A distributed unmanned aerial vehicle (UAV) active defense system

Abstract

This invention belongs to the field of radio countermeasures technology, and specifically relates to a distributed active defense system for unmanned aerial vehicles (UAVs). It includes an intelligent deployment dynamic optimization module, a multimodal cognitive jamming module, a high-precision three-level clock synchronization module, and a flexible self-organizing network communication module for overall system function support; distributed hardware devices and edge intelligent decision-making terminals for distributed deployment locations to implement detection and countermeasure functions; in practical operation, it can provide a distributed active defense system for UAVs targeting large areas and multiple important locations, avoiding application problems such as inaccurate deployment location selection, large coverage blind spots, low synchronization accuracy, unreliable communication networking, severe self-interference with the electromagnetic and timing equipment of partners, and poor UAV countermeasure effects. It achieves rapid, automatic, passive detection and precise jamming of "low, slow, and small" UAVs targeting large areas and multiple important locations.

Description

Technical Field

[0001] This invention belongs to the field of radio countermeasures technology, and specifically relates to a distributed unmanned aerial vehicle (UAV) active defense system. Background Technology

[0002] Current drone countermeasure systems used in key target areas primarily rely on long-term monitoring and detection using electro-optical, radar, and radio sensors to detect drones. Countermeasures are then employed through navigation deception, omnidirectional electromagnetic interference, and high-energy lasers. These devices constitute the drone countermeasure system, typically deployed centrally in key target areas. When the area of ​​the key target far exceeds the effective range of a single device, multiple drone countermeasure systems are required. While the centralized deployment method and the relatively crude method of stacking multiple devices have solved some of the challenges of drone countermeasures, they also present the following problems:

[0003] 1. Centralized deployment of drone countermeasure systems poses a risk of single-point failure, and fixed deployment of detection and countermeasure equipment has coverage blind spots. After detecting "low, slow, and small" drones, countermeasures are generally carried out by navigation deception or omnidirectional electromagnetic interference. Navigation deception equipment can affect other timing and positioning systems in important target areas. Omnidirectional electromagnetic interference is generally achieved by personnel operating jamming guns, which have high power and cause serious self-interference to the electromagnetic equipment of partners. It also has spatial coverage blind spots and is easily identified and avoided by drone AI obstacle avoidance systems.

[0004] 2. Multiple countermeasure devices often synchronize their clocks via satellite methods such as GPS and form local area networks using fixed Ethernet IPs. This results in low clock synchronization accuracy and susceptibility to navigation decoy devices, leading to low network reliability. CN110161533A discloses a UAV detection scheme based on phased array, but it does not solve the problem of multi-node coordination. At the same time, multi-point UAV countermeasure systems lack optimized deployment criteria, and deployment based on experience leads to a waste of countermeasure effectiveness and economic investment. Summary of the Invention

[0005] The purpose of this invention is to provide a distributed active defense system for unmanned aerial vehicles (UAVs). This system can provide a distributed active defense system for important targets in large areas and multiple important locations. It effectively avoids application problems such as inaccurate selection of deployment locations, large coverage blind spots, low synchronization accuracy, unreliable communication networking, serious self-interference with the electromagnetic and timing equipment of partners, and poor UAV countermeasures. It enables rapid and automatic passive detection and precise interference of "low, slow and small" UAVs against important targets in large areas and multiple important locations.

[0006] To achieve the above objectives, the present invention adopts the following technical solution:

[0007] A distributed unmanned aerial vehicle (UAV) active defense system includes an intelligent deployment dynamic optimization module, a multimodal cognitive interference module, a high-precision three-level clock synchronization module, and a flexible self-organizing network communication module for supporting the overall system functions, as well as distributed hardware devices and edge intelligent decision-making terminals for implementing detection and countermeasure functions at distributed deployment locations.

