Quantum encryption and ai coordination low altitude unmanned plane global management and control system

Abstract

The application provides a quantum encryption and AI cooperative low-altitude unmanned aerial vehicle global management and control system, belonging to the field of low-altitude safety management and control, comprising: a quantum secure transmission module, used for distributing quantum keys to unmanned aerial vehicles and detection terminals, and encrypting and quantum digitally signing flight data collected by the unmanned aerial vehicles and multi-source heterogeneous detection data collected by each detection and sensing terminal based on the quantum keys to obtain trusted multi-source data; an AI intelligent analysis module, used for predicting a flight trajectory based on the trusted detection data, outputting a risk assessment and a key scheduling instruction, and the quantum secure transmission module responding to the key scheduling instruction to adjust a key update frequency; a global management and control execution module, used for generating a management and control instruction according to a risk assessment result, and issuing the management and control instruction for execution after quantum encryption and signature. The application resists attacks through quantum encryption, realizes multi-source data fusion and risk research and judgment, and effectively improves the accurate identification and cooperative management and control capability of low-altitude global risks.

Description

Technical Field

[0001] This invention relates to the field of drone management, specifically to a low-altitude drone full-domain management system that combines quantum encryption and AI. Background Technology

[0002] The low-altitude economy is developing rapidly, and drones are now widely used in logistics, agricultural and forestry protection, power line inspection, emergency rescue, and aerial photography for cultural tourism, leading to a continuous increase in the number of drones in China. However, with the large-scale popularization of drones, safety incidents such as unauthorized flights, privacy leaks, malicious manipulation, and flight collisions have seriously threatened public safety, making the management and control of low-altitude drones a critical issue that urgently needs to be addressed. To meet this need, current low-altitude drone management and control mainly relies on various types of airspace target perception hardware devices, including passive / active radar detection equipment, radio signal detection equipment, visible light / infrared multi-channel photoelectric imaging detection equipment, ADS-B, RemoteID, multi-line lidar detection equipment, acoustic fingerprint detection equipment, 5G-A sensing base stations, BeiDou navigation satellite network monitoring systems, and general-purpose satellite remote sensing monitoring terminals, to collect data. The aim is to achieve comprehensive, all-time, and high-precision safety management and flight behavior supervision of various consumer-grade, industrial-grade, and industry-application-grade drones.

