Unmanned aerial vehicle airborne access method and system based on double-link ad hoc network

Abstract

The invention discloses an unmanned aerial vehicle airborne access method and system based on a double-link ad hoc network, and belongs to the technical field of communication networks. Carrying out equipment type selection and configuration; network deployment and debugging; unmanned aerial vehicle task execution and data transmission; according to the unmanned aerial vehicle airborne access method and system based on the double-link ad hoc network, a power grid professional unmanned aerial vehicle airborne high-speed ad hoc network access method based on 1.4 G networking access and 5.8 G networking return can significantly improve the communication efficiency, real-time performance and anti-interference capability of an unmanned aerial vehicle cluster; high-speed and stable data transmission between the unmanned aerial vehicle and a ground station or other unmanned aerial vehicles is realized, and the requirements of complex applications such as power grid inspection are met; by combining the advantages of two frequency bands of 1.4 G and 5.8 G, high-speed and stable data transmission is realized, and the efficiency and safety of power grid operation and the communication efficiency are improved; and by using 1.4 G and 5.8 G networking, the traffic fee is 0, and the traffic fee is reduced.

Description

Technical Field

[0001] The present invention belongs to the technical field of communication networks, and in particular relates to an unmanned aerial vehicle airborne access method and system based on a dual-link ad hoc network. Background Art

[0002] With the continuous expansion of the scale of power grids and the increase in the complexity of lines, traditional inspection methods face problems such as low efficiency and many safety hazards. Drone inspection has become a new choice to solve this problem with its high efficiency, accuracy and flexibility. Drones are equipped with high-definition cameras, thermal imagers and AI recognition algorithms, which can comprehensively and accurately detect abnormal conditions of power lines and equipment, and improve inspection efficiency and accuracy. Drone inspection has been widely used in inspection objects such as transmission lines, substations, transmission towers and distribution facilities to ensure the stability and safety of power supply. With the continuous advancement of technology, drone inspection is developing in a more intelligent and automated direction, providing strong support for the digital transformation of the power industry. However, due to the complexity and dynamic nature of the power grid environment, drone communication and data transmission face many challenges; traditional communication methods cannot meet the needs of high-speed and stable data transmission.

[0003] There are various existing communication networking methods for drone swarms, such as narrowband data radio, 4G / 5G, Wi-Fi, etc. However, these methods have many shortcomings in the high-speed, high-dynamic, and long-distance communication of drone swarms.

[0004] Communication distance limitation: Communication methods such as 4G / 5G, Wi-Fi or Bluetooth have certain limitations on communication distance. For example, the Wi-Fi point-to-point communication distance generally does not exceed 500 meters, which affects the coverage of drone inspections.

[0005] Bandwidth and latency issues: Due to limited bandwidth, the transmitted image may not be clear enough and there may be high latency, which affects the efficiency and accuracy of real-time inspections;

[0006] Cost issue: Although 4G / 5G technology provides broader application prospects for drone inspections, 5G traffic charges may become a cost barrier to its promotion, especially in scenarios where drones need to be used on a large scale and for a long time. The high traffic costs may discourage some companies. Therefore, it is necessary to develop a new drone airborne access method and system based on dual-link self-organizing networks to solve existing problems. Summary of the invention

[0007] The purpose of the present invention is to provide a method and system for unmanned aerial vehicle airborne access based on a dual-link ad hoc network to solve the problem of being unable to meet the demand for high-speed and stable data transmission.

[0008] To achieve the above object, the present invention provides the following technical solution: a method for airborne access of a UAV based on a dual-link ad hoc network, comprising:

[0009] System planning and design;

[0010] Equipment selection and configuration;

[0011] Network deployment and debugging;

[0012] UAV mission execution and data transmission.

[0013] Preferably, the system planning and design includes: designing a network architecture among drones, networking nodes, and a central control platform, and calculating an access distance between drones and networking nodes.

[0014] Preferably, the network deployment and system debugging include: deploying networking nodes according to the grid coverage area and the UAV flight route, and planning the frequency through the same-frequency interference protection strategy;

[0015] Dynamically adjust network topology and optimize MAC protocol and routing protocol according to its own location and mobility status.