[0008] The intelligent deployment dynamic optimization module combines the asset value V of important targets, airspace openness α, historical attack frequency β, and the effectiveness of the detection and identification system performance E to construct a four-dimensional weight. Based on the spatial Durbin model, it calculates the composite value index ρ of different locations of each important target and deploys four types of heterogeneous distributed devices according to the distribution of ρ values.

[0009] The multimodal cognitive jamming module can realize real-time fusion processing of radio signals, radar signals and photoelectric signals. When it is identified as a UAV target, it provides high-precision UAV positioning information, combines historical flight paths to output the motion state estimation result of the UAV, and then implements precise jamming.

[0010] The high-precision three-level clock synchronization module can realize the time reference unification of distributed deployment equipment, laying the foundation for direction finding, positioning and data fusion. It is accomplished by a three-layer local clock synchronization mechanism that does not rely on satellite navigation systems.

[0011] The elastic self-organizing network communication module is used to realize the networking and data sharing of distributed devices.

[0012] Furthermore, key nodes are deployed in the top 10% of the ρ value area, which includes detection and identification, electromagnetic interference, and hard damage functions; general nodes are deployed in the 10%-40% ρ value area, which includes detection and identification, and electromagnetic interference; slave nodes are deployed in the 40%-70% ρ value area, which includes radio spectrum monitoring and electromagnetic interference; and portable electromagnetic interference devices are deployed in the bottom 30% ρ value area. Through optimized distributed deployment algorithms, the overall equipment cost in large and important target areas can be reduced while coverage blind spots are also reduced.

[0013] Furthermore, the frequency domain of the interference electromagnetic signal of the multimodal cognitive interference module adopts the same frequency band as the current UAV, that is, it is achieved by using a broadband coverage signal method for the frequency hopping signal. In the air domain, it forms a directional narrow beam for the UAV's direction of movement through adaptive digital beamforming. In the time domain, it is basically simultaneous with the detection and identification of UAV parameters. Combined with the distance of the UAV, it designs an appropriate low transmission power to complete the electromagnetic interference of precise three-dimensional suppression of the UAV target in time-frequency-space.

[0014] Furthermore, in the high-precision three-level clock synchronization module, the reference layer deploys a rubidium atomic clock with an accuracy of 1e-12 as the master clock source, distributing IRIG-B code time signals through optical fiber. The relay layer is implemented by using a TCXO oscillator with a temperature drift of ±0.1ppm and an improved IEEE 1588v2 protocol built into the edge intelligent decision terminal, directly sharing the clock with nearby devices. The terminal layer solves the clock synchronization problem of the end devices. For the distributed end devices within 2km and without wired network access, a 1PPS signal is transmitted through wireless LoRa modulation, with a signal rise time of <2ns, as a clock alignment correction signal.

[0015] Furthermore, in addition to the Ethernet and fiber optic links built into each device, additional communication modules supporting wireless MESH networks and LoRa communication modules are added to ensure redundant backup of physical connections. When the latency and bandwidth of one physical link decrease, it can automatically switch to other communication links. Different distributed devices within the network use an adaptive TDMA networking method for route maintenance and updates. The time axis is divided into a superframe structure. Each superframe contains a 20ms beacon period for broadcasting network topology information, a 30ms contention period using CSMA / CA access, and a 250ms guarantee period. For mobile distributed devices, Kalman filtering is used to predict the location of the next cycle and update the routing table.

[0016] Furthermore, distributed hardware devices used for distributed deployment to implement detection and countermeasure functions include radio, photoelectric and radar detection equipment, navigation deception, electromagnetic interference, high-energy laser and high-power microwave devices. Different types and interfaces of devices can be distributed networked and clock synchronized with the support of the hardware protocol middleware of the edge intelligent decision terminal. At the same time, the intelligent identification and decision-making algorithms are implemented in the processor of the edge intelligent decision terminal through embedded firmware programs, which serve as the execution unit for system decision-making to drive and control the distributed UAV countermeasure devices.