[0003] However, in the existing low-altitude drone monitoring system, the aforementioned sensing and detection devices are mostly deployed independently and operate in separate domains. There is no unified data exchange channel or interoperability mechanism between the devices, resulting in fragmented and incompatible multi-source monitoring data. Furthermore, each type of detection device has its own inherent technical shortcomings: passive / active radar is susceptible to ground clutter interference in low-altitude near-ground scenarios, and its detection range, tracking stability, and resolution for low, slow, and small targets are insufficient; radio detection equipment can only detect active drones and is completely ineffective against "black flight" targets that are flying silently with their signals turned off. Effectiveness is compromised by several factors. Photoelectric detection equipment is susceptible to damage from rain, fog, low light at night, and physical obstructions, significantly increasing the probability of failure in harsh environments. ADS-B and RemoteID rely on drones actively broadcasting messages, making the information vulnerable to tampering and forgery, and they cannot monitor drones without or with their broadcast modules disabled. Multi-line lidar and acoustic detection equipment have short effective ranges, hindering large-area coverage. 5G-A sensing base stations have limited accuracy in ranging and angular measurement of small targets, with significant errors in complex urban scenarios. BeiDou and satellite remote sensing terminals suffer from poor real-time data transmission and low resolution, failing to meet the demands of refined continuous tracking. If these sensing devices are used independently for monitoring, they will create numerous blind spots, resulting in high false alarm and missed alarm rates, and weak comprehensive identification capabilities for target classification, identity recognition, and behavior analysis. Furthermore, the industry lacks a unified standard and interface for multi-source sensing data interaction, and lacks a mature and reliable data aggregation, cleaning, registration, and fusion processing system. This hinders the full utilization of each device's performance advantages, the mitigation of inherent defects, and the construction of a collaborative, multi-device, all-domain sensing capability. Furthermore, mainstream low-altitude drone control systems on the market have the following shortcomings: In terms of communication security, existing systems generally use traditional encryption algorithms such as AES and RSA to build communication links. With the iterative upgrade of quantum computing technology, these algorithms are easily cracked. Once the link is hijacked, it will directly lead to drone loss of control or data leakage. Existing patents CN116782037A and CN117236521A both use traditional encryption methods and cannot resist quantum computing attacks. Although CN115834856A achieves point-to-point quantum encryption, it only supports fixed node transmission and cannot adapt to the networking requirements of high-speed mobile drones and distributed heterogeneous devices. At the same time, the key update strategy of traditional quantum key distribution networks is fixed and cannot be dynamically adjusted according to communication load or risk level, resulting in an imbalance between security and transmission efficiency. In terms of risk warning, most existing systems rely on a single detection data source and do not perform unified normalization and fusion processing on multi-source heterogeneous data. They lack AI multi-target tracking, confidence assessment, dynamic identity authentication and behavior analysis capabilities, and the problem of multi-trajectory conflict is prominent. They can only provide post-event alarms and cannot achieve flight trajectory prediction and forward-looking warning.In terms of global collaboration and emergency response, traditional systems are mostly deployed independently in different regions. Data is not shared between different systems and regulatory departments, there is no collaborative linkage mechanism, and there is a lack of unified interfaces and network scheduling capabilities, making it difficult to restrain cross-regional violations. When a security incident occurs, the existing system relies on manual summarization, analysis, and scheduling, which involves many intermediate links and takes a long time to respond, making it easy for the situation to escalate and unable to meet the needs of rapid response in emergency scenarios.

[0004] In summary, the core bottleneck of existing technologies lies in the fact that traditional encryption mechanisms are difficult to resist quantum computing attacks, and multi-source heterogeneous sensing data lacks effective fusion and AI judgment mechanisms, resulting in fundamental defects in both communication security and intelligent collaboration in the management and control of low-altitude drones. Summary of the Invention

[0005] In view of this, it is necessary to provide a low-altitude UAV full-domain control system that combines quantum encryption and AI collaboration to overcome the shortcomings of traditional encryption mechanisms in resisting quantum computing attacks and the lack of effective integration and AI judgment mechanisms for multi-source heterogeneous sensing data. This would solve the fundamental technical problems in communication security and intelligent collaboration for low-altitude UAV control.

[0006] To address the aforementioned technical problems, this invention provides a low-altitude unmanned aerial vehicle (UAV) all-domain control system that integrates quantum encryption and AI, comprising: The quantum-secure transmission module is used to distribute quantum keys to the UAV and various detection and sensing terminals, and to encrypt and quantum digitally sign the flight data collected by the UAV and the multi-source heterogeneous detection data collected by various detection and sensing terminals based on the quantum keys, so as to obtain trusted multi-source data. The AI ​​intelligent analysis module is communicatively connected to the quantum secure transmission module and is used to predict flight trajectories based on the trusted multi-source data, and output risk assessment results and key scheduling instructions; the quantum secure transmission module is also used to respond to the key scheduling instructions to adjust the key update frequency; The global control execution module is communicatively connected to the quantum-secure transmission module and the AI ​​intelligent analysis module. It is used to generate control instructions based on the risk assessment results, and then send the control instructions to the drone and various detection and sensing terminals for execution after being encrypted and quantum digitally signed by the quantum-secure transmission module.

[0007] In one possible implementation, the quantum secure transmission module includes multiple quantum ground stations deployed across the entire region, wherein the quantum ground stations located in critical airspace and no-fly zones are configured as trusted nodes; The quantum ground station is used to distribute an initial quantum key to the UAV and each detection and sensing terminal when they are powered on. The trusted node is used to automatically update the quantum key between the drone and the trusted node when the drone passes by.