[0016] Preferably, the co-channel interference protection strategy includes: power control, time slot division, adaptive adjustment, topology optimization, and multi-path selection;

[0017] Power control: Each networking node adaptively adjusts the node's transmission power according to the distance between nodes, signal strength and receiving sensitivity;

[0018] Time slot division: allocate transmission time slots between nodes;

[0019] Adaptive adjustment: The node monitors the intensity fluctuation of external interference signals in real time, adjusts the transmission power and optimizes channel selection based on the monitoring data;

[0020] Topology optimization: connect nodes that are far away and nodes that are close together;

[0021] Multi-path selection: Provides multi-path selection function to select the best path to transmit data.

[0022] Preferably, the power control includes: an adaptive transmit power adjustment algorithm,

[0023] Input parameters include:

[0024] RSSI_current: represents the current received signal strength indication;

[0025] RSSI_target: represents the target received signal strength indication;

[0026] Interference_level: represents the current interference level;

[0027] Path_loss: represents the estimated path loss;

[0028] P_max: represents the maximum allowed transmit power;

[0029] P_min: represents the minimum allowed transmit power;

[0030] P_current: represents the current transmit power;

[0031] Step_size: represents the transmit power adjustment step size;

[0032] Max_iterations: represents the maximum number of iterations;

[0033] Output parameters include:

[0034] P_adjusted: represents the adjusted transmit power

[0035] The specific steps include:

[0036] Step 121, initialization:

[0037] Set the iteration counter iteration = 0;

[0038] Set the adjusted transmit power P_adjusted = the current transmit power P_current as the initial value;

[0039] Step 122, calculate the signal strength deviation: ΔRSSI = RSSI_target - RSSI_current;

[0040] Step 123, calculate the interference adjustment factor: Where Max_Interference is the defined maximum interference level;

[0041] Step 124, calculate the path loss adjustment factor:

[0042] Step 125, calculate the transmit power adjustment amount: P_adjustment=ΔRSSI*Interference_factor*Path_loss_factor*Step_size;

[0043] Step 126: Apply the transmit power adjustment amount;

[0044] If P_adjusted + P_adjustment > P_max, then P_adjusted = P_max;

[0045] If P_adjusted + P_adjustment < P_min, then P_adjusted = P_min;

[0046] Otherwise, P_adjusted = P_adjusted + P_adjustment;

[0047] Step 127. Check the number of iterations:

[0048] If iteration < Max_iterations, then iteration = iteration + 1 and return to Step 122;

[0049] Otherwise, end the algorithm and output P_adjusted;

[0050] Step 128. Return the adjusted transmission power P_adjusted.

[0051] Preferably, the division of the time slot includes: dividing a channel into multiple time slices, and each time slice is a time slot;

[0052] Set the frame length to 256 bit, which is divided into 32 time slots, each time slot is 8 bit, and the transmission rate is 64 kbps.

[0053] Preferably, the multi-path selection includes:

[0054] In the initialization stage, collect the information of all nodes in the network, and establish a preliminary routing table according to the node information to record the possible paths;

[0055] In the path selection stage, based on the signal strength, hop count, and delay, calculate the weights of each path, and select the best path as the main path for data transmission;

[0056] In the dynamic adjustment stage, monitor the network status in real time, and dynamically update the routing table and adjust the path selection according to the changes in the network status.

[0057] Preferably, the method further includes: security and reliability guarantee measures:

[0058] The airborne equipment of the UAV adopts the authentication of the MAC white list, and the networking node equipment uses the MAC address and serial number as the white list information.

[0059] Preferably, the calculation of the access distance between the airborne equipment of the UAV and the node equipment includes:

[0060] Calculate the receiving power Pr and path loss Lp required by the receiver. The formula for receiving power Pr is: Pr=Pt+Gt+Gr-Lp; where Pt represents the transmit power, which is the original power transmitted by the wireless device; Gt represents the transmit antenna gain, which is the signal gain of the transmit antenna in a specific direction relative to a non-directional antenna, such as an omnidirectional antenna; Gr represents the receive antenna gain, which is the signal gain of the receive antenna in a specific direction relative to an non-directional antenna; Lp represents path loss: the energy loss caused by factors such as air absorption, scattering, and multipath effects in the process of signal propagation from the transmitter to the receiver.

[0061] Determine the path loss Lp and calculate the communication distance;

[0062] Calculate the path loss LP; Lp = Pt + Gt + Gr - Pr;

[0063] Calculate the maximum distance and use the FSPL formula to calculate the distance d:

[0064]

[0065] d represents the distance between the transmitter and the receiver in meters (m);

[0066] f represents the frequency of the signal, in Hertz (Hz);

[0067] c represents the speed of light, which is approximately 3×10 8 m / s.

[0068] The present invention further provides an unmanned aerial vehicle airborne access system based on a dual-link ad hoc network, comprising:

[0069] UAV onboard equipment, including 1.4G communication equipment;

[0070] Networking nodes; including ground 1.4G and 5.8G dual-mode base stations, used to receive data transmitted through the 1.4G network of drone-mounted equipment;

[0071] The central control platform includes 5.8G communication equipment and receives the networking node equipment data through the 5.8G network.

[0072] The technical effects and advantages of the present invention are as follows: the airborne access method and system of unmanned aerial vehicles based on dual-link self-organizing network, and the airborne high-speed self-organizing network access method of power grid professional unmanned aerial vehicles based on 1.4G networking access and 5.8G networking backhaul can significantly improve the communication efficiency, real-time performance and anti-interference ability of unmanned aerial vehicle clusters, realize high-speed and stable data transmission between unmanned aerial vehicles and ground stations or other unmanned aerial vehicles, and meet the needs of complex applications such as power grid inspection; by combining the advantages of the two frequency bands of 1.4G and 5.8G, high-speed and stable data transmission is realized, and the efficiency, safety and communication efficiency of power grid operations are improved; using 1.4G and 5.8G networking, the traffic fee is 0, which reduces the traffic fee; dual-link multi-hop relay networking reduces the delay and improves the real-time performance of data transmission; adopts advanced anti-interference technology to ensure the communication stability in complex electromagnetic environments and improve the anti-interference ability; supports the dynamic access and exit of unmanned aerial vehicle nodes, and the network topology structure is flexible and variable, adapts to different application scenarios, and enhances flexibility; is particularly suitable for emergency information services in major disasters or military demand scenarios, and improves the mission success rate. In complex environments such as power grid inspections, the emergency response capability is improved, and efficient, stable, economical and secure communication solutions are achieved. BRIEF DESCRIPTION OF THE DRAWINGS

[0073] Figure 1 A schematic diagram of the implementation process of the dual-link networking access method of the present invention;

[0074] Figure 2 It is a schematic diagram of the dual-link networking access method for unmanned aerial vehicles of the present invention. DETAILED DESCRIPTION

[0075] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0076] The present invention provides Figure 1 A flow chart of a method for high-speed self-organizing network access of a power grid professional UAV based on 1.4G network access and 5.8G network backhaul is shown in the figure, which is used for a UAV communication method based on wireless network network inspection, and is applied to UAV inspection, including the following steps:

[0077] S10: System planning and design;

[0078] S11: Equipment selection and configuration;

[0079] S12: Network deployment and debugging;

[0080] S13: UAV mission execution and data transmission;

[0081] S14: Safety and reliability assurance;

[0082] In step S10, the system is planned and designed to clarify the main tasks of the power grid professional drone, such as power line inspection and troubleshooting, as well as the real-time, security, and reliability requirements of data transmission; based on the results of the demand analysis, the 1.4G frequency band is selected as the access frequency band between the drone and the networking node, and the 5.8G frequency band is selected as the backhaul frequency band between the networking node and the central control platform, and the network architecture between the drone, networking node, and central control platform is designed, including the network topology, communication protocol, data format, etc.

[0083] In step S11, select appropriate equipment and configuration, select UAV airborne communication equipment that supports 1.4G, including transceivers, antennas, etc., and ensure that these devices have high-speed data transmission capabilities, low latency characteristics and anti-interference capabilities. At the same time, the UAV is configured with high-definition cameras, infrared thermal imagers and other sensor equipment according to mission requirements; select networking node equipment with good signal coverage and data processing capabilities, and configure corresponding transceivers and antennas to support 1.4G and 5.8G frequency band communications; select an intelligent center control platform, configure high-performance servers and data processing equipment to support real-time processing and analysis of received data, and can also send control instructions to the UAV to guide it to perform the next step.

[0084] In step S12, network deployment and system debugging are performed. According to the grid coverage area and the flight route of the drone, the networking nodes are reasonably deployed to ensure that the drone can stably access the network during flight. Reasonable frequency planning is performed for the 1.4G and 5.8G frequency bands to avoid co-frequency interference and improve communication quality; the networking network is optimized and adjusted, and the drone nodes dynamically adjust the network topology according to their own position and mobility status to ensure the continuity and stability of communication; at the same time, the QoS of data transmission is guaranteed by optimizing the MAC protocol and routing protocol.

[0085] By properly designing the location and connection method of nodes, interference and conflicts between nodes can be reduced. That is, nodes that are farther away are connected together, and nodes that are closer are connected together, so as to reduce the spread of interference and the occurrence of conflicts; that is to say, in the entire coverage network, a certain node is connected to the nearest node around it as much as possible. The node MAC and location information in the routing table are related, similar to the way of forming gangs and holding groups. On a straight line, the algorithm will plan the points within 0 to 3 meters to give priority to communication between two points, and the points of 7 to 10 meters will be planned together to optimize communication, which can ensure that the same-frequency signals floating from a distance will not interfere with the entire network; finally, network debugging and equipment joint debugging are carried out to ensure that the communication links between drones, networking nodes, and central control platforms are unimpeded, and data transmission is stable and reliable.

[0086] Corresponding protection strategies have been developed for co-frequency interference between nodes. The protection strategies for co-frequency interference mainly include power control, time slot division, adaptive adjustment, topology optimization, multi-path selection and other methods for protection, which can effectively solve the interference and conflict problems between nodes in wireless networking, thereby improving network performance and enhancing network throughput.

[0087] Power control: Each networking node adaptively adjusts the node's transmission power according to the distance between nodes, signal strength and receiving sensitivity to achieve optimal performance.

[0088] The power control uses the following adaptive transmit power adjustment algorithm, and the following parameters are input:

[0089] RSSI_current: current received signal strength indicator, measured by the base station;

[0090] RSSI_target: target received signal strength indication, determined by network planning or dynamic adjustment strategy;

[0091] Interference_level: current interference level, measured by the node device;

[0092] Path_loss: estimated path loss, based on propagation model or historical data);

[0093] P_max: maximum allowed transmit power, limited by node device hardware and regulations;

[0094] P_min: minimum allowed transmit power, determined by node device hardware and network requirements;

[0095] P_current: current transmit power, maintained by the node device control software;

[0096] Step_size: transmit power adjustment step size, used to control the adjustment granularity;

[0097] Max_iterations: Maximum number of iterations, used to prevent the algorithm from infinite loop;

[0098] Output parameters:

[0099] P_adjusted: Adjusted transmit power;

[0100] Algorithm steps:

[0101] Step 121. Initialization:

[0102] Set the iteration counter iteration = 0;

[0103] Set P_adjusted = P_current as the initial value;

[0104] Step 122. Calculate the signal strength deviation: ΔRSSI = RSSI_target - RSSI_current;

[0105] Step 123. Calculate the interference adjustment factor: where Max_Interference is the maximum interference level defined by the system;

[0106] Step 124. Calculate the path loss adjustment factor:

[0107] Step 125. Calculate the transmit power adjustment amount: P_adjustment = ΔRSSI * Interference_factor * Path_loss_factor * Step_size;

[0108] Step 126. Apply the transmit power adjustment amount:

[0109] If P_adjusted + P_adjustment > P_max, then P_adjusted = P_max;

[0110] If P_adjusted + P_adjustment < P_min, then P_adjusted = P_min;

[0111] Otherwise, P_adjusted = P_adjusted + P_adjustment;

[0112] Step 127. Check the number of iterations:

[0113] If iteration < Max_iterations, then iteration = iteration + 1 and return to step 122;

[0114] Otherwise, end the algorithm and output P_adjusted;

[0115] Step 128. Return the adjusted transmit power P_adjusted.

[0116] Approximate the target received signal strength by iteratively adjusting the transmit power, taking into account the interference level and path loss; by limiting the number of iterations, it is possible to prevent the algorithm from looping infinitely when the target received signal strength cannot be reached.

[0117] Time slot division: In wireless networking, communication between nodes is carried out in a time-division manner. When multiple nodes send data simultaneously, conflicts may occur. By using the time slot division method and reasonably allocating the transmission time slots between nodes, conflicts can be avoided and network throughput can be improved. The division of time slots mainly relies on time-division multiplexing (TDM) technology, which divides a channel into multiple time slices, and each time slice is a time slot. For example, a frame with a length of 256 bits is divided into 32 time slots, each time slot is 8 bits, and the transmission rate is 64 kbps. The division of time slots ensures that multiple signals can be transmitted轮流 on the same channel, improving channel utilization.

[0118] Adaptive adjustment: The interference and conflict problems in wireless networking are dynamically changing, and the environmental conditions and signal strengths between nodes may change at any time. Therefore, adaptive algorithms and strategies are used to monitor and adjust the communication between nodes to improve network performance. Nodes continuously monitor the intensity fluctuations of external interference signals. According to the monitoring data, the transmission power is adjusted. At the same time, the channel selection is optimized to reduce interference and conflicts. Using historical data, the future interference trend is predicted and adjusted in advance to avoid performance degradation. The algorithm has the capabilities of monitoring, adjustment, prediction, and learning, enabling it to effectively handle the dynamic interference and conflict problems in wireless networking.

[0119] Topology optimization: By reasonably designing the positions and connection methods of nodes, interference and conflicts between nodes can be reduced. mainly by connecting nodes that are far apart and connecting nodes that are close together, thereby reducing the propagation of interference and the occurrence of conflicts.

[0120] Multi-path selection: Provide a multi-path selection function to select the best path in the network to transmit data, thereby reducing the impact of interference and conflicts. The following methods are used for multi-path selection:

[0121] 1. Initialization phase: collect information about all nodes in the network, including location, signal strength, etc. Based on the node information, establish a preliminary routing table and record possible paths;

[0122] 2. In the path selection phase, the weight of each path is calculated by considering factors such as signal strength, number of hops, and delay. Based on the weight, the best path is selected as the main path for data transmission;

[0123] 3. In the dynamic adjustment phase, the network status is monitored in real time, including node changes, signal fluctuations, etc. The routing table is dynamically updated and the path selection is adjusted according to the changes in the network status.

[0124] In step S13, the drone performs the task and transmits related data; the drone takes off according to the preset route, controls the handle or flies automatically, performs tasks such as power line inspection and troubleshooting, and transmits the collected images, videos and other data to the networking node in real time through the 1.4G network. After the networking node receives the video and image data transmitted by the drone, it transmits it back to the central control platform through the 5.8G network.

[0125] In step S14, measures to ensure safety and reliability are taken; the node equipment and drone-mounted equipment are embedded with the State Grid security encryption chip, and the access of all equipment must be verified by the security management platform before it can go online. The drone-mounted equipment uses MAC whitelist authentication, and the networking node equipment uses MAC address and serial number as whitelist information to ensure that other drones cannot illegally enter the data transmitted by the networking. The AES256 dynamic encryption mechanism is used to ensure data security. Design redundant backup mechanisms, such as backup base stations, backup communication links, etc., to deal with possible equipment failures or network interruptions. At the same time, real-time monitoring and troubleshooting are carried out to monitor drones, networking nodes, and central control platforms in real time, and potential problems are discovered and handled in a timely manner to ensure stable system operation.

[0126] Example 2

[0127] The present invention further provides Figure 2 The UAV airborne access system based on dual-link self-organizing network shown in the figure includes: Network architecture design:

[0128] The access layer uses the 1.4G frequency band to build an access network between drones and networking nodes. The advantages of the 1.4G frequency band mainly lie in its specialization, security, broadband characteristics and wide range of mobile applications. It is very suitable as an access frequency band for government-specific networks or specific industries such as power grids. Drones establish stable communication connections with networking nodes through the 1.4G network to transmit real-time data and control instructions; the nodes are ground base stations;

[0129] The backhaul layer uses the 5.8G frequency band to build a backhaul network between the networking nodes and the central control platform. The advantages of the 5.8G frequency band are reflected in its high transmission speed and low interference. The 5.8G frequency band supports the IEE E802.11ac wireless standard, the bandwidth can be increased to 40MHz or 80MHz or even higher, the transmission speed is increased to 1Gbps, and about 125MB of data can be transmitted per second. In addition, due to the high cost and less use of 5.8G equipment, its frequency band signal is pure and there is rarely any channel occupancy, which is suitable for application scenarios that require high bandwidth such as transmitting large amounts of data or high-definition video. The networking node transmits the received drone data back to the central control platform through the 5.8G network for further processing and analysis.