[0017] The working process of a distributed unmanned aerial vehicle (UAV) active defense system is as follows:

[0018] S1. The intelligent deployment dynamic optimization module first calculates the composite value index ρ for each location based on four dimensions: the value of important target assets (V), airspace openness (α), historical attack frequency (β), and system performance effectiveness (E), using a spatial Durbin model. Based on the ρ value distribution, the system automatically plans deployment schemes for four types of nodes: deploying important nodes with detection, identification, electromagnetic interference, and hard damage capabilities in the top 10% of high-value areas; deploying general nodes with detection and identification + electromagnetic interference in areas with ρ values ​​of 10%-40%; deploying slave nodes with radio monitoring + electromagnetic interference in areas with ρ values ​​of 40%-70%; and configuring portable jamming equipment in the remaining areas. This optimized deployment strategy reduces equipment costs while ensuring coverage effectiveness.

[0019] S2. Distributed radio, optoelectronic, and radar detection equipment continuously monitor the protected airspace. When a suspicious target is detected, the multimodal cognitive jamming module fuses multi-source sensor data in real time and determines whether it is a UAV target through signal feature analysis and pattern recognition. After confirming the target, the module combines real-time measurement data and historical flight paths to calculate the target's precise distance, azimuth, pitch angle, three-dimensional coordinates, velocity, and heading motion status, forming a complete UAV situational awareness.

[0020] S3, High-precision three-level clock synchronization module maintains the system time base: The reference layer transmits the IRIG-B code signal of the rubidium atomic clock through optical fiber; the relay layer uses the improved IEEE 1588v2 protocol to achieve microsecond-level synchronization between devices; the terminal layer completes nanosecond-level time alignment of the end devices by transmitting 1PPS signal wirelessly through LoRa; the flexible self-organizing network communication module builds a redundant network through wired Ethernet / fiber and wireless Mesh / LoRa multi-link, uses an adaptive TDMA mechanism to dynamically allocate communication resources, and uses Kalman filtering to predict the location of mobile nodes and update the routing table in real time to ensure communication continuity when the network topology changes;

[0021] S4. After confirming the threat target, the system automatically selects the optimal jamming node and generates a spatially directional jamming beam with a beamwidth of approximately 3° based on the UAV's operating frequency band, real-time position, and motion trajectory. The jamming signal is synchronized with the detection period in the time domain, matches the target signal in the frequency domain, and is precisely pointed at the target in the air domain. At the same time, the transmission power is dynamically adjusted according to the distance to achieve precise three-dimensional suppression in time, frequency, and space. The entire process is completed within 200ms, effectively avoiding the collateral effects of traditional omnidirectional jamming.

[0022] S5: The management software monitors the interference effect in real time. If the target persists, it automatically upgrades the countermeasure strategy, such as coordinating multiple nodes to jointly interfere or activating hard damage equipment. The system continuously learns the signal characteristics and avoidance strategies of new UAVs, updates the interference parameter library and deployment plan, and forms a closed-loop defense system of "detection-identification-interference-evaluation-optimization".

[0023] The beneficial effects of this invention are as follows: The distributed active defense system for unmanned aerial vehicles (UAVs) provided by this invention, in practical operation, can provide a distributed active defense system for important targets in large areas and multiple important locations, covering an area of ​​more than 50 square kilometers. It can avoid application problems such as inaccurate selection of deployment locations, large coverage blind spots, low synchronization accuracy, unreliable communication networking, serious self-interference with the electromagnetic and timing equipment of partners, and poor UAV countermeasures. It achieves rapid and automatic passive detection and precise interference of "low, slow and small" UAVs on important targets in large areas and multiple important locations. Specifically, when this invention is applied, it can reduce signal blind spots by 80%, improve anti-interference accuracy, and reduce electromagnetic collateral effects by 90%. The system adopts a highly reliable architecture and has extremely strong survivability. A single point of failure will not affect the overall operation. Its excellent adaptability to complex electromagnetic environments is particularly suitable for countering modern threats such as intelligent UAVs, and it can demonstrate comprehensive battlefield communication support capabilities. Attached Figure Description

