Unmanned aerial vehicle ad hoc network cluster management and control system based on intelligent street lamp and satellite communication

Abstract

The invention relates to the technical field of unmanned aerial vehicle ad hoc network cluster management and control scheme design based on intelligent street lamps and satellite communication, in particular to an unmanned aerial vehicle ad hoc network cluster management and control system based on intelligent street lamps and satellite communication. The system comprises an intelligent street lamp subsystem, a satellite communication subsystem, an unmanned aerial vehicle cluster node and a dynamic cooperative control platform. The innovative scheme comprises the following steps: (1) the multimode communication gateway realizes seamless conversion between a satellite protocol and a ground Internet of Things protocol; (2) a street lamp sensor generates a dynamic risk map to guide cluster obstacle avoidance; (3) supporting signal interruption emergency networking by a rapid clustering algorithm based on geometric topology; (4) task priority drives time slot distribution to improve communication efficiency; and (5) the satellite-street lamp-relay unmanned aerial vehicle multistage redundancy guarantee system is continuously controllable. According to the scheme, the communication reliability, the environmental adaptability and the cooperative capability of the cluster in a complex urban area are remarkably enhanced.

Description

Technical Field

[0001] The present invention relates to the technical field of design of unmanned aerial vehicle (UAV) self-organizing network cluster control scheme based on smart street lamps and satellite communications, and specifically to a UAV self-organizing network cluster control system based on smart street lamps and satellite communications. Background Art

[0002] Existing smart city drone swarm control technologies suffer from multiple flaws. Satellite communications, the mainstream remote control method, are subject to obstruction by high-rise urban buildings, resulting in frequent signal interruptions at low altitudes and difficulty ensuring continuous drone communication in complex urban areas. Ground-based communication networks, however, rely on cellular base stations, which have coverage gaps and are susceptible to sudden interference, making them unable to meet the high-speed maneuverability requirements of swarms. While smart streetlight systems offer the advantage of widespread distribution, their sensing capabilities are limited to environmental monitoring and fail to effectively collaborate with drone swarm control, creating data silos. More significantly, heterogeneous network protocols lack compatibility: satellite communication's spatial data protocols and terrestrial IoT protocols are independent of each other, requiring multiple encapsulation and decapsulation cycles for cross-network data transmission, introducing significant latency and packet loss risks. The lack of multi-level redundancy mechanisms can easily lead to swarm control failures in the face of extreme weather or equipment failures. While some research has attempted to enhance network resilience through relay drones, this underutilizes urban infrastructure resources, and dynamic topology reconstruction is inefficient, making it difficult to support the precise coordinated operation of large-scale swarms in densely populated areas.

[0003] Therefore, the existing technology needs to be further developed. Summary of the Invention

[0004] The purpose of the present invention is to overcome the above technical deficiencies and provide a drone self-organizing network cluster management and control system based on smart street lights and satellite communications to solve the problems existing in the existing technology.

[0005] To achieve the above technical objectives, the present invention provides a drone self-organizing network cluster control system based on smart street lamps and satellite communications, including: Smart streetlight subsystem, including a multi-mode communication gateway, an environmental sensor array, and an ad hoc network module; a satellite communications subsystem to provide wide-area communications via a constellation of low-Earth orbit satellites; Drone cluster nodes, equipped with dual-frequency communication modules, are used to simultaneously access streetlights and satellite networks; Dynamic collaborative control platform, used to integrate street lamp sensor data and satellite positioning data in real time to generate cluster task instructions.

[0006] Specifically, the multi-mode communication gateway has an embedded protocol converter for bidirectional conversion between the satellite-specific space data packet protocol and the IEEE 802.15.4 protocol of the street lamp network.

[0007] Specifically, the features of the environmental sensor array include lidar, temperature and humidity sensors, and crowd density cameras. The data collected by the environmental sensor array is used to generate a gridded environmental risk map through edge computing nodes.