[0130] The hardware and software equipment includes:

[0131] UAV onboard equipment:

[0132] Drones must be equipped with 1.4G communication equipment, including transceivers, antennas, etc. These devices should have high-speed data transmission capabilities, low latency characteristics and anti-interference capabilities to ensure that the drone can communicate with the networking nodes stably and reliably during flight. Drones can also be equipped with sensor equipment such as high-definition cameras and infrared thermal imagers to collect real-time images and video information of the power grid. This information will be transmitted to the networking nodes through the 1.4G network. Airborne equipment can also be networked with networking node equipment in 1.4G, with flexible carrier bandwidth, supporting any network topology such as multi-point to multi-point and mesh grid.

[0133] Network node equipment:

[0134] The ground 1.4G and 5.8G dual-mode base station is responsible for receiving the data transmitted by the drone's 1.4G communication and transmitting it back to the central control platform through the 5.8G network. The networking nodes should have good signal coverage and data processing capabilities to ensure real-time transmission and processing of data.

[0135] The networking nodes have good coverage capabilities, and the access distance between the airborne equipment and the node equipment is calculated. For example, the base station with a transmission power of 4W + antenna gain is 8dBi, the terminal equipment with a transmission power of 0.5W + antenna gain is 2dBi, and the communication distance is calculated according to the space loss formula (the frequency of the equipment is 1.4GHz and the receiving sensitivity is -75dBm).

[0136] The following parameters are used: base station transmission power Pt: 4W = 36dBm, base station antenna gain Gt: 8dBi, terminal equipment transmission power Pt: 0.5W = 27dBm, terminal equipment antenna gain Gt: 2dBi, frequency f:

[0137] 1.4GHz=1.4×109Hz, receiving sensitivity Pr:-75dBm;

[0138] First, calculate the received power Pr and path loss Lp required by the receiver;

[0139] Receive power formula: Pr = Pt + Gt + Gr-Lp, where Pt represents the transmit power, which is the original power transmitted by the wireless device; Gt represents the transmit antenna gain, which is the signal gain of the transmit antenna in a specific direction relative to a non-directional antenna, such as an omnidirectional antenna; Gr represents the receive antenna gain, which is the signal gain of the receive antenna in a specific direction relative to an non-directional antenna; Lp represents the path loss: the energy loss caused by air absorption, scattering, multipath effect, etc. in the process of signal propagation from the transmitter to the receiver; in order to calculate the communication distance, we need to determine the path loss Lp;

[0140] To calculate the path loss LP, substitute the known values ​​into the formula:

[0141] For node devices to terminals:

[0142] Lp=Pt+Gt+Gr-Pr;

[0143] Lp = 36 + 8 + 2 + 75 = 121 dB;

[0144] For end-to-node devices:

[0145] Lp=Pt+Gt+Gr-Pr;

[0146] Lp = 27 + 2 + 8 + 75 = 112 dB;

[0147] Calculate the farthest distance, and then use the FSPL formula to calculate the distance d:

[0148] Lp=20log10(d)+20log10(f)+20log10(4π / C);

[0149] Substituting the known frequency f and speed of light c into the formula:

[0150] f = 1.4 × 10 9 Hz;

[0151] c≈3×10 8 m / s;

[0152] First calculate 20log10(f):

[0153] 20log10(f)=20log10(1.4×10 9 );

[0154] =20(log10(1.4)+log10(10 9 ));

[0155] =20(0.146+9);

[0156] =20×9.146;

[0157] =182.92dB;

[0158] Then calculate the constant term 20log10(4π / c):

[0159] 4π≈12.566;

[0160] 20log10(4π / 3×10 8 )≈20log10(12.566 / 3×10 8 )=20(log10(12.566)-log10(3×108))≈20(1.099-8.477)≈20×(-7.378)≈-147.56d B;

[0161] Combining all the parts, the calculation of the terminal to the node device is:

[0162] Substitute the path loss Lp = 112dB into the FSPL formula:

[0163] 112=20log10(d)+182.92-147.56

[0164] 112=20log10(d)+35.36

[0165] 20log10(d)=112-35.36

[0166] 20log10(d)=76.64

[0167] log10(d)=76.64 / 20=3.832

[0168] d≈103.832≈6723.57 meters

[0169] The final result is that the maximum communication distance from the drone's onboard equipment to the node equipment is about 6723.57 meters (about 6.72 kilometers).