[0008] In one possible implementation, the quantum-secure transmission module includes: The quantum key distribution module is used to adaptively adjust the key update frequency according to the key scheduling instructions output by the AI ​​intelligent analysis module; The quantum encryption communication module is used to encrypt and quantum digitally sign the flight data collected by the UAV and the multi-source heterogeneous detection data collected by each of the aforementioned detection and sensing terminals to obtain trusted multi-source data; and to encrypt and quantum digitally sign the control commands to obtain trusted control commands. The key management module is used for the full lifecycle management of global quantum keys, including generation, storage, authorization distribution, and expiration destruction.

[0009] In one possible implementation, after receiving the trusted multi-source data, the AI ​​intelligent analysis module verifies the quantum digital signature of the trusted multi-source data, and obtains trusted verification data after the verification is successful.

[0010] In one possible implementation, the AI ​​intelligent analysis module includes: A multi-source heterogeneous data normalization unit is used to convert the trusted verification data with different data formats and coordinate systems into standardized detection data with a unified data format and coordinate system. The environmental perception and confidence dynamic evaluation unit is used to evaluate the confidence of the standardized detection data according to the current environmental conditions, and to assign fusion weights to the standardized detection data of each detection and perception terminal according to the confidence evaluation results, so as to generate standardized detection data with confidence labels.

[0011] In one possible implementation, the AI ​​intelligent analysis module further includes: The multi-target tracking and trajectory fusion unit is used to associate, deduplicate, and fuse multiple target trajectories from various detection and sensing terminals within the same time period based on the standardized detection data with confidence labels, so as to generate unique fused trajectory data for the same UAV target.

[0012] In one possible implementation, the AI ​​intelligent analysis module further includes: The multi-source data fusion module is used to fuse multi-source heterogeneous detection data collected by different types of detection and sensing terminals based on the fused trajectory data to generate multi-source fused sensing data. The target identification unit is used to identify the aircraft type and flight attitude of the target based on the multi-source fusion sensing data, and generate a target identification result; The flight trajectory prediction unit is used to predict the flight trajectory of the target within a preset time period based on the multi-source fusion sensing data and real-time environmental information, and generate a flight trajectory prediction result.

[0013] In one possible implementation, the AI ​​intelligent analysis module further includes: The risk assessment module is used to classify the airspace attributes, identity authentication results, and behavioral characteristics of each UAV based on the target identity recognition results, the flight trajectory prediction results, and the fused flight trajectory data, and in combination with preset airspace rules, and generate risk assessment results.

[0014] In one possible implementation, the global control execution module includes: The risk warning module is used to output corresponding warning information based on the risk assessment results output by the AI ​​intelligent analysis module, and send the warning information to the regulatory terminal through at least one of the following methods: sound and light, SMS, APP push or large screen display. The emergency response module is used to execute corresponding emergency response actions based on the risk level in the risk assessment results: When the risk level is low, a warning message is sent to the pilot. When the risk level is medium risk, the jamming equipment is activated and surrounding detection equipment is dispatched to enhance monitoring; When the risk level is high, intercept drones will be dispatched to intercept the illegal targets. When the risk level is extremely high, multiple departments will work together to handle the violations across the entire region.

[0015] In one possible implementation, the global control execution module further includes: The unified scheduling module for all-domain detection equipment is used to issue control commands to each detection and sensing terminal. The control commands include at least one of the following: equipment start / stop, angle adjustment, power adjustment, network linkage, or mode switching.