[0008] Specifically, the dual-frequency communication module integrates a link switching logic unit, which automatically connects to the triangle communication cluster formed by the nearest three street lamps when the satellite signal strength is lower than the threshold X.

[0009] Specifically, the dynamic calculation method of the threshold value X is: in, is the minimum received power, is the noise figure, is the Boltzmann constant, is the absolute temperature, For bandwidth.

[0010] Specifically, the dynamic collaborative control platform includes: The task allocation engine divides drones into task groups based on the risk map.

[0011] Specifically, the dynamic collaborative control platform includes: The dynamic path optimizer recalculates the cluster path at preset intervals to avoid high-risk areas.

[0012] Specifically, the system also includes an emergency relay drone. When the satellite and street light network fail at the same time, the delay-tolerant network module carried by the emergency relay drone is used to store and forward key instructions.

[0013] Specifically, the delay-tolerant network module adopts an infectious routing algorithm, and the message copy diffusion formula is: in, is the maximum number of hops, TTL is the lifetime, The preset maximum number of copies.

[0014] Specifically, the communication topology of the ad hoc network module adopts a time-division frequency-division multiple access mechanism to allocate dynamic time slots for the drone cluster: in, is the frame period, is the number of drones, is the task priority weighting coefficient.

[0015] Beneficial effects: This system achieves a breakthrough in cluster control technology by integrating smart streetlights with satellite communication capabilities: 1. Innovation in communication reliability: Multimode gateways break down the barriers between satellite and terrestrial network protocols, enabling seamless switching between dual-domain communications. Smart streetlights and drones form a dynamic ad hoc network, completely eliminating communication blind spots caused by building obstructions and ensuring full connectivity across the cluster.

[0016] 2. Environmental intelligent perception upgrade: The streetlight sensor array builds a real-time dynamic risk map, providing drones with centimeter-level situational awareness. The deep collaboration between task allocation and path planning modules enables the swarm to proactively avoid obstacles and respond to situations.

[0017] 3. System resilience is greatly enhanced: The four-level redundant architecture integrates a primary satellite link, a backup streetlight link, an emergency relay drone link, and a local decision-making module, establishing a tiered failover mechanism. Dual-mode hot-swap technology ensures that any single point of failure does not interrupt cluster control.

[0018] 4. Resource utilization optimization: A dynamic time slot allocation mechanism based on task priority enables intelligent, on-demand allocation of communication bandwidth, ensuring exclusive use of critical mission resources while improving overall spectrum resource utilization and effectively supporting ultra-large-scale cluster collaboration.

[0019] 5. Facility reuse reduces costs and increases efficiency: Deeply reuse the city's smart streetlight network, eliminating the cost of building dedicated communication base stations. Streetlight sensing data directly drives cluster decision-making, significantly enhancing the overall value of urban infrastructure. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 This is a schematic diagram of the system composition of a drone self-organizing network cluster control system based on smart street lamps and satellite communications provided in a specific embodiment of the present invention; Figure 2 It is a schematic diagram of the construction process of the dynamic risk map provided in a specific embodiment of the present invention. DETAILED DESCRIPTION

[0021] In order to enable those skilled in the art to better understand the technical solution of the present invention, the technical solution of the present invention is clearly and completely described below in conjunction with the drawings of the present invention. Based on the embodiments in this application, other similar embodiments obtained by ordinary technicians in this field without making creative work should fall within the scope of protection of this application. In addition, the directional words mentioned in the following embodiments, such as "up", "down", "left", "right", etc., are only reference to the directions of the drawings. Therefore, the directional words used are used to illustrate rather than limit the invention.

[0022] The present invention will be further described below with reference to the accompanying drawings and preferred embodiments.