[0170] Central control platform:

[0171] The central control platform further processes and analyzes the received data, including image recognition, fault diagnosis, etc. The central control platform can also send control instructions to the drone to guide it to perform the next operation.

[0172] Network access method:

[0173] After the UAV node and the networking node device are powered on, they are initialized through the 1.4G frequency band to complete network synchronization and parameter configuration. The networking node device sends networking instructions in the 1.4G frequency band, and the UAV node accesses the network according to the instructions to form a primary network. The UAV and the networking node device broadcast, exchange telemetry information and inter-machine collaborative information through the 1.4G frequency band. The UAV node dynamically adjusts the network topology according to its own position and mobility status to ensure the continuity and stability of communication.

[0174] In networking, each node is connected to multiple other nodes to form a multi-hop network. The network can self-organize to form the best path. When a node fails, the network can automatically find a new route. Due to the multi-hop feature, the network can achieve load balancing and avoid overloading a single node.

[0175] The layout is carried out according to actual needs, and the communication efficiency is improved and the bandwidth congestion is reduced through automatic multi-hop relay networking between nodes. At the same time, redundant links are also added to improve the fault tolerance and reliability of the network and reduce the impact of single point failures. At the same time, the network topology optimization method based on traffic engineering is adopted to dynamically adjust the network topology structure by monitoring and analyzing traffic patterns, reducing transmission delays and enhancing the real-time performance of data transmission.

[0176] Network backhaul method:

[0177] The power grid inspection data (such as video, images, location information, etc.) collected by the drone's onboard equipment is transmitted back to the central control platform at high speed through the 5.8G network. In complex terrain or beyond line of sight, multi-hop relay is automatically performed between nodes to ensure that the data can be transmitted back reliably.

[0178] Safety and reliability measures:

[0179] Advanced encryption technology and security protection measures are used to ensure data security and device security during communication.

[0180] Ensure the stable operation of the entire system by optimizing the network structure and improving the reliability of communication equipment;

[0181] Design redundant backup mechanisms to cope with possible equipment failures or network outages.

[0182] By optimizing the MAC protocol and routing protocol, the different requirements of various services on transmission delay, transmission rate, and transmission packet error rate are guaranteed, thereby ensuring the quality of data transmission.

[0183] Finally, it should be noted that the above is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, it is still possible for those skilled in the art to modify the technical solutions described in the aforementioned embodiments or to make equivalent substitutions for some of the technical features therein. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for airborne access of a UAV based on a dual-link ad hoc network, characterized in that: Including: System planning and design; Equipment selection and configuration; Network deployment and debugging; UAV mission execution and data transmission.

2. The method for accessing a drone onboard a dual-link ad hoc network according to claim 1, characterized in that: The system planning and design includes: designing the network architecture among the UAV, networking nodes, and the central control platform, and calculating the access distance between the UAV and the networking nodes.

3. The method for accessing a drone onboard a dual-link ad hoc network according to claim 1, characterized in that: The network deployment and system debugging include: deploying networking nodes according to the power grid coverage area and the UAV flight route, and planning frequencies through co-channel interference protection strategies; Dynamically adjusting the network topology structure according to its own position and movement state, and optimizing the MAC protocol and routing protocol.

4. The method for accessing a drone onboard a dual-link ad hoc network according to claim 3 is characterized in that: The co-channel interference protection strategies include: power control, time slot division, adaptive adjustment, topology optimization, and multi-path selection; Power control: Each networking node adaptively adjusts the transmission power of the node according to the distance, signal strength, and receiving sensitivity between nodes; Time slot division: Allocating the transmission time slots between nodes; Adaptive adjustment: Nodes monitor the intensity fluctuations of external interference signals in real time, and adjust the transmission power and optimize the channel selection according to the monitoring data; Topology optimization: Connecting nodes that are farther apart and connecting nodes that are closer together; Multi-path selection: Providing a multi-path selection function to select the best path to transmit data.