[0016] The beneficial effects of this invention are as follows: The quantum encryption and AI-coordinated low-altitude UAV full-domain control system provided by this invention firstly distributes quantum keys through a quantum secure transmission module, and encrypts and quantum digitally signs the flight data collected by the UAV and the multi-source heterogeneous detection data collected by various detection and sensing terminals based on the quantum keys, obtaining trusted multi-source data, fundamentally ensuring the resistance to quantum computing attacks and the data trustworthiness of the low-altitude communication link; secondly, the AI ​​intelligent analysis module predicts flight trajectories based on trusted multi-source data, outputs risk assessment results and key scheduling instructions, and responds to the key scheduling instructions through the quantum secure transmission module to adjust the key update frequency, realizing bidirectional collaboration between AI and quantum encryption; finally, the full-domain control execution module generates control instructions based on the risk assessment results, and issues them for execution after encryption through the quantum secure transmission module, forming a closed-loop process from secure transmission and intelligent judgment to precise handling, significantly improving the communication security, early warning accuracy, and emergency response efficiency of low-altitude UAV full-domain control. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 A schematic diagram of an embodiment of the quantum encryption and AI collaborative low-altitude drone full-domain control system provided by the present invention; Figure 2 A schematic diagram of another embodiment of the quantum encryption and AI collaborative low-altitude drone all-domain control system provided by the present invention; Figure 3 A schematic diagram of an embodiment of quantum key management provided by the present invention; Figure 4 A schematic diagram of an embodiment of AI intelligent analysis provided by the present invention; Figure 5 A schematic diagram of an embodiment of the emergency response provided by the present invention. Detailed Implementation

[0019] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0020] In the description of the embodiments of the present invention, unless otherwise stated, "multiple" means two or more. "And / or" describes the relationship between related objects, indicating that there can be three relationships. For example, A and / or B can represent three situations: A exists alone, A and B exist simultaneously, and B exists alone.

[0021] The terms "first," "second," etc., used in the embodiments of this invention are for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated. Therefore, a technical feature defined with "first" or "second" may explicitly or implicitly include at least one of that feature.

[0022] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of the invention. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0023] Before demonstrating the embodiments, the following terms will be explained.

[0024] Quantum digital signature: A digital signature technology based on the principles of quantum mechanics. It uses the uniqueness and non-cloning properties of quantum states to sign data, verifying the authenticity and integrity of the data source and preventing data from being tampered with or forged.

[0025] Quantum bit error rate (QBER): The proportion of bits that are inconsistent when the receiver and sender compare quantum state measurement results during quantum key distribution out of the total number of compared bits. It is a core physical indicator for measuring the security of quantum channels. Under normal circumstances, it is usually maintained at a low level. An abnormal increase may indicate the presence of eavesdropping.

[0026] One-time pad: an encryption rule that requires the key to be generated completely randomly, to be the same length as the plaintext, and to be used only once. When these conditions are met, it is mathematically proven to have perfect confidentiality, meaning it cannot be cracked by any computing power.

[0027] Quantum key distribution (QKD) is a technology that uses the principles of quantum mechanics to securely distribute keys between communicating parties. Based on the quantum no-cloning theorem and the principle of measurement collapse, any eavesdropping will inevitably be detected, thus ensuring the security of the key distribution process.

[0028] This invention provides a low-altitude drone global control system that combines quantum encryption and AI, which will be described in detail below.

[0029] Figure 1This is a schematic diagram of an embodiment of the quantum encryption and AI-assisted low-altitude drone global control system provided by the present invention, as shown below. Figure 1 As shown, it includes: The quantum-secure transmission module 100 is used to distribute quantum keys to the UAV and various detection and sensing terminals, and to encrypt and quantum digitally sign the flight data collected by the UAV and the multi-source heterogeneous detection data collected by various detection and sensing terminals based on the quantum keys, so as to obtain trusted multi-source data. The AI ​​intelligent analysis module 200 is communicatively connected to the quantum secure transmission module 100. It is used to predict flight trajectories based on trusted multi-source data and output risk assessment results and key scheduling instructions. The quantum secure transmission module 100 is also used to respond to key scheduling instructions to adjust the key update frequency. The global control execution module 300 is connected to the quantum secure transmission module 100 and the AI ​​intelligent analysis module 200. It is used to generate control instructions based on risk assessment results and then send the control instructions to the drones and various detection and sensing terminals for execution after being encrypted and digitally signed by the quantum secure transmission module 100.