[0023] See also Figure 1-Figure 2 The present invention provides a UAV self-organizing network cluster management and control system based on smart street lamps and satellite communications, including: Smart streetlight subsystem 100, including a multi-mode communication gateway, an environmental sensor array, and an ad hoc network module; It should be noted that each smart street light is provided with a smart street light subsystem 100. The deployment standard of the smart street light subsystem 100 can be specifically set according to the actual needs of the user of the present invention. The present invention preferably designs the deployment standard of the smart street light subsystem 100 as follows: 1. Installation spacing: 25±5m, meeting the 5.8GHz signal strength requirement of -70dBm; 2. Height configuration: The main light pole height is preferably 8m, taking into account both lighting and signal coverage; 3. Communication module: 6m above the ground to avoid ground obstruction; 4. Power supply redundancy: dual mains power + solar cell. The power generation power of the solar cell is preferably 120W, ensuring 72 hours of battery life in the event of a power outage.

[0024] Satellite communication subsystem 200, for providing wide area communications via a low-orbit satellite constellation; It should be noted that the present invention preferably designs a satellite communication configuration as shown in Table 1: Table 1 Satellite communication configuration It should be further explained that the satellite communication subsystem 200 described in the present invention preferably adopts a low-orbit satellite constellation (orbital altitude 500-800km), the operating frequency band is 26.5-40GHz (Ka band), and the satellite terminal equivalent isotropic radiated power (EIRP) is 33dBW. The above settings are obtained by the technicians of the present invention through a large number of tests and can better ensure the communication effect.

[0025] The drone cluster node 300 is equipped with a dual-band communication module for simultaneous access to streetlights and satellite networks; It should be noted here that the maximum flight speed of the drone cluster node 300 is 20m / s (72km / h), and it is equipped with a dual-frequency communication module (2.4GHz / 5.8GHz) and an RTK-GPS positioning system (accuracy <0.5m). The above settings were obtained by the technicians of the present invention through a large number of tests and can better ensure the communication effect.

[0026] Dynamic collaborative control platform 400, used to integrate streetlight sensor data and satellite positioning data in real time to generate cluster task instructions; It should be noted here that the dynamic collaborative control platform 400 is deployed on the edge computing node, with a response delay of ≤100ms, and processes sensor data and positioning information in real time.

[0027] Specifically, the multi-mode communication gateway has an embedded protocol converter for bidirectional conversion between the satellite-specific space data packet protocol and the IEEE 802.15.4 protocol of the streetlight network; It should be further explained that the protocol conversion process is performed in three steps: 1. Header stripping: Remove the 6-byte header (AX.25 frame structure) of the satellite CCSDS protocol to extract the payload data; 2. Payload encapsulation: Add the IEEE 802.15.4 protocol MAC header (including microsecond timestamp, source address, and destination address); 3. Checksum append: Calculate the 32-bit CRC checksum (generated by the polynomial 0x04C11DB7) and append it to the end of the data packet; Specifically, the conversion delay is less than or equal to 50 milliseconds, meeting the 100ms control cycle requirement of the drone, and the 100ms control cycle requirement of the drone includes completing the conversion in half a cycle.

[0028] Specifically, the features of the environmental sensor array include lidar, temperature and humidity sensors, and crowd density cameras. The data collected by the environmental sensor array is used to generate a gridded environmental risk map through edge computing nodes; It should be further explained that, regarding environmental risk map modeling, the solutions designed by the present invention include: 1. Design grid modeling specifications: Cell size: 1.8m x 1.8m, chosen because it is smaller than the minimum rotor pitch of the drone; Refresh rate: 5Hz, chosen to match the drone's maximum angular velocity of 30° / s; 2. Design risk value calculation model: in: is the dynamic risk value at the target node j; : obstacle density (ratio of area occupied by obstacles in a unit); : Crowd density (value min(1, actual number of people / 5), saturation at 5 people / m²); : Temperature gradient ( , 25°C is the ideal temperature); Weight coefficient: , , (The collision rate is minimized through a thousand - time simulation verification); It should be further noted that the parameters of the lidar, temperature - humidity sensor, and optical camera preferably used in the present invention are shown in Table 2: Table 2 Sensor parameters: Specifically, the dual - frequency communication module integrates a link - switching logic unit. When the satellite signal strength is lower than threshold X, it automatically accesses the triangular communication cluster formed by the three nearest street lamps.