[0024] Figure 1 This is a schematic diagram of the structure of the distributed unmanned aerial vehicle active defense system of the present invention;

[0025] Figure 2 This is a schematic diagram of the intelligent deployment dynamic optimization module in this invention;

[0026] Figure 3 This is a schematic diagram of the multimodal cognitive interference module in this invention;

[0027] Figure 4 This is a schematic diagram of the high-precision three-level clock synchronization module in this invention. Detailed Implementation

[0028] Specific Embodiment 1: The technical solution of the present invention will be clearly and completely described below with reference to the embodiments. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention. It should be noted that: In the present invention, unless otherwise specified, all implementation methods and preferred implementation methods mentioned herein can be combined with each other to form new technical solutions. In the present invention, unless otherwise specified, all technical features and preferred features mentioned herein can be combined with each other to form new technical solutions.

[0029] As per the specification attached to this invention Figure 1 To the instruction manual Figure 4As shown, to address the application challenges of existing UAV countermeasure systems, such as inaccurate deployment location selection, large coverage blind spots, low synchronization accuracy, unreliable communication networks, severe self-interference with partner electromagnetic and timing equipment, and poor UAV countermeasure effectiveness, this invention provides a distributed UAV active defense system. This distributed UAV active defense system adopts a distributed networking architecture, and its core modules include: distributed hardware devices for distributed deployment locations to implement detection and countermeasure functions; these hardware devices integrate countermeasures such as radio, photoelectric, and radar detection and electromagnetic interference, high-energy lasers, and high-power microwaves; an edge intelligent decision-making terminal that performs data processing, interference decision-making, and equipment control; a real-time intelligent deployment dynamic optimization module; a multi-modal cognitive interference module that generates precise interference strategies; a high-precision three-level clock synchronization module that unifies the system's time base; a flexible self-organizing network communication module that ensures reliable network transmission; and management software that enables system monitoring, threat analysis, and countermeasure execution. This architecture, through multi-module collaboration, constructs an intelligent protection system integrating detection, decision-making, interference, and optimization.

[0030] This invention achieves precise defense deployment through a smart deployment dynamic optimization module: First, based on the composite value index ρ, the protection level of each area is calculated using the spatial Durbin model and a distribution map is generated; then, defense nodes are deployed in layers according to the ρ value range to form a multi-level protection system of core area - key area - regular area - auxiliary area; finally, dynamic optimization is achieved by periodically updating the ρ value and temporarily supplementing mobile equipment.

[0031]

[0032] Intelligent countermeasures are achieved through multimodal cognitive jamming module technology: First, target detection and identification are performed, integrating multi-source data such as radio monitoring to capture 2.4GHz / 5.8GHz remote control signals, radar detection to obtain distance / velocity, and AI image analysis to confirm the target type and photoelectric identification; then, a precise jamming strategy is generated, including frequency domain matching (tracking frequency-hopping signals and using broadband coverage), spatial domain focusing (adaptive beamforming to form a 3° narrow beam directional jamming), time domain synchronization (aligning the jamming signal with the detection period), and power adjustment (dynamically adjusting the transmission power); finally, the target status is monitored in real time through jamming effect evaluation, and if it is not ineffective, it is upgraded to enhanced modes such as multi-node collaborative suppression, forming a closed-loop countermeasure process of "detection-jamming-evaluation".

[0033] A high-precision three-level clock synchronization module architecture is adopted, achieving a unified time base across the entire domain through a layered design: the reference layer uses a rubidium atomic clock + fiber optic IRIG-B to provide 1e-12 ultra-high precision synchronization, ensuring the timing of core nodes; the relay layer achieves ±0.1ppm accuracy through the TCXO + PTP protocol, covering the needs of general nodes; the terminal layer utilizes LoRa wireless 1PPS technology to achieve low-cost synchronization with <2ns jitter, suitable for edge nodes. The master clock source distributes time signals through optical fiber, while wireless LoRa is used for synchronization of end devices within 2km, forming a hybrid "wired + wireless" synchronization network.

[0034] The system employs a resilient self-organizing network communication module architecture, achieving highly reliable transmission through a hybrid wired and wireless network: the wired side provides a high-bandwidth, low-latency backbone channel based on Ethernet and fiber optics; the wireless side utilizes Mesh networking and LoRa technology to enhance resilience. The communication protocol adopts a 300ms periodic adaptive TDMA superframe structure, divided into a 20ms beacon period for topology broadcasting, a 30ms contention period for CSMA / CA random access, and a 250ms guarantee period for fixed-slot data transmission. For mobile nodes, Kalman filtering is used to predict location for dynamic routing optimization, ensuring the network maintains optimal connectivity even in complex environments. This design combines deterministic transmission with dynamic adaptability, meeting the high real-time requirements of critical services.

[0035] It achieves efficient localized processing through edge intelligent decision-making terminals, adopts hardware protocol middleware compatible with devices from multiple vendors, and enables plug-and-play rapid deployment; equipped with embedded AI algorithms, it can complete target recognition and interference strategy generation within 200ms to ensure real-time response; at the same time, it supports remote firmware upgrade capability, and continuously improves the response effectiveness to new drone threats through dynamic updates of algorithms and strategies, forming an edge computing node with self-evolution capability.

[0036] The specific working process of the distributed unmanned aerial vehicle (UAV) active defense system of the present invention is as follows:

[0037] S1, the intelligent deployment dynamic optimization module first calculates the composite value index ρ for each location based on four dimensions: the value of important target assets (V), airspace openness (α), historical attack frequency (β), and system performance effectiveness (E), using a spatial Durbin model. Based on the ρ value distribution, the system automatically plans deployment schemes for four types of nodes: important nodes with detection, identification, electromagnetic interference, and hard damage capabilities are deployed in the top 10% of high-value areas; general nodes with detection and identification + electromagnetic interference are deployed in areas with ρ values ​​between 10% and 40%; slave nodes with radio monitoring + electromagnetic interference are deployed in areas with ρ values ​​between 40% and 70%; and portable jamming equipment is configured in the remaining areas. This optimized deployment strategy reduces equipment costs while ensuring coverage effectiveness.

[0038] S2. Distributed radio, optoelectronic, and radar detection equipment continuously monitor the protected airspace. When a suspicious target is detected, the multimodal cognitive jamming module fuses multi-source sensor data in real time and determines whether it is a UAV target through signal feature analysis and pattern recognition. After confirming the target, the module combines real-time measurement data and historical flight paths to calculate the target's precise three-dimensional coordinates (distance, azimuth, pitch angle) and velocity and heading motion status, forming a complete UAV situational awareness.

[0039] S3, High-precision three-level clock synchronization module maintains the system time base: The reference layer transmits the IRIG-B code signal of the rubidium atomic clock through optical fiber; the relay layer uses the improved IEEE 1588v2 protocol to achieve microsecond-level synchronization between devices; the terminal layer completes nanosecond-level time alignment of the end devices by transmitting 1PPS signal wirelessly through LoRa; the flexible self-organizing network communication module builds a redundant network through wired Ethernet / fiber and wireless Mesh / LoRa multi-link, uses an adaptive TDMA mechanism to dynamically allocate communication resources, and uses Kalman filtering to predict the location of mobile nodes and update the routing table in real time to ensure communication continuity when the network topology changes;

[0040] S4. After confirming the threat target, the system automatically selects the optimal jamming node and generates a spatially directional jamming beam with a beamwidth of approximately 3° based on the UAV's operating frequency band, real-time position, and motion trajectory. The jamming signal is synchronized with the detection period in the time domain, matches the target signal in the frequency domain, and is precisely pointed at the target in the air domain. At the same time, the transmission power is dynamically adjusted according to the distance to achieve precise three-dimensional suppression in time, frequency, and space. The entire process is completed within 200ms, effectively avoiding the collateral effects of traditional omnidirectional jamming.

[0041] S5: The management software monitors the interference effect in real time. If the target persists, it automatically upgrades the countermeasure strategy, such as coordinating multiple nodes to jointly interfere or activating hard damage equipment. The system continuously learns the signal characteristics and avoidance strategies of new UAVs, updates the interference parameter library and deployment plan, and forms a closed-loop defense system of "detection-identification-interference-evaluation-optimization".

[0042] The distributed UAV active defense system of this invention has the following characteristics when in use: First, the system adopts a spatial Durbin model to construct a four-dimensional evaluation system, namely asset value V, airspace openness α, historical attack frequency β, and system effectiveness E. Through the composite value index ρ, it realizes the dynamic optimization of protection resources, forming a four-level defense circle of "core-key-routine-auxiliary". Compared with the traditional uniform deployment scheme, it can reduce equipment investment by 30% while reducing coverage blind spots. It innovatively integrates radio spectrum monitoring, radar detection and photoelectric identification technology, and improves the detection probability of "low, slow and small" targets through multi-source data fusion, with a measured value of 98%. The accuracy of UAV model identification is improved to over 95% by employing a three-dimensional joint analysis algorithm of time, frequency, and space. Breaking through the traditional omnidirectional interference mode, it adopts an adaptive digital beamwidth of 3° and dynamic power adjustment technology, increasing the concentration of interference energy by 20dB. While ensuring suppression effectiveness, it reduces incidental electromagnetic interference by 90%, effectively solving the problem of timing system pollution caused by navigation deception. A unique three-level clock synchronization architecture is used to construct a highly reliable synchronization system: the reference layer provides an ultra-high precision time reference through a rubidium atomic clock with 1e-12 precision and fiber optic IRIG-B code; the relay layer uses a ±0.1ppm TCXO oscillator combined with an improved PTP protocol to achieve precise relay synchronization; and the terminal layer uses LoRa wireless 1PPS technology to complete the synchronization of end devices. The aforementioned architecture achieves a breakthrough by realizing 100ns-level time synchronization accuracy across the entire system, completely eliminating reliance on external signals such as GPS, and providing an autonomous and controllable time reference for collaborative operations in complex electromagnetic environments. It constructs a multi-physical-layer redundant architecture of "wired Ethernet / fiber optic + wireless Mesh / LoRa," employing a 300ms periodic adaptive TDMA superframe structure and a Kalman filter predictive routing algorithm, resulting in a network reconstruction time of <50ms and communication availability of 99.999%, meeting the requirements of high-intensity wartime environments. Efficient autonomous response is achieved through edge intelligent decision-making terminals, integrating 12 protocol intermediates. The system enables plug-and-play compatibility with devices from multiple vendors, achieves rapid localized decision-making within 200ms thanks to embedded computing power, and is equipped with an interference strategy library with online learning capabilities, allowing for dynamic updates of countermeasures. This significantly improves the real-time adaptability and countermeasure effectiveness against emerging threats such as intelligent drones. The system achieves comprehensive performance optimization through a closed-loop control system of "detection-identification-interference-assessment," achieving full coverage of a 50km² area. It possesses strong survivability with automatic reconfiguration for single-point failures. While ensuring protective effectiveness, it significantly reduces countermeasure energy consumption by 40% and maintenance costs by 35%, forming an efficient, reliable, and energy-saving integrated defense system.

[0043] Overall, the management software of the distributed UAV active defense system of this invention integrates four core functions: real-time monitoring and fault warning of the status of all network nodes through device management; situational awareness function based on multi-source data fusion to dynamically display UAV tracks and assess threat levels; countermeasure execution module to automatically match the optimal interference strategy and trigger it quickly; and provides effect evaluation support, including statistical analysis of interference success rate and suggestions for system parameter optimization, forming a closed-loop management from monitoring to countermeasure, comprehensively improving the intelligent operation and maintenance level of the protection system. It should be noted that, in this invention, those skilled in the art can understand the specific meaning of the above terms according to the specific circumstances. Furthermore, it should be understood that although this specification describes embodiments, not every embodiment contains only one independent technical solution. This descriptive method is merely for clarity. Those skilled in the art should consider the specification as a whole, and the technical solutions in each embodiment can also be appropriately combined to form other embodiments that can be understood by those skilled in the art.

