A method and system for unmanned aerial vehicle airborne access based on dual-link ad hoc network

Abstract

The application discloses a kind of unmanned aerial vehicle airborne access method and system based on double-link ad hoc network belongs to communication network technical field, including: system planning and design;Equipment selection and configuration;Network deployment and debugging;Unmanned aerial vehicle task execution and data transmission;The unmanned aerial vehicle airborne access method and system based on double-link ad hoc network based on 1.4G networking access and 5.8G networking backhaul power grid professional unmanned aerial vehicle airborne high-speed ad hoc network access method, can significantly improve the communication efficiency of unmanned aerial vehicle cluster, real-time and anti-interference ability, realize high-speed, stable data transmission between unmanned aerial vehicle and ground station or other unmanned aerial vehicle, meet the needs of complex applications such as power grid inspection;By combining the advantages of 1.4G and 5.8G two frequency bands, high-speed, stable data transmission is realized, the efficiency and safety and communication efficiency of power grid operation are improved;Using 1.4G and 5.8G networking, traffic fee is 0, reduces traffic expense.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of communication networks, and particularly relates to a UAV airborne access method and system based on a dual-link ad hoc network. BACKGROUND

[0002] With the continuous expansion of the power grid scale and the increase of line complexity, traditional inspection methods face problems such as low efficiency, many safety hazards, etc. UAV inspection has become a new choice to solve this problem with its efficient, accurate and flexible characteristics. UAVs equipped with high-definition cameras, thermal imagers and AI recognition algorithms can comprehensively and accurately detect abnormal conditions of power lines and equipment, improving inspection efficiency and accuracy. UAV inspection has been widely used in transmission lines, substations, transmission towers and distribution facilities, etc. to ensure the stability and safety of power supply. With the continuous progress of technology, UAV inspection is developing towards more intelligent and automated direction, providing strong support for the digital transformation of the power industry. However, due to the complexity and dynamics of the power grid environment, the communication and data transmission of UAVs face many challenges; traditional communication methods cannot meet the high-speed and stable data transmission requirements.

[0003] Existing UAV cluster communication networking methods are various, such as narrowband data radio, 4G / 5G, Wi-Fi, etc., but these methods have many shortcomings in high-speed, high-dynamic, long-distance communication of UAV clusters;

[0004] Communication distance limitation: 4G / 5G, Wi-Fi or Bluetooth communication methods have certain limitations in communication distance, such as Wi-Fi point-to-point communication distance generally does not exceed 500 meters, affecting the coverage of UAV inspection;

[0005] Bandwidth and latency issues: due to limited bandwidth, transmitted images may not be clear enough, and there is a high latency phenomenon, affecting the efficiency and accuracy of real-time inspection;

[0006] Cost issues: although 4G / 5G technology provides a broader application prospect for UAV inspection, 5G traffic fees may become a cost barrier to its promotion, especially in scenarios that require large-scale and long-term use of UAVs, high traffic fees may deter some enterprises; therefore, a new UAV airborne access method and system based on dual-link ad hoc network is needed to solve the existing problems. SUMMARY

[0007] The purpose of the present application is to provide a UAV airborne access method and system based on dual-link ad hoc network to solve the problem of not being able to meet the high-speed and stable data transmission requirements.

[0008] To achieve the above object, the present application provides the following technical scheme: a UAV airborne access method 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 task execution and data transmission.

[0013] Preferably, the system planning and design comprises: designing the network architecture among the UAV, the networking node and the central control platform, and calculating the access distance of the UAV and the networking node.

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

[0015] According to the position and movement state of itself, the network topology structure is dynamically adjusted, and the MAC protocol and the routing protocol are optimized.

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

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

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

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

[0020] Topology optimization: connect nodes with long distance to each other, and connect nodes with short distance to each other;

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

[0022] Preferably, the power control comprises: adaptive transmission power adjustment algorithm,

[0023] The input parameters comprise:

[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] Specific steps include:

[0036] Step 121, initialization:

[0037] Set iteration counter iteration = 0;

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

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

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

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

[0042] Step 125, calculate 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

[0046] Otherwise, P_adjusted=P_adjusted+P_adjustment;

[0047] Step 127. Check the iteration number:

[0048] If iteration

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

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

[0051] Preferably, the time slot division comprises: dividing a channel into multiple time slices, each time slice being a time slot.

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

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

[0054] In the initialization stage, information of all nodes in the network is collected, and a preliminary routing table is established according to the node information, recording possible paths.