[0029] It should be further noted that regarding the link - switching logic unit, the solution designed in the present invention includes: 1. Design a three - level switching strategy: ① Normal mode (RSSI > 10dB): Maintain the satellite link; ② Warning mode (8dB < RSSI ≤ 10dB): Pre - connect to the three nearest street lamps; ③ Switching mode (RSSI ≤ 8dB): Access the triangular communication cluster of street lamps.

[0030] 2. Construction of the triangular communication cluster: ① Screen the 10 candidate street lamps with the strongest signals; ② Calculate the area of the triangle formed by every three street lamps (area threshold > 100m²); ③ Select the triangle with the largest sum of signal strengths; Threshold basis: It is measured that when RSSI ≤ 8dB, the bit error rate increases steeply (exceeding the tolerance of the control instruction by 10 -3 ).

[0031] Specifically, the dynamic calculation method of the threshold X is: Among them, is the minimum received power, is the noise figure, is the Boltzmann constant, is the absolute temperature, is the bandwidth; In the preferred embodiment of the present invention, the preferred values and preferred bases of the calculation parameters of the threshold X are shown in Table 3: Table 3 Preferred values and preferred bases of the calculation parameters of the threshold X Substitute into the calculation to obtain which is approximately equal to 7.96dB (rounded to 8dB).

[0032] Specifically, the dynamic collaborative control platform 400 includes: The task allocation engine divides drones into task groups based on the risk map.

[0033] Specifically, the dynamic collaborative control platform 400 includes: The dynamic path optimizer recalculates the cluster path at preset intervals to avoid high-risk areas.

[0034] It should be further explained that, regarding the path dynamic optimizer, the solution designed by the present invention includes: The parameters of the improved ant colony algorithm are shown in Table 4: Table 4 Parameters of the improved ant colony algorithm State transition probability formula: in: is the probability that drone k moves from node i to node j; is the pheromone concentration on path (i, j); is the influence weight index of the pheromone, which is preferably 1.2 in the present invention, to amplify the effect of the pheromone (when α>1, positive feedback is strengthened); is the heuristic function value from i to j; is the influence weight index of the heuristic function, which is preferably 2.5 in the present invention to strengthen the effect of real-time environmental factors. Greater than The choice is used to focus on safety; Indicates the set of neighbor nodes that the drone can currently select.

[0035] The heuristic function is: The coefficient a=0.7 represents the preferred weight coefficient of distance cost, and b=0.3 represents the preferred weight coefficient of risk cost. It should be noted that the present invention has been verified by 5000 Monte Carlo simulations. When a=0.7 and b=0.3: The collision rate is reduced to 0.3% (compared to 1.2% when a=b=0.5); The path length only increases by 8.7% (the best balance between safety and efficiency).

[0036] is the Euclidean distance from node i to node j; is the dynamic risk value at the target node j, which comes from the real-time data of the street light sensor (the higher the value, the more dangerous it is); Update cycle: 2 seconds (synchronized with the drone navigation system refresh rate, a single ant colony optimization takes about 1.2 seconds (Intel i7-11800H), leaving a 0.8 second communication delay margin).

[0037] It should be noted here that the collaborative working mechanism of the above formula includes: 1. Probability calculation: molecular , used to enhance risk aversion ( ); Denominator normalization is used to ensure reasonable probability distribution in multi-path competition; 2. Dynamic tuning: when Sudden increase (such as sudden crowd gathering), drastically decreased, It is greatly reduced, and the drone will take the initiative to bypass it; 3. Long-term learning: Release pheromones on the path to success, Accumulate and guide subsequent drones to choose safer paths.