Claims

1. A distributed unmanned aerial vehicle (UAV) active defense system, characterized in that, It includes an intelligent deployment dynamic optimization module, a multimodal cognitive interference module, a high-precision three-level clock synchronization module, and a flexible self-organizing network communication module for supporting the overall system functions; distributed hardware devices and edge intelligent decision-making terminals for distributed deployment locations to implement detection and countermeasure functions. The intelligent deployment dynamic optimization module combines the asset value V of important targets, airspace openness α, historical attack frequency β, and the effectiveness of the detection and identification system performance E to construct a four-dimensional weight. Based on the spatial Durbin model, it calculates the composite value index ρ of different locations of each important target and deploys four types of heterogeneous distributed devices according to the distribution of ρ values. The multimodal cognitive jamming module can realize real-time fusion processing of radio signals, radar signals and photoelectric signals. When it is identified as a UAV target, it provides high-precision UAV positioning information, combines historical flight paths to output the motion state estimation result of the UAV, and then implements precise jamming. The high-precision three-level clock synchronization module enables unified time reference for distributed equipment, laying the foundation for direction finding, positioning, and data fusion. It employs a three-layer local clock synchronization mechanism independent of satellite navigation systems, with the following architecture: The reference layer provides an ultra-high-precision time reference through a rubidium atomic clock and fiber optic IRIG-B code; the relay layer uses a TCXO oscillator combined with an improved PTP protocol to achieve precise relay synchronization; and the terminal layer utilizes LoRa wireless 1PPS technology to synchronize end devices. This architecture achieves a breakthrough of 100ns-level time synchronization accuracy across the entire system, completely eliminating dependence on external GPS signals and providing an autonomous and controllable time reference guarantee for collaborative operations in complex electromagnetic environments. The flexible self-organizing network communication module is used to realize the networking and data sharing of distributed devices; Important nodes are deployed in the first 10% of the ρ value area, general nodes are deployed in the 10%-40% of the ρ value area, slave nodes are deployed in the 40%-70% of the ρ value area, and portable electromagnetic interference devices are deployed in the last 30% of the ρ value area. Through the above-mentioned optimized distributed deployment algorithm, the overall equipment cost of large and important target areas can be reduced while reducing coverage blind spots.

2. The distributed unmanned aerial vehicle (UAV) active defense system according to claim 1, characterized in that, The multimodal cognitive interference module uses the same frequency band as the current UAV in the frequency domain for its interference electromagnetic signal. In the air domain, it forms a directional narrow beam in the direction of the UAV's movement through adaptive digital beamforming. In the time domain, while detecting and identifying UAV parameters, it designs an appropriate low transmission power based on the distance to the UAV, thus completing the electromagnetic interference that precisely suppresses the UAV target in three dimensions: time, frequency, and space.

3. A distributed unmanned aerial vehicle (UAV) active defense system according to claim 2, characterized in that, In the high-precision three-level clock synchronization module, the reference layer deploys a rubidium atomic clock with an accuracy of 1e-12 as the master clock source, and distributes IRIG-B code time signals through optical fiber. The relay layer is implemented by the edge intelligent decision terminal with built-in TCXO oscillator and improved IEEE 1588v2 protocol, directly sharing the clock with nearby devices. The terminal layer solves the clock synchronization problem of the end devices. For the distributed end devices within 2km and without wired network access, a 1PPS signal is sent through wireless LoRa modulation as a clock alignment correction signal.

4. A distributed unmanned aerial vehicle (UAV) active defense system according to claim 3, characterized in that, In addition to the Ethernet and fiber optic links built into each device, additional communication modules supporting wireless MESH networks and LoRa communication modules are added to ensure redundant backup of physical connections. When the latency and bandwidth of one physical link decrease, it can automatically switch to other communication links. Different distributed devices within the network use an adaptive TDMA networking method for route maintenance and updates, dividing the time axis into a superframe structure. Each superframe contains a beacon period, a contention period, and a guarantee period. For mobile distributed devices, Kalman filtering is used to predict the location of the next cycle and update the routing table.

5. A distributed unmanned aerial vehicle (UAV) active defense system according to claim 1, characterized in that, Distributed hardware devices for distributed deployment to implement detection and countermeasure functions include radio, photoelectric and radar detection equipment, navigation deception, electromagnetic interference, high-energy laser and high-power microwave. Different types and interfaces of devices are distributed and networked and clock synchronized with the support of hardware protocol middleware of the edge intelligent decision terminal. At the same time, the intelligent identification and decision-making algorithms are implemented in the processor of the edge intelligent decision terminal through embedded firmware programs, which serve as the execution unit for system decision-making to drive and control the distributed UAV countermeasure devices.

6. The distributed unmanned aerial vehicle (UAV) active defense system according to any one of claims 1-5, characterized in that, The system works as follows: S1. The intelligent deployment dynamic optimization module first calculates the composite value index ρ of each location based on four dimensions: the value of important target assets (V), airspace openness (α), historical attack frequency (β), and system performance effectiveness (E), using the spatial Durbin model. Based on the ρ value distribution, the system automatically plans the deployment schemes of four types of nodes: deploying important nodes with detection, identification, electromagnetic interference, and hard damage capabilities in the top 10% of high-value areas; deploying general nodes with detection and identification + electromagnetic interference in areas with ρ values ​​of 10%-40%; deploying slave nodes with radio monitoring + electromagnetic interference in areas with ρ values ​​of 40%-70%; and configuring portable jamming equipment in the remaining areas. The above-mentioned optimized deployment strategy reduces equipment costs while ensuring coverage. S2. Distributed radio, photoelectric, and radar detection equipment continuously monitor the protected airspace. When a suspicious target is detected, the multimodal cognitive jamming module fuses multi-source sensor data in real time and determines whether it is a UAV target through signal feature analysis and pattern recognition. After confirming the target, the multimodal cognitive jamming module combines real-time measurement data and historical flight paths to calculate the target's precise three-dimensional coordinates and motion state, forming a complete UAV situational awareness. S3. The high-precision three-level clock synchronization module maintains the system time reference: the reference layer transmits the IRIG-B code signal of the rubidium atomic clock through optical fiber; the relay layer uses the improved IEEE 1588v2 protocol to achieve microsecond-level synchronization between devices; The terminal layer completes nanosecond-level time alignment of the end device by transmitting 1PPS signals wirelessly via LoRa; the elastic self-organizing network communication module builds a redundant network through wired and wireless multi-links, dynamically allocates communication resources using an adaptive TDMA mechanism, and uses Kalman filtering to predict the location of mobile nodes and update the routing table in real time to ensure communication continuity when the network topology changes. S4. After confirming the threat target, the system automatically selects the optimal jamming node and generates a spatially directional jamming beam using adaptive digital beamforming technology based on the UAV's operating frequency band, real-time position, and motion trajectory. The jamming signal is synchronized with the detection period in the time domain, matches the target signal in the frequency domain, and is precisely pointed at the target in the air domain. At the same time, the transmission power is dynamically adjusted according to the distance to achieve precise three-dimensional suppression in time, frequency, and space. The entire process is completed within 200ms, effectively avoiding the collateral effects of traditional omnidirectional jamming. S5: The management software monitors the interference effect in real time. If the target persists, it automatically upgrades the countermeasure strategy. The system continuously learns the signal characteristics and avoidance strategies of new UAVs, updates the interference parameter library and deployment plan, and forms a closed-loop defense system of "detection-identification-interference-evaluation-optimization".

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