[0055] In the path selection stage, the weights of paths are calculated based on signal strength, hop count, and delay, and the best path is selected as the main path for data transmission.

[0056] In the dynamic adjustment stage, the network state is monitored in real time, and the routing table is dynamically updated according to the network state changes, and the path selection is adjusted.

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

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

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

[0060] The receiving power Pr and the path loss Lp required by the computing receiver are calculated, and the formula of the receiving power Pr is: Pr=Pt+Gt+Gr-Lp, wherein Pt represents the transmitting power, the original power transmitted by the wireless device; Gt represents the transmitting antenna gain, the signal gain of the transmitting antenna in a specific direction relative to the non-directional antenna, such as an omnidirectional antenna; Gr represents the receiving antenna gain, the signal gain of the receiving antenna in a specific direction relative to the non-directional antenna; and Lp represents the path loss: the energy loss caused by air absorption, scattering, multipath effect and other factors in the process of signal transmission from the transmitting end to the receiving end.

[0061] The path loss Lp is determined, and the communication distance is calculated.

[0062] The path loss LP is calculated; Lp=Pt+Gt+Gr-Pr.

[0063] The farthest distance is calculated, and the distance d is calculated using the FSPL formula:

[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, about 3*10 8 m / s.

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

[0069] An unmanned aerial vehicle airborne device; comprising a 1.4G communication device;

[0070] A networking node; comprising a ground 1.4G and 5.8G dual-mode base station, used for receiving data transmitted by the unmanned aerial vehicle airborne device 1.4G network;

[0071] A central control platform, comprising a 5.8G communication device, receiving data of the networking node device through a 5.8G network.

[0072] The technical effects and advantages of the present application: the unmanned aerial vehicle airborne access method and system based on dual-link ad hoc network can significantly improve the communication efficiency, real-time performance and anti-interference capability of the unmanned aerial vehicle cluster, realize high-speed and stable data transmission between the unmanned aerial vehicle and the ground station or other unmanned aerial vehicles, and meet the needs of complex applications such as power grid inspection; by combining the advantages of 1.4G and 5.8G frequency bands, high-speed and stable data transmission is realized, the efficiency and safety of power grid operation and communication efficiency are improved; using 1.4G and 5.8G networking, the traffic fee is 0, reducing the traffic cost; dual-link multi-hop relay networking reduces the delay and improves the real-time performance of data transmission; advanced anti-interference technology is adopted to ensure the communication stability in complex electromagnetic environment and improve the anti-interference capability; dynamic network access and network exit of unmanned aerial vehicle nodes are supported, the network topology structure is flexible and variable, suitable for different application scenarios, enhancing flexibility and improving task success rate. In complex environments such as power grid inspection, the emergency response capability is improved, realizing an efficient, stable, economical and safe communication solution. BRIEF DESCRIPTION OF DRAWINGS

[0073] Figure 1 It is an implementation flowchart of the dual-link networking access method of the present application.

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

[0075] The technical solutions in the embodiments of the present application will be described clearly and completely in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application. Embodiment 1

[0076] The present application provides a flowchart of a power grid professional unmanned aerial vehicle airborne high-speed ad hoc network access method based on 1.4G networking access and 5.8G networking backhaul as shown in Figure 1 The present application provides a flowchart of a power grid professional unmanned aerial vehicle airborne high-speed ad hoc network access method based on 1.4G networking access and 5.8G networking backhaul as shown in

[0077] S10: system planning and design;

[0078] S11: equipment selection and configuration;

[0079] S12: network deployment and debugging;

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

[0081] S14: Security and reliability guarantee;

[0082] In step S10, the system is planned and designed, and the main tasks of the power grid professional UAV, such as power line inspection, fault diagnosis, etc., and the real-time, security, reliability, etc. requirements of data transmission are clarified; according to the demand analysis result, 1.4G frequency band is selected as the access frequency band between UAV and networking node, 5.8G frequency band is selected as the backhaul frequency band between networking node and center control platform, and the network architecture among UAV, networking node and center control platform is designed, including network topology structure, communication protocol, data format, etc.

[0083] In step S11, appropriate equipment and configuration are selected, UAV airborne communication equipment supporting 1.4G is selected, including transceiver, antenna, etc., and it is ensured that these equipment have high-speed data transmission capability, low delay characteristic and anti-interference capability, at the same time, UAV is configured with high-definition camera, infrared thermal imager, etc. sensor equipment according to task demand; networking node equipment with good signal coverage capability and data processing capability is selected, and corresponding transceiver and antenna are configured to support 1.4G and 5.8G frequency band communication; intelligent center control platform is selected, high-performance server and data processing equipment are configured to support real-time processing and analysis of received data, and control instructions can also be sent to UAV to guide its next operation.