[0038] The following is an example of a specific engineering application to illustrate the above solution: Suppose a drone needs to move from node A to B: Path 1: , Risk = 0.1, then ; Path 2: , Risk = 0.02, then ; If the pheromone concentration of path 1 1.2 times that of path 2: ; ; Result: The probability of choosing Path 1 is 70% (although it is slightly shorter, it is riskier), which reflects the system's emphasis on safety.

[0039] Specifically, the system also includes an emergency relay drone. When the satellite and street light network fail at the same time, the delay-tolerant network module carried by the emergency relay drone is used to store and forward key instructions.

[0040] It should be further explained that, regarding the delay-tolerant network architecture, the solution designed by the present invention includes: The dedicated relay drone has a flight time of ≥90 minutes and a storage capacity of 64GB; Message copy control model: in: (Tests have shown that delays greater than 10 hops are uncontrollable); TTL = 300s (covering a typical mission cycle); (neighbor discovery interval); (The upper limit of the copy, when exceeded, the probability of network congestion increases by 46%).

[0041] Implementation process: 1. Relay drones patrol the edge of the network; 2. Activate infectious routing when a link outage is detected; 3. Broadcast storage instructions according to the replica number model.

[0042] Specifically, the delay-tolerant network module adopts an infectious routing algorithm, and the message copy diffusion formula is: in, is the maximum number of hops, TTL is the lifetime, The preset maximum number of copies.

[0043] Specifically, the communication topology of the ad hoc network module adopts a time-division frequency-division multiple access mechanism to allocate dynamic time slots for the drone cluster: in, is the frame period, is the number of drones, is the task priority weighting coefficient.

[0044] It should be further explained that, regarding the time slot allocation mechanism, the scheme designed by the present invention includes: 1. Design dynamic time slot calculation formula: Variable definition: (frame period, to meet the human eye's persistence of vision); : The number of drones in the current communication domain; : Task priority coefficient (determined by looking up the table, as shown in Table 5): Table 5 Task priority coefficients Allocation rules: 1. Each drone obtains a basic time slot: ; in, Indicates the number of drones in the current communication domain.

[0045] 2. Multiply the time slot resources according to the task priority coefficient; Specifically, the time slot resources are multiplied using the following formula: in: is the original time slot; is the time slot after doubling; : Task priority coefficient (determined by looking up the table); : Bandwidth utilization factor( , is the number of high-priority drones); Specifically, an example of the priority decision matrix is ​​shown in Table 6: Table 6 Priority decision matrix Anti-collision mechanism: When there are too many high priority tasks (the present invention is preferably hour): Startup Excess Factor ; Actual allocation: .

[0046] 3. Idle time slots are dynamically allocated to high-priority tasks.

[0047] It is understandable that this system achieves a breakthrough improvement in cluster control technology by integrating smart street lights with satellite communication capabilities: 1. Innovation in communication reliability: Multimode gateways break down the barriers between satellite and terrestrial network protocols, enabling seamless switching between dual-domain communications. Smart streetlights and drones form a dynamic ad hoc network, completely eliminating communication blind spots caused by building obstructions and ensuring full connectivity across the cluster.

[0048] 2. Environmental intelligent perception upgrade: The streetlight sensor array builds a real-time dynamic risk map, providing drones with centimeter-level situational awareness. The deep collaboration between task allocation and path planning modules enables the swarm to proactively avoid obstacles and respond to situations.

[0049] 3. System resilience is greatly enhanced: The four-level redundant architecture integrates a primary satellite link, a backup streetlight link, an emergency relay drone link, and a local decision-making module, establishing a tiered failover mechanism. Dual-mode hot-swap technology ensures that any single point of failure does not interrupt cluster control.