[0030] The quantum encryption and AI-coordinated low-altitude UAV full-domain control system provided in this invention first distributes quantum keys through a quantum-secure transmission module. Based on the quantum keys, it encrypts and quantum digitally signs the flight data collected by the UAV and the multi-source heterogeneous detection data collected by various detection and sensing terminals, obtaining trusted multi-source data. This fundamentally ensures the low-altitude communication link's resistance to quantum computing attacks and data trustworthiness. Second, the AI ​​intelligent analysis module predicts flight trajectories based on the trusted multi-source data, outputs risk assessment results and key scheduling instructions, and responds to the key scheduling instructions through the quantum-secure transmission module to adjust the key update frequency, achieving bidirectional collaboration between AI and quantum encryption. Finally, the full-domain control execution module generates control instructions based on the risk assessment results, which are encrypted and sent out for execution through the quantum-secure transmission module. This forms a closed-loop process from secure transmission and intelligent analysis to precise handling, significantly improving the communication security, early warning accuracy, and emergency response efficiency of low-altitude UAV full-domain control.

[0031] This invention is a low-altitude drone risk early warning and control system that combines quantum encryption and AI. The system adopts a three-layer distributed architecture, from top to bottom: the overall control and execution layer, the AI ​​intelligent analysis layer, and the quantum secure transmission layer. The three layers achieve bidirectional data interaction and command linkage through a standardized communication interface.

[0032] Divided by physical deployment: (1) Quantum secure transmission layer: Distributed deployment in ground quantum stations, trusted nodes, UAV airborne terminals, and communication base stations across the entire domain, while also connecting to all detection and sensing devices such as passive / active radar detection equipment, radio signal detection equipment, visible light / infrared multi-channel photoelectric imaging detection equipment, ADS-B, RemoteID, multi-line lidar detection equipment, acoustic UAV detection equipment, 5G-A sensing base stations, Beidou navigation satellite network monitoring system, and general satellite remote sensing monitoring terminals; (2) AI intelligent analysis layer: centrally deployed on the server cluster of the control center, while setting up distributed edge analysis nodes, and built-in modules for multi-source heterogeneous data normalization, AI multi-target tracking fusion, dynamic identity authentication, behavior analysis, environmental perception and confidence dynamic assessment; (3) Full-domain control execution layer: deployed on the command platform of the control center, on-site early warning terminal, jamming equipment, interception drones and multi-department linkage terminal, to uniformly manage and dispatch all detection and sensing equipment in the entire domain.

[0033] The overall data flow of the system is as follows: raw sensing data collected by all types of detection devices and drones → encryption / signature verification by the quantum secure transmission layer → data normalization, fusion, tracking, identity verification, behavior analysis and risk assessment by the AI ​​intelligent analysis layer → execution of early warning, equipment scheduling and emergency response by the full-domain control and execution layer; at the same time, the AI ​​intelligent analysis layer can send key scheduling instructions to the quantum secure transmission layer in reverse, and the full-domain control and execution layer can send control instructions such as parameter configuration, start and stop, angle adjustment and power adjustment to downstream detection and sensing devices to form a two-way closed-loop control.

[0034] It should be noted that the quantum-secure transmission layer, AI intelligent analysis layer, and global control execution layer correspond to the quantum-secure transmission module, AI intelligent analysis module, and global control execution module, respectively. Here, "layer" describes the system from a vertical hierarchical perspective of the system's logical architecture, while "module" defines it from a functional entity perspective. In this specification, whenever "quantum-secure transmission layer" is mentioned, it refers to the "quantum-secure transmission module"; "AI intelligent analysis layer" refers to the "AI intelligent analysis module"; and "global control execution layer" refers to the "global control execution module." These differences in terminology do not constitute any substantial limitation on the scope of protection of this invention.

[0035] In some embodiments of the present invention, the quantum secure transmission module includes multiple quantum ground stations deployed across the entire domain, wherein the quantum ground stations located in critical airspace and no-fly zones are configured as trusted nodes; The quantum ground station is used to distribute initial quantum keys to the drones and various detection and sensing terminals when they are powered on. Trusted nodes are used to automatically update the quