspection path m under the final relay scheme.

[0066] In one implementation, α, β, and γ can be set according to the actual needs of the hydropower station. α is used to adjust the weight of the deviation between the new inspection path and the initial inspection path, β is used to adjust the weight of the distance between the new inspection path and the new inspection target, and γ is used to adjust the weight of the communication quality of the new inspection path. For example, if it is desirable to minimize path adjustments, the value of α can be set to be larger; if it is desirable to prioritize coverage of the new inspection target, the value of β can be set to be larger; if it is desirable to ensure communication quality, the value of γ can be set to be larger.

[0067] In one implementation, the specific location and inspection requirements (such as inspection accuracy and frequency) of the new inspection target are first determined. Then, the parameters of the final relay scheme (relay station location, communication parameters, etc.) and the information of the initial inspection path (reference point location, flight trajectory, etc.) are obtained. Subsequently, a loss function is constructed based on this information. The core of the loss function is to balance three factors: the deviation between the new inspection path and the initial inspection path (to avoid increased planning costs due to excessive path changes), the distance between the new inspection path and the new inspection target (to ensure effective coverage of the new inspection target), and the communication quality of the new inspection path under the final relay scheme (to ensure stable communication). The initial inspection path is iteratively updated with the goal of minimizing the loss function value. Specifically, the reference point positions of the initial inspection path are adjusted to generate new inspection paths. For each new inspection path, its corresponding loss function value is calculated, and the communication quality of the path under the final relay scheme is verified to ensure that there are no new communication blind spots. If the loss function value of the new inspection path is less than the current optimal value and the communication quality meets the requirements, it is taken as the new optimal path. This process is continued until the loss function value tends to stabilize or reaches the preset target value. The inspection path obtained at this time is the new inspection path, which can adapt to the new inspection target and achieve stable communication using the existing final relay scheme without reconfiguring the relay station.

[0068] The above provides a solution for handling changes in inspection targets. It eliminates the need to reconfigure relay stations; simply updating the inspection path is sufficient to adapt to new inspection requirements, reducing the adjustment cost and complexity. By constructing a loss function, it is possible to balance path deviation, new target coverage, and communication quality, ensuring that the new inspection path effectively covers the new inspection target while maintaining stable communication quality, and minimizing the impact of path adjustments.

[0069] In one implementation, after configuring the relay station for UAV communication according to the final relay scheme, the method further includes the following steps: Generate spectral fingerprint features for each relay station; During the drone inspection process, real-time spectrum data is collected through each relay station. When the deviation between the real-time spectrum data and the spectrum fingerprint characteristics exceeds a preset threshold, the relay station is controlled to switch to an interference-free frequency or the weakest interference frequency in the available frequency list. Based on the pilot signal of the communication object, the antenna beam direction is adjusted to maintain the communication link by using the obstacle diffraction path or reflection path.

[0070] In the offline digital twin simulation phase, a fine-grained electromagnetic spectrum was constructed for the inspection area. For each relay station location in the final relay scheme, during the initial quiet period before or after deployment, the system performs a fingerprint acquisition process through the broadband spectrum sensing unit mounted on each relay station. Specifically, frequency sweeping is performed on the target frequency band (such as the 2.4GHz or 5.8GHz ISM band commonly used by UAVs), recording the background interference power spectral density at each relay station location. Background interference may include broadband noise generated by corona discharge from high-voltage equipment in hydropower stations, harmonics and narrowband interference generated by various power electronic devices, and conventional signals from surrounding known wireless communication systems. Then, the channel multipath angular spectrum characteristics of the relay station location are collected. 360-degree spatial spectrum estimation is performed using the antenna array configured on the relay station, recording the arrival angle, main lobe azimuth, and angular spread of the incident signals from the control station direction and the direction of adjacent relay stations. This azimuth information is verified with the 3D model using ray tracing to determine the spatial angles corresponding to the main path, primary reflection path, and main diffraction path. This information is then converted into structured data to obtain spectral fingerprint features, including the expected interference frequency distribution and multipath angular spectrum at each location point. The spectral fingerprint features can be stored in the relay station's local computing device and synchronized to the ground communication station or control station as a reference.

[0071] During routine inspections, each relay station, while performing normal data forwarding, activates the background monitoring mode of its spectrum sensing unit. This mode periodically captures idle communication slots using a time-division or low duty cycle approach to collect real-time spectrum data at the current location. It also runs a deviation detection algorithm to calculate the difference in spectral shape between the real-time spectrum data and the spectral fingerprint features. For example, a normalized deviation index based on KL divergence (Kullback-Leibler divergence, also known as relative entropy) or a spectral correlation function can be used to characterize the deviation between the real-time spectrum data and the spectral fingerprint features. In one implementation, two typical anomalies can be focused on: first, narrowband burst interference, which refers to the appearance of narrowband spikes in the real-time spectrum data that are not present in the spectral fingerprint features, and the spike power exceeding a certain threshold; and second, broadband noise floor elevation, which refers to a significant increase in the overall noise floor within a sub-band in the real-time spectrum data compared to the spectral fingerprint features, possibly caused by increased partial discharge or changes in weather conditions. When a deviation exceeding a preset threshold (which can be set based on experience, historical data, specific requirements, etc.) is detected, it is determined that an unexpected electromagnetic environment change has occurred at the relay station's location, i.e., a burst interference event. This determination process can be completed locally at the relay station, without relying on centralized processing at ground communication stations or control stations, thus ensuring real-time response.

[0072] Upon confirmation of a sudden interference event, the affected relay station retrieves a pre-configured list of available frequencies. This list can be a set of candidate clean channels determined according to relevant regulations and previous detection results. For each candidate frequency in the list, the relay station assesses its current interference energy level through a short-time spectrum snapshot. A frequency hopping strategy prioritizing the weakest interference is adopted, selecting the frequency with the lowest real-time interference power from the available frequency list as the target frequency hopping point. To simultaneously consider link quality, frequencies whose downlink pilot signal strength still meets the demodulation threshold can be further filtered from the available frequency list as secondary selections. After the frequency hopping decision is determined, beam realignment is performed between the relay station and the communication target (such as a ground communication station, upstream relay station, downstream relay station, or UAV). This implementation utilizes obstacle diffraction or reflection paths to bypass the impact of the sudden interference source. For example, the relay station's antenna system uses a switchable beam antenna array or a small phased array, capable of beam scanning in both horizontal and vertical planes. When interference occurs, the relay station attempts to focus its beam along the main path direction recorded in the spectral fingerprint feature. If the signal quality in the main path direction remains unacceptable (indicating the interference source is in or near the main path direction), the relay station initiates a pilot-assisted spatial scanning mechanism. The communication target continuously broadcasts a pilot signal containing its identification identifier. The relay station uses its receiving array to perform high-resolution spatial spectrum estimation on this pilot signal, searching for other significant coherent paths besides the direct main path. In a three-dimensional electromagnetic environment model, these paths typically correspond to reflection paths generated by strong reflectors such as dam surfaces, metal structures, and mountains, or diffraction paths generated by building edges and valleys. If a sufficiently strong pilot signal is captured at a non-main path angle, the relay station switches the main lobe direction of its working beam to that non-main path angle, using the reflection or diffraction path to establish a new communication link. Furthermore, by switching the beam polarization, a mode with polarization mismatch with the interference source can be selected to further reduce interference coupling.

[0073] Based on the above methods, real-time detection of electromagnetic environment changes is achieved by comparing real-time spectrum data with spectrum fingerprint features. This enables accurate identification of sudden interference events. Furthermore, through frequency hopping and beam coordination, interference countermeasures are carried out in both the frequency and spatial domains to ensure communication quality. Moreover, the beam alignment strategy that actively utilizes reflection and diffraction paths is suitable for scenarios with multiple reflective surfaces and complex obstacles in hydropower stations, thus expanding the spatial freedom of effective communication.

[0074] In one implementation, the method further includes the following steps: If the initial relay scheme or any relay scheme in the iterative optimization process does not meet the basic communication constraints, then the signal blind zone is determined according to the three-dimensional model, and a temporary relay position is determined outside the signal blind zone. The distance between the temporary relay position and the signal blind zone shall not exceed the preset distance. During drone inspections, at least one drone is controlled to hover at a temporary relay position to provide a temporary relay function.

[0075] If the initial relay scheme or any relay scheme in the iterative optimization process fails to meet the basic communication constraints—meaning that it is impossible to completely cover the no-communication path by deploying relay stations—then a signal blind zone is determined based on the 3D model. A signal blind zone refers to an area that cannot be covered even with relay stations deployed; it is typically located deep in canyons, on the back of mountains, or in narrow gullies where terrain obstruction is severe. Specifically, communication simulation can be used to search for all candidate relay locations in the 3D model. If there are still continuous path segments that cannot be covered by any relay location, the spatial area corresponding to that path segment is determined as the signal blind zone.

[0076] A temporary relay location is determined outside the signal blind zone, with the distance between the temporary relay location and the signal blind zone not exceeding a preset distance. The temporary relay location refers to the location of the temporarily hovering UAV relay node. Its selection principle is that the location can establish a communication link with the UAV within the signal blind zone, and simultaneously establish a communication link with the ground communication station or other relay stations, thus forming a communication link between the ground communication station, the temporary relay, and the inspection UAV. The distance between the temporary relay location and the signal blind zone does not exceed a preset distance (e.g., 200 meters) to ensure that the signal from the temporary relay can penetrate the edge of the signal blind zone and cover the UAV within it. When determining the temporary relay location, a communication reachability analysis can be performed based on a 3D model to screen candidate points that can communicate with both the path to the signal blind zone and existing communication nodes (such as ground communication stations or other relay stations). The point closest to the signal blind zone is then selected as the temporary relay location.

[0077] During drone inspections, at least one drone is controlled to hover at a temporary relay position to provide temporary relay functionality. This temporary relay drone can be a dedicated relay drone or a drone temporarily switching roles from the inspection task. When the inspection drone enters a signal blind spot, the temporary relay drone receives its transmitted data and forwards it to the ground communication station, or forwards instructions from the ground communication station to the inspection drone, thereby maintaining communication. After the inspection drone leaves the signal blind spot, the temporary relay drone can return to base or enter standby mode.

[0078] The above method provides an emergency solution when basic communication constraints cannot be met. When conventional relay solutions cannot completely eliminate communication blind spots due to extreme terrain limitations, temporary relay drones can be deployed as a supplement to provide on-demand, mobile relay services to signal blind spots. This temporary relay solution not only solves the communication guarantee problem in extreme situations, but its flexibility also allows relay resources to be precisely deployed to the areas most in need, avoiding the resource waste caused by deploying a large number of fixed relay stations to cover extremely small blind spots.

[0079] This disclosure also provides a communication relay configuration device for an inspection drone. (See reference...) Figure 7 As shown, the communication relay configuration device 700 includes: The terrain information processing module 710 is configured to collect terrain information of the UAV inspection area and build a three-dimensional model based on the terrain information; the inspection area includes the hydropower station and its surrounding area. The first signal coverage space determination module 720 is configured to determine the first signal coverage space of the ground communication station in the three-dimensional model based on information from the UAV ground communication station. The initial relay scheme determination module 730 is configured to determine the inspection path of the UAV in the three-dimensional model. If there is a non-communication path outside the first signal coverage space in the inspection path, an initial relay scheme that satisfies the basic communication constraints is generated based on the non-communication path. The basic communication constraints are: the second signal coverage space corresponding to the relay scheme contains the non-communication path. The optimization function construction module 740 is configured to construct optimization functions based on the communication quality and deployment cost of the relay scheme; The final relay scheme determination module 750 is configured to iteratively optimize the initial relay scheme using the optimization function under the basic communication constraints to obtain the final relay scheme, so as to configure the relay station for UAV communication according to the final relay scheme.

[0080] In one implementation, the step of iteratively optimizing the initial relay scheme using an optimization function to obtain a final relay scheme includes: performing communication simulation on the initial relay scheme; determining the communication quality of the initial relay scheme based on the communication simulation results; and obtaining the deployment cost of the initial relay scheme; substituting the communication quality and deployment cost corresponding to the initial relay scheme into the optimization function to calculate the optimization function value corresponding to the initial relay scheme; iteratively optimizing the initial relay scheme with the goal of maximizing the optimization function value; and determining the currently optimized relay scheme as the final relay scheme when a first preset condition is met.

[0081] In one implementation, the optimization function is: ; Where Opt() represents the optimization function; w1, w2, and w3 represent the weights in the optimization function; relay k Represents relay scheme k; route i Represents reference point i on the inspection path; signal(route) i relay k) represents the communication quality of reference point i under relay scheme k; min(signal(route) i relay k )) represents the minimum communication quality of each reference point under relay scheme k; cost(relay) k ) represents the deployment cost of relay scheme k.

[0082] In one embodiment, the device is further configured to: divide the inspection area into multiple sub-areas based on the inspection targets within the inspection area, with different sub-areas having different inspection targets; divide the relay scheme k into multiple relay segments based on the multiple sub-areas, and determine the weight corresponding to each relay segment based on the inspection target corresponding to each relay segment; calculate the optimization function value of each relay segment using the weight corresponding to each relay segment and based on the optimization function, and obtain the optimization function value of the relay scheme k by combining the optimization function values ​​of each relay segment.

[0083] In one embodiment, substituting the communication quality and deployment cost corresponding to the initial relay scheme into the optimization function to calculate the optimization function value corresponding to the initial relay scheme includes: determining the terrain evaluation value of the initial relay scheme based on the terrain features of the relay locations in the initial relay scheme; the terrain features include height, flatness, and geological type; and substituting the communication quality, deployment cost, and terrain evaluation value corresponding to the initial relay scheme into the optimization function to determine the optimization function value corresponding to the initial relay scheme.

[0084] In one implementation, generating an initial relay scheme that satisfies basic communication constraints based on the absence of a communication path includes: expanding the absence of a communication path into a first region; selecting a second region that satisfies a second preset condition within the first region; determining one or more relay locations within the second region; forming one or more initial relay schemes based on the one or more relay locations; and if multiple initial relay schemes are obtained, using the optimization function to select the optimal initial relay scheme from the multiple initial relay schemes.

[0085] In one embodiment, determining one or more relay locations within the second area and forming one or more initial relay schemes based on the one or more relay locations includes: dividing the second area into multiple relay areas based on relay communication distance and the distribution characteristics of the second area; determining at least one relay location within each relay area; and combining the relay locations in different relay areas to obtain one or more initial relay schemes.

[0086] In one embodiment, the device is further configured to: when the inspection target of the UAV changes, construct a loss function based on the new inspection target, the final relay scheme, and the inspection path; and use the loss function to iteratively update the inspection path to obtain a new inspection path.

[0087] In one implementation, the loss function is: ; Where Loss() represents the loss function; α, β, and γ represent the weights of the loss function; route0 represents the initial inspection path, route m Indicates the inspection path m; route 0,i Represents the reference point i on the initial inspection path, route m,i Dis represents the reference point i on the inspection path m. m,i ,route 0,i The distance between reference point i on the initial inspection path and reference point i on the inspection path m is represented by ; target represents the new inspection target, dis(route) m `,target)` represents the distance between the inspection path `m` and the new inspection target; `relay` represents the distance between the inspection path `m` and the new inspection target. f This represents the final relay scheme; signal(route) m,i, relay f ) represents the communication quality of reference point i on the inspection path m under the final relay scheme.

[0088] In one embodiment, the device is further configured to: after configuring relay stations for UAV communication according to the final relay scheme, generate a spectral fingerprint feature for each relay station; during UAV inspection, collect real-time spectrum data through each relay station; when the deviation between the real-time spectrum data and the spectral fingerprint feature exceeds a preset threshold, control the relay station to switch to an interference-free frequency or the weakest interference frequency in the available frequency list, and adjust the antenna beam direction based on the pilot signal of the communication object to maintain the communication link by utilizing the obstacle diffraction path or reflection path.

[0089] The specific details of each part of the above-mentioned device have been described in detail in the method section of the implementation plan. For any undisclosed details, please refer to the implementation plan of the method section, and therefore will not be repeated here.

[0090] It should be noted that although several modules or units for the device used to perform actions have been mentioned in the detailed description above, this division is not mandatory. In fact, according to exemplary embodiments of this disclosure, the features and functions of two or more modules or units described above can be embodied in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided and embodied by multiple modules or units.