[0050] 4. Resource utilization optimization: A dynamic time slot allocation mechanism based on task priority enables intelligent, on-demand allocation of communication bandwidth, ensuring exclusive use of critical mission resources while improving overall spectrum resource utilization and effectively supporting ultra-large-scale cluster collaboration.

[0051] 5. Facility reuse reduces costs and increases efficiency: Deeply reuse the city's smart streetlight network, eliminating the cost of building dedicated communication base stations. Streetlight sensing data directly drives cluster decision-making, significantly enhancing the overall value of urban infrastructure.

[0052] The various technical features described above can be combined arbitrarily. Although not all possible combinations of these technical features are described, any combination of these technical features should be considered to be covered by this specification as long as such combination does not conflict.

[0053] The specific embodiments of the present invention described above do not limit the scope of protection of the present invention. Any other corresponding changes and modifications made based on the technical concept of the present invention should be included in the scope of protection of the claims of the present invention.

Claims

1. A UAV self-organizing network cluster control system based on smart street lights and satellite communications, characterized by: The method comprises: Smart streetlight subsystem, including a multi-mode communication gateway, an environmental sensor array, and an ad hoc network module; a satellite communications subsystem to provide wide-area communications via a constellation of low-Earth orbit satellites; Drone cluster nodes, equipped with dual-frequency communication modules, are used to simultaneously access streetlights and satellite networks; Dynamic collaborative control platform, used to integrate street lamp sensor data and satellite positioning data in real time to generate cluster task instructions.

2. The UAV self-organizing network cluster control system based on smart street lamps and satellite communications according to claim 1 is characterized in that: The multi-mode communication gateway has an embedded protocol converter for bidirectional conversion between the satellite-specific space data packet protocol and the IEEE 802.15.4 protocol of the streetlight network.

3. The UAV self-organizing network cluster control system based on smart street lamps and satellite communications according to claim 1 is characterized in that: The features of the environmental sensor array include lidar, temperature and humidity sensors, and crowd density cameras. The data collected by the environmental sensor array is used to generate a gridded environmental risk map through edge computing nodes.

4. The UAV self-organizing network cluster control system based on smart street lamps and satellite communications according to claim 1 is characterized in that: The dual-frequency communication module integrates a link switching logic unit, which automatically connects to the triangle communication cluster formed by the nearest three street lamps when the satellite signal strength is lower than the threshold X.

5. The UAV self-organizing network cluster management and control system based on smart street lamps and satellite communications according to claim 4 is characterized in that: The dynamic calculation method of the threshold value X is: in, is the minimum received power, is the noise figure, is the Boltzmann constant, is the absolute temperature, For bandwidth.

6. The UAV self-organizing network cluster control system based on smart street lamps and satellite communications according to claim 1 is characterized in that: The dynamic collaborative control platform includes: The task allocation engine divides drones into task groups based on the risk map.

7. The UAV self-organizing network cluster control system based on smart street lamps and satellite communications according to claim 1 is characterized in that: The dynamic collaborative control platform includes: The dynamic path optimizer recalculates the cluster path at preset intervals to avoid high-risk areas.

8. The UAV self-organizing network cluster management and control system based on smart street lamps and satellite communications according to claim 1 is characterized in that: The system also includes an emergency relay drone. When the satellite and street light network fail at the same time, the delay-tolerant network module carried by the emergency relay drone is used to store and forward key instructions.

9. The UAV self-organizing network cluster control system based on smart street lamps and satellite communications according to claim 8 is characterized in that: The delay-tolerant network module adopts the infectious routing algorithm, and the message copy diffusion formula is: in, is the maximum number of hops, TTL is the lifetime, The preset maximum number of copies.

10. The UAV self-organizing network cluster control system based on smart street lamps and satellite communications according to claim 1 is characterized in that: The communication topology of the ad hoc network module adopts the time-division frequency-division multiple access mechanism to allocate dynamic time slots for the drone cluster: in, is the frame period, is the number of drones, is the task priority weighting coefficient.

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