5. The method for airborne access of a UAV based on a dual-link ad hoc network according to claim 4, characterized in that: The power control includes: an adaptive transmit power adjustment algorithm: Input parameters include: RSSI_current: representing the current received signal strength indication; RSSI_target: representing the target received signal strength indication; Interference_level: representing the current interference level; Path_loss: representing the estimated path loss; P_max: representing the maximum allowable transmit power; P_min: representing the minimum allowable transmit power; P_current: representing the current transmit power; Step_size: representing the transmit power adjustment step size; Max_iterations: representing the maximum number of iterations; Output parameters include: P_adjusted: representing the adjusted transmit power The specific steps include: Step 121, Initialization: Set the iteration counter iteration = 0; Set the adjusted transmit power P_adjusted = the current transmit power P_current as the initial value; Step 122, Calculate the signal strength deviation: ΔRSSI = RSSI_target - RSSI_current; Step 123, calculate the interference adjustment factor: Where Max_Interference is the defined maximum interference level; Step 124, calculate the path loss adjustment factor: Step 125, Calculate the transmit power adjustment amount: P_adjustment = ΔRSSI * Interference_factor * Path_loss_factor * Step_size; Step 126. Apply the transmit power adjustment amount; If P_adjusted + P_adjustment > P_max, then P_adjusted = P_max; If P_adjusted + P_adjustment < P_min, then P_adjusted = P_min; Otherwise, P_adjusted = P_adjusted + P_adjustment; Step 127. Check the number of iterations: If iteration < Max_iterations, then iteration = iteration + 1 and return to Step 122; Otherwise, end the algorithm and output P_adjusted; Step 128. Return the adjusted transmit power P_adjusted.

6. The method for airborne access of a UAV based on a dual-link ad hoc network according to claim 4, characterized in that: The division of the time slots includes: dividing a channel into multiple time slices, and each time slice is a time slot; Set the frame length to 256 bit, which is divided into 32 time slots, each time slot is 8 bit, and the transmission rate is 64 kbps.

7. The method for accessing a drone onboard a dual-link ad hoc network according to claim 4, characterized in that: The multi-path selection includes: In the initialization phase, collect the information of all nodes in the network, and based on the node information, establish a preliminary routing table to record the possible paths; In the path selection phase, calculate the weights of each path based on the signal strength, hop count, and delay, and select the best path as the main path for data transmission; In the dynamic adjustment phase, monitor the network status in real time, and according to the changes in the network status, dynamically update the routing table and adjust the path selection.

8. The method for UAV airborne access based on dual-link ad hoc network according to any one of claims 1 to 7, characterized in that: The method further includes: security and reliability guarantee measures: The airborne equipment of the drone adopts the authentication of the MAC white list, and the networking node equipment uses the MAC address and serial number as the white list information.

9. The method for accessing a drone onboard a dual-link ad hoc network according to claim 2, 3 or 4, characterized in that: The calculation of the access distance between the airborne equipment of the drone and the node equipment includes: Calculate the required received power Pr of the receiver and the path loss Lp. The formula for the received power Pr is: Pr = Pt + Gt + Gr - Lp; where, Pt represents the transmit power; Gt represents the transmit antenna gain; Gr represents the receive antenna gain; Lp represents the path loss; Determine the path loss Lp and calculate the communication distance; Calculate the path loss LP; Lp = Pt + Gt + Gr - Pr; Calculate the maximum distance, and use the FSPL formula to calculate the distance d: d represents the distance between the transmitter and the receiver, and the unit is meter (m). f represents the frequency of the signal, and the unit is Hertz (Hz); c represents the speed of light, which is approximately 3×10 8 m / s.

10. An unmanned aerial vehicle airborne access system based on a dual-link ad hoc network, characterized in that: It includes: The airborne equipment of the drone; It includes the 1.4G communication equipment carried; Networking nodes; It includes the ground 1.4G and 5.8G dual-mode base stations for receiving the data transmitted by the 1.4G network of the airborne equipment of the drone; The central control platform includes the 5.8G communication equipment and receives the data of the networking node equipment through the 5.8G network.

Images