[0091] This disclosure also provides a computer program product. The computer program product includes a computer program that, when executed by a processor, implements the method steps of various exemplary embodiments of this disclosure.

[0092] In one implementation, the computer program product can be a tangible product, such as a computer-readable storage medium storing a computer program. The readable storage medium can be based on electrical, magnetic, optical, electromagnetic, infrared, or other signals, and includes, but is not limited to: Random Access Memory (RAM), Read-Only Memory (ROM), magnetic tape, floppy disk, flash memory, Hard Disk Drive (HDD), Solid State Disk (SSD), etc. For example, the computer program product can be a non-volatile storage medium storing a computer program, such as read-only memory, NAND flash memory, etc.

[0093] In one implementation, the computer program product can be an intangible product. For example, the computer program product can be a virtual digital product, such as an executable file or installation package containing a computer program.

[0094] Computer program code can be written in one or more programming languages. Examples of programming languages ​​include C, Java, and C++. Program code can execute entirely on the user's computing device, partially on the user's computing device, or as a standalone software package. It can also execute partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server. In cases involving remote computing devices, the remote computing device can be connected to the user's computing device via any type of network, such as a Local Area Network (LAN) or a Wide Area Network (WAN), or it can be connected to an external computing device (e.g., via an internet connection provided by a mobile network operator).

[0095] Computer programs can be carried or transmitted via signals such as electrical, magnetic, optical, electromagnetic, and infrared rays. Electronic devices can convert the signals carrying computer programs into digital signals, thereby running the computer programs. When a computer program runs on an electronic device, its code is used to cause the electronic device to execute (more specifically, to be executed by the processor of the electronic device) the method steps of various embodiments of this disclosure, such as... Figure 1 The method and steps.

[0096] Implementing the above methods and steps through computer programs achieves the following technical effects: Firstly, by performing 3D modeling and signal coverage analysis of the terrain information of the hydropower station and its surrounding area, the impact of terrain on UAV communication can be predicted more accurately, identifying communication-deprived paths. Based on this fundamental communication constraint of covering communication-deprived paths, an initial relay scheme is generated and iteratively optimized to ensure that the final configured relay station can resolve communication blind spots during UAV inspections and guarantee communication quality. Secondly, by constructing an optimization function that considers factors such as communication quality and deployment cost, and using this function to iteratively optimize the relay scheme, the final relay scheme achieves high communication quality and low deployment cost, meeting the actual needs of the project.

[0097] This disclosure also provides an electronic device. The electronic device includes a processor and a memory. The memory stores executable instructions for the processor, such as computer programs. The processor executes the executable instructions to perform the method steps of various exemplary embodiments of this disclosure.

[0098] The following is for reference. Figure 8 The electronic device is illustrated by way of a general-purpose computing device. It should be understood that... Figure 8 The electronic device 800 shown is merely an example and should not be construed as limiting the functionality or scope of this disclosure.

[0099] like Figure 8 As shown, the electronic device 800 may include: a processor 810, a memory 820, a bus 830, an I / O (input / output) interface 840, and a network adapter 850.

[0100] Memory 820 may include volatile memory, such as RAM 821 and cache unit 822, and may also include non-volatile memory, such as ROM 823. Memory 820 may also include one or more program modules 824, such program modules 824 including, but not limited to, an operating system, one or more application programs, other program modules, and program data. Each or some combination of these examples may include an implementation of a network environment. For example, program module 824 may include the modules in the above-described device.

[0101] The processor 810 may include one or more processing units, such as an AP (Application Processor), a modem processor, a GPU (Graphics Processing Unit), an ISP (Image Signal Processor), a controller, an encoder, a decoder, a DSP (Digital Signal Processor), a baseband processor, and / or an NPU (Neural-Network Processing Unit).

[0102] The processor 810 can be used to execute executable instructions stored in the memory 820 to perform method steps of various embodiments of this disclosure, such as... Figure 1 The method and steps.

[0103] By executing the above method steps through processor 810, the following technical effects are achieved: Firstly, by performing three-dimensional modeling and signal coverage space analysis of the terrain information of the hydropower station and its surrounding area, the impact of terrain on UAV communication can be predicted more accurately, and communication-free paths can be identified. Based on the fundamental communication constraint of covering communication-free paths, an initial relay scheme is generated and iteratively optimized to ensure that the final configured relay station can solve the communication blind spot problem during UAV inspections and guarantee communication quality. Secondly, by constructing an optimization function that considers factors such as communication quality and deployment cost, and using this function to iteratively optimize the relay scheme, the final relay scheme achieves high communication quality and low deployment cost, meeting the actual needs of the project.

[0104] Bus 830 is used to connect different components of electronic device 800 and may include data bus, address bus and control bus.

[0105] Electronic device 800 can communicate with one or more external devices 900 (such as keyboard, mouse, external controller, etc.) through I / O interface 840.

[0106] Electronic device 800 can communicate with one or more networks via network adapter 850. For example, network adapter 850 can provide mobile communication solutions such as 3G / 4G / 5G, or wireless communication solutions such as wireless LAN, Bluetooth, and near-field communication. Network adapter 850 can communicate with other modules of electronic device 800 via bus 830.

[0107] In one embodiment, the electronic device 800 further includes a display for displaying a graphical user interface.

[0108] although Figure 8 As not shown in the diagram, other hardware and / or software modules may also be configured in the electronic device 800, including but not limited to: microcode, device drivers, redundant processors, external disk drive arrays, RAID (Redundant Arrays of Independent Disks) systems, tape drives, and data backup storage systems.

[0109] As can be seen from the above, the technical solutions disclosed herein can be implemented as methods, apparatus, systems, computer program products, storage media, electronic devices, etc. Those skilled in the art will understand that various aspects of this disclosure can be specifically implemented in the following forms: a completely hardware implementation, a completely software implementation (including firmware, microcode, etc.), or an implementation combining hardware and software aspects. Exemplarily, these three forms can be referred to as "circuit," "module," and "system," respectively.

[0110] It should be understood that this disclosure is not limited to the specific methods, steps, or structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. Those skilled in the art will readily conceive of other embodiments based on the specific implementations provided in this disclosure. Therefore, the specific implementations provided in this disclosure are merely exemplary, and the scope and spirit of this disclosure are indicated by the claims, and should cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary technical means in the art not disclosed in this disclosure.

Claims

1. A communication relay configuration method for an inspection drone, characterized in that, The method includes: Collect terrain information of the area inspected by the drone, and build a three-dimensional model based on the terrain information; the inspection area includes the hydropower station and its surrounding area. Based on the information from the UAV ground communication station, the first signal coverage space of the ground communication station is determined in the three-dimensional model; In the three-dimensional model, the inspection path of the UAV is determined. If there is a non-communication path outside the first signal coverage space in the inspection path, an initial relay scheme that satisfies the basic communication constraints is generated based on the non-communication path. The basic communication constraints are: the second signal coverage space corresponding to the relay scheme contains the non-communication path. An optimization function is constructed based on the communication quality and deployment cost of the relay scheme. Under the basic communication constraints, the initial relay scheme is iteratively optimized using the optimization function to obtain the final relay scheme, and relay stations for UAV communication are configured according to the final relay scheme.

2. The communication relay configuration method for the inspection drone according to claim 1, characterized in that, The step of iteratively optimizing the initial relay scheme using an optimization function to obtain the final relay scheme includes: A communication simulation is performed on the initial relay scheme. Based on the communication simulation results, the communication quality of the initial relay scheme is determined, and the deployment cost of the initial relay scheme is obtained. Substitute the communication quality and deployment cost corresponding to the initial relay scheme into the optimization function to calculate the optimization function value corresponding to the initial relay scheme; The initial relay scheme is iteratively optimized with the goal of maximizing the optimization function value. When the first preset condition is met, the current optimized relay scheme will be determined as the final relay scheme.

3. The communication relay configuration method for the inspection drone according to claim 2, characterized in that, The optimization function is: ； Where Opt() represents the optimization function; w1, w2, and w3 represent the weights in the optimization function; relay k Represents relay scheme k; route i Represents reference point i on the inspection path; signal(route) i relay k ) represents the communication quality of reference point i under relay scheme k; min(signal(route) i relay k )) represents the minimum communication quality of each reference point under relay scheme k; cost(relay) k ) represents the deployment cost of relay scheme k.

4. The communication relay configuration method for the inspection drone according to claim 3, characterized in that, The method further includes: Based on the inspection targets within the inspection area, the inspection area is divided into multiple sub-areas, with different sub-areas having different inspection targets. The relay scheme k is divided into multiple relay segments according to the multiple sub-regions, and the weight of each relay segment is determined according to the inspection target corresponding to each relay segment. The optimization function value of relay scheme k is obtained by using the weight corresponding to each relay segment and calculating the optimization function value of each relay segment based on the optimization function.

5. The communication relay configuration method for the inspection drone according to claim 2, characterized in that, The step of substituting the communication quality and deployment cost corresponding to the initial relay scheme into the optimization function to calculate the optimization function value corresponding to the initial relay scheme includes: Based on the terrain features of the relay locations in the initial relay scheme, the terrain evaluation value of the initial relay scheme is determined; the terrain features include height, flatness, and geological type. The communication quality corresponding to the initial relay scheme, the deployment cost of the initial relay scheme, and the terrain evaluation value of the initial relay scheme are input into the optimization function to determine the optimization function value corresponding to the initial relay scheme.

6. The communication relay configuration method for the inspection drone according to claim 1, characterized in that, The step of generating an initial relay scheme that satisfies the basic communication constraints based on the absence of a communication path includes: The no-communication-path area is expanded into a first region, and a second region that meets the second preset condition is selected from the first region. In the second area, one or more relay locations are determined, and one or more initial relay schemes are formed based on the one or more relay locations; If multiple initial relay schemes are obtained, the optimal initial relay scheme is selected from the multiple initial relay schemes using the optimization function.

7. The communication relay configuration method for the inspection drone according to claim 6, characterized in that, The step of determining one or more relay locations within the second area and forming one or more initial relay schemes based on the one or more relay locations includes: The second region is divided into multiple relay regions based on the relay communication distance and the distribution characteristics of the second region; Identify at least one relay location within each relay area; By combining relay locations within different relay areas, one or more initial relay schemes can be obtained.

8. The communication relay configuration method for the inspection drone according to claim 1, characterized in that, The method further includes: When the inspection target of the UAV changes, a loss function is constructed based on the new inspection target, the final relay scheme, and the inspection path. The inspection path is iteratively updated using the loss function to obtain a new inspection path.

9. The communication relay configuration method for the inspection drone according to claim 8, characterized in that, The loss function is: ； Where Loss() represents the loss function; α, β, and γ represent the weights of the loss function; route0 represents the initial inspection path, route m Indicates the inspection path m; route 0,i Represents the reference point i on the initial inspection path, route m,i Dis(route) represents the reference point i on the inspection path m. m,i ,route 0,i The distance between reference point i on the initial inspection path and reference point i on the inspection path m is represented by ; target represents the new inspection target, dis(route) m (,target) represents the distance between the inspection path m and the new inspection target; relay f This represents the final relay scheme; signal(route) m,i, relay f ) represents the communication quality of reference point i on the inspection path m under the final relay scheme.

10. The communication relay configuration method for an inspection drone according to any one of claims 1 to 9, characterized in that, After configuring the relay station for UAV communication according to the final relay scheme, the method further includes: Generate spectral fingerprint features for each relay station; During the UAV inspection process, real-time spectrum data is collected through each relay station. When the deviation between the real-time spectrum data and the spectrum fingerprint features exceeds a preset threshold, the relay station is controlled to switch to an interference-free frequency or the weakest interference frequency in the available frequency list. Based on the pilot signal of the communication object, the antenna beam direction is adjusted to maintain the communication link by utilizing the obstacle diffraction path or reflection path.

11. A computer program product, characterized in that, The invention includes a computer program that, when executed by a processor, implements the communication relay configuration method for the inspection drone as described in any one of claims 1 to 10.

12. An electronic device, characterized in that, include: Processor and memory; The memory is used to store executable instructions of the processor; the processor is configured to implement the communication relay configuration method of the inspection UAV according to any one of claims 1 to 10 by executing the executable instructions.

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