[0084] In step S12, network deployment and system debugging are carried out. According to the power grid coverage area and UAV flight route, networking node is reasonably deployed to ensure that UAV can stably access network during flight. 1.4G and 5.8G frequency bands are reasonably planned to avoid same frequency interference and improve communication quality; networking network is optimized and adjusted, UAV node dynamically adjusts network topology structure according to its own position and movement state to ensure the continuity and stability of communication; at the same time, MAC protocol and routing protocol are optimized to ensure the QoS of data transmission.

[0085] By reasonably designing the position and connection mode of the nodes, the interference and conflict between the nodes can be reduced. That is, nodes far away from each other are connected together, and nodes close to each other are connected together, so as to reduce the spread of interference and the occurrence of conflict; that is, in the entire coverage network, a node is connected with the nearest nodes around it as much as possible, the node MAC and position information in the routing table are associated, similar to the way of forming a group, similar to a straight line, the points within 0-3 meters will be planned to communicate with each other first, and the points within 7-10 meters will be planned to optimize communication, so as to ensure that the same frequency signal floating from a distance will not interfere with the entire network; finally, network debugging and device commissioning are carried out to ensure that the communication link between the unmanned aerial vehicle, the networking node and the center control platform is smooth and unobstructed, and the data transmission is stable and reliable.

[0086] For the same frequency interference between nodes, corresponding protection strategies are made; the same frequency interference protection strategy mainly includes power control, time slot division, adaptive adjustment, topology optimization, multi-path selection function and other methods for protection, which can effectively solve the interference and conflict problems between nodes in wireless networking, so as to improve the network performance and enhance the network throughput;

[0087] Power control: each networking node adjusts the transmission power of the node adaptively according to the distance between nodes, signal strength and receiving sensitivity, so as to achieve the best performance.

[0088] The adaptive transmission power adjustment algorithm is adopted as follows, and the following parameters are input:

[0089] RSSI_current: current received signal strength indication, 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 transmission power, limited by node device hardware and regulations;

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

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

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

[0097] Max_iterations: maximum number of iterations to prevent the algorithm from looping indefinitely;

[0098] Output parameters:

[0099] P_adjusted: adjusted transmit power;

[0100] Algorithm steps:

[0101] Step 121. Initialization:

[0102] Set iteration counter iteration = 0;

[0103] Set P_adjusted = P_current as initial value;

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

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

[0106] Step 124. Calculate path loss adjustment factor: Step 125. Calculate transmit power adjustment amount: P_adjustment = ΔRSSI * Interference_factor * Path_loss_factor * Step_size;

[0107] Step 126. Apply transmit power adjustment amount:

[0108] If P_adjusted + P_adjustment > P_max, then P_adjusted = P_max;

[0109] If P_adjusted + P_adjustment < P_min, then P_adjusted = P_min;

[0110] Else, P_adjusted = P_adjusted + P_adjustment;

[0111] Step 127. Check number of iterations:

[0112] If iteration < Max_iterations, then iteration = iteration + 1 and go back to step 122;

[0113] Otherwise, end the algorithm and output P_adjusted;

[0114] Step 128. Return the adjusted transmit power P_adjusted.

[0115] By iteratively adjusting the transmit power to approach the target received signal strength, while considering the interference level and path loss; by limiting the number of iterations, it can prevent the algorithm from infinite loop when it cannot reach the target received signal strength.

[0116] Time slot division: In wireless networking, communication between nodes is carried out by time division. When multiple nodes send data at the same time, conflicts may occur. By using time slot division method, by reasonably allocating the transmission time slots between nodes, conflicts can be avoided and network throughput can be improved. The division of time slots mainly depends on the time division multiplexing (TDM) technology, which divides a channel into multiple time slices, 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 on the same channel in turn, improving channel utilization.

[0117] Adaptive adjustment: The interference and conflict problems in wireless networking are dynamic, and the environmental conditions and signal strength between nodes may change at any time. Therefore, adaptive algorithms and strategies are used to monitor and adjust communication between nodes to improve network performance. Nodes monitor the strength fluctuations of external interference signals in real time. According to the monitoring data, adjust the transmission power. At the same time, optimize channel selection to reduce interference conflicts. Use historical data to predict future interference trends and adjust in advance to avoid performance degradation. The algorithm has the ability to monitor, adjust, predict and learn, so as to effectively deal with dynamic interference and conflict problems in wireless networking.

[0118] Topology optimization: By reasonably designing the location and connection method of nodes, the interference and conflict between nodes can be reduced. Mainly connect nodes that are far apart together, and connect nodes that are close together, so as to reduce the spread of interference and the occurrence of conflicts.

[0119] Multi-path selection: Provide multi-path selection function, select the best path in the network to transmit data, so as to reduce the influence of interference and conflict. The following methods are used for multi-path selection:

[0120] 1. Initialization phase, collect information of all nodes in the network, including location, signal strength, etc. According to the node information, establish a preliminary routing table to record possible paths;

[0121] 2. Path selection phase, considering signal strength, hop count, delay, etc. Calculate the weight of each path. Based on the weight, select the best path as the main path for data transmission;

[0122] 3. Dynamic adjustment phase, real-time monitoring of network status, including node changes, signal fluctuations, etc. According to the changes of network status, dynamically update the routing table and adjust the path selection.

[0123] In step S13, the UAV performs task execution and related data transmission; the UAV takes off according to the preset flight route, and is controlled by the handle or automatically navigates, performs power line inspection, fault diagnosis and other tasks, and transmits the collected image, video 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 UAV, it is transmitted back to the center control platform through the 5.8G network.

[0124] In step S14, the safety and reliability guarantee measures; the node device and the UAV on-board device are embedded with a national network security encryption chip, and all devices can only be online after being verified by the security management platform. The UAV on-board device uses MAC whitelist authentication, and the networking node device uses MAC address and serial number as whitelist information, ensuring that other UAVs cannot illegally access the data transmitted by the networking transmission. The AES256 dynamic encryption mechanism is adopted to ensure the security of the data layer. Redundant backup mechanisms such as backup base stations and backup communication links are designed to deal with possible device failures or network interruptions. At the same time, real-time monitoring and fault diagnosis are carried out, and the UAV, networking node and center control platform are monitored in real time to discover and handle potential problems in time, ensuring the stable operation of the system. Embodiment 2

[0125] The application also provides a UAV on-board access system based on a dual-link ad hoc network, as shown in Figure 2 The networking architecture design comprises:

[0126] The access layer uses the 1.4G frequency band to build an access network between the UAV and the networking node. The advantages of the 1.4G frequency band mainly lie in its specificity, security, broadband characteristics and extensive mobile applications, which are very suitable for government special networks or specific industries such as power grids. The UAV establishes a stable communication connection with the networking node through the 1.4G network to transmit real-time data and control instructions; the node is a ground base station;

[0127] The backhaul layer uses a 5.8G frequency band to construct a backhaul network between the networking nodes and the central control platform. The advantage of the 5.8G frequency band lies in its high transmission speed and low interference. The 5.8G frequency band supports the IEEE 802.11ac wireless standard, with a bandwidth that can be increased to 40MHz or 80MHz or even higher, and a transmission speed that can be increased to 1Gbps, which can transmit about 125MB of data per second. In addition, since the cost of 5.8G equipment is relatively high, it is less used, so the frequency band signal is pure, and there is little channel occupation, which is suitable for applications that require high bandwidth, such as transmitting large amounts of data or high-definition video. The networking nodes will receive the data from the unmanned aerial vehicle through the 5.8G network and return it to the central control platform for further processing and analysis.

[0128] The software and hardware devices include:

[0129] The unmanned aerial vehicle on-board equipment includes:

[0130] The unmanned aerial vehicle needs to carry 1.4G communication equipment, including transceivers, antennas, etc. These devices should have high-speed data transmission capability, low delay characteristics and anti-interference capability to ensure that the unmanned aerial vehicle can communicate stably and reliably with the networking nodes during flight. The unmanned aerial vehicle can also carry sensor devices such as high-definition cameras and infrared thermal imagers to collect real-time image and video information of the power grid. This information will be transmitted to the networking nodes through the 1.4G network. The on-board equipment can also be 1.4G networked with the networking node devices, with flexible carrier bandwidth, supporting any network topology structure such as multipoint-to-multipoint and mesh grid.

[0131] The networking node device includes:

[0132] The ground 1.4G and 5.8G dual-mode base station is responsible for receiving data transmitted by the unmanned aerial vehicle 1.4G communication and returning it to the central control platform through the 5.8G network. The networking node should have good signal coverage and data processing capability to ensure real-time transmission and processing of data.

[0133] The networking node has good coverage, and the access distance between the on-board equipment and the node device is calculated, such as: 4W transmit power + 8dBi antenna gain, 0.5W terminal device + 2dBi antenna gain, according to the space loss formula, how far is the communication distance (where the frequency of the device is 1.4GHz, and the receiving sensitivity is -75dBm).

[0134] There are the following parameters, base station transmit power Pt: 4W = 36dBm, base station antenna gain Gt: 8dBi, terminal device transmit power Pt: 0.5W = 27dBm, terminal device antenna gain Gt: 2dBi, frequency f:

[0135] 1.4 GHz = 1.4 x 109Hz, reception sensitivity Pr: -75 dBm;

[0136] First, calculate the required reception power Pr and path loss Lp of the receiver;

[0137] The reception power formula is: Pr = Pt + Gt + Gr - Lp, where Pt represents the transmission power, the original power transmitted by the wireless device; Gt represents the transmission antenna gain, the signal gain of the transmission antenna in a certain direction relative to the non-directional antenna, such as omnidirectional antenna; Gr represents the reception antenna gain, the signal gain of the reception antenna in a certain direction relative to the non-directional antenna; Lp represents the path loss: the energy loss caused by air absorption, scattering, multipath effect and other factors in the process of signal propagation from the transmission end to the reception end; In order to calculate the communication distance, we need to determine the path loss Lp;

[0138] Calculate the path loss LP, and substitute the known values into the formula:

[0139] For node device to terminal:

[0140] Lp = Pt + Gt + Gr - Pr;

[0141] Lp = 36 + 8 + 2 + 75 = 121 dB;

[0142] For terminal to node device:

[0143] Lp = Pt + Gt + Gr - Pr;

[0144] Lp = 27 + 2 + 8 + 75 = 112 dB;

[0145] Calculate the farthest distance, and then use the FSPL formula to calculate the distance d:

[0146] Lp = 20log10(d) + 20log10(f) + 20log10(4π / C);

[0147] Substitute the known frequency f and light speed c into the formula:

[0148] f = 1.4 x 10 9 Hz;

[0149] c ≈ 3 x 10 8 m / s;

[0150] First calculate 20log10(f):

[0151] 20log10(f) = 20log10(1.4 x 10 9 );

[0152] = 20 (log10 (1.4) + log10 (10 9 ));

[0153] = 20 (0.146 + 9);

[0154] = 20 x 9.146;

[0155] = 182.92 dB;

[0156] Then calculate the constant term 20log10(4π / c):

[0157] 4π≈12.566;

[0158] 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)≈-147.56dB;

[0159] Combine all parts, the calculation of the terminal to the node device:

[0160] Substitute the path loss Lp = 112 dB into the FSPL formula:

[0161] 112 = 20log10(d) + 182.92 - 147.56

[0162] 112 = 20log10(d) + 35.36

[0163] 20log10(d) = 112 - 35.36

[0164] 20log10(d) = 76.64

[0165] log10(d) = 76.64 / 20 = 3.832

[0166] d ≈ 103.832 ≈ 6723.57 meters

[0167] The final result, the farthest communication distance from the UAV on-board device to the node device is about 6723.57 meters (about 6.72 kilometers).

[0168] Central control platform:

[0169] 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 UAV to guide its next operation.

[0170] Networking access method:

[0171] After the UAV node and the networking node device are powered on, they are initialized through the 1.4G frequency band, complete network synchronization and parameter configuration. The networking node device sends a networking instruction through the 1.4G frequency band, and the UAV node accesses the network according to the instruction to form a primary network. The UAV and the networking node device exchange broadcast, telemetry information and inter-aircraft coordination information through the 1.4G frequency band. The UAV node dynamically adjusts the network topology according to its own position and movement state to ensure the continuity and stability of communication.

[0172] In networking, each node establishes a connection with multiple other nodes to form a multi-hop network. The network can self-organize to form the optimal path, and 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 single node overload.

[0173] According to actual needs, the layout is performed through automatic multi-hop relay networking between nodes to improve communication efficiency and reduce bandwidth congestion. At the same time, redundant links are added to improve the fault tolerance and reliability of the network and reduce the impact of single-point failure. At the same time, a network topology optimization method based on traffic engineering is adopted to dynamically adjust the network topology by monitoring and analyzing the traffic pattern, reducing transmission delay and enhancing the real-time performance of data transmission.

[0174] Networking backhaul method:

[0175] The power grid inspection data (such as video, image, position information, etc.) collected by the UAV onboard equipment is transmitted back to the central control platform through the 5.8G network at high speed. In complex terrain or over-the-horizon conditions, nodes automatically perform multi-hop relay to ensure reliable data transmission.

[0176] Safety and reliability measures:

[0177] Advanced encryption technology and security measures are adopted to ensure data security and device security during communication.

[0178] By optimizing the network structure and improving the reliability of communication equipment, the stable operation of the entire system is ensured.

[0179] A redundant backup mechanism is designed to deal with possible equipment failure or network interruption.

[0180] By optimizing the MAC protocol and routing protocol, the different requirements of various services for transmission delay, transmission rate and transmission packet error rate are guaranteed to ensure the quality of data transmission.

[0181] Finally, it should be noted that the above only describes the preferred embodiments of the present application and is not intended to limit the present application. Although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art will appreciate that the technical solutions described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalent features, and any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A method for airborne access of a UAV based on a dual-link ad hoc network, characterized by: include: System planning and design; Equipment selection and configuration; Network deployment and debugging; UAV mission execution and data transmission; The network deployment and commissioning includes: deploying networking nodes based on the grid coverage area and the drone flight path, and planning frequencies using co-frequency interference protection strategies; Dynamically adjust network topology and optimize MAC and routing protocols based on its own location and mobility status; The co-channel interference protection strategy includes: power control, time slot division, adaptive adjustment, topology optimization, and multi-path selection; Power control: Each network node adaptively adjusts the node's transmission power based on the distance between nodes, signal strength and receiving sensitivity; Time slot division: allocating transmission time slots between nodes; Adaptive adjustment: The node monitors the intensity fluctuations of external interference signals in real time, adjusts the transmission power based on the monitoring data, and optimizes channel selection; Topology optimization: connect nodes that are farther apart and nodes that are closer together; Multi-path selection: Provides multi-path selection function to select the best path to transmit data; The power control includes: an adaptive transmit power adjustment algorithm: Input parameters include: RSSI_current: represents the current received signal strength indicator; RSSI_target: represents the target received signal strength indicator; Interference_level: represents the current interference level; Path_loss: represents the estimated path loss; P_max: represents the maximum allowed transmit power; P_min: represents the minimum allowed transmit power; P_current: represents the current transmit power; Step_size: represents the transmit power adjustment step size; Max_iterations: represents the maximum number of iterations; Output parameters include: P_adjusted: represents 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: 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.

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

3. The method for onboard access of a UAV based on a dual-link ad hoc network according to claim 1, characterized in that: The time slot division includes: dividing a channel into multiple time slices, each time slice being a time slot; The frame length is set to 256 bits, divided into 32 time slots, each time slot is 8 bits, and the transmission rate is 64 kbps.

4. The method for onboard access of a UAV based on a dual-link ad hoc network according to claim 1, characterized in that: The multi-path selection includes: In the initialization phase, information about all nodes in the network is collected, and a preliminary routing table is established based on the node information to record possible paths. In the path selection phase, the weight of each path is calculated based on signal strength, number of hops, and delay, and the best path is selected as the main path for data transmission; During the dynamic adjustment phase, the network status is monitored in real time, and the routing table is dynamically updated and the path selection is adjusted according to changes in the network status.

5. The method for airborne access to a UAV based on a dual-link ad hoc network according to any one of claims 1 to 4, characterized in that: The method also includes: safety and reliability assurance measures: The drone’s onboard equipment uses MAC whitelist authentication, and the networking node equipment uses MAC address and serial number as whitelist information.

6. The method for onboard access of a UAV based on a dual-link ad hoc network according to claim 2, characterized in that: Calculating the access distance between the drone and the networking node includes: Calculate the received power Pr and path loss Lp required by the receiver. The formula for 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; and 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 in meters; f represents the frequency of the signal in Hertz; c represents the speed of light, which is 3×10 8 m / s.

7. A system for implementing the method for onboard access to a UAV based on a dual-link ad hoc network according to any one of claims 1 to 6, characterized in that: include: UAV onboard equipment; Including 1.4G communication equipment; Networking nodes; It includes a ground-based 1.4G and 5.8G dual-mode base station for receiving data transmitted over the 1.4G network by drone-mounted equipment; The central control platform includes 5.8G communication equipment and receives the networking node device data through the 5.8G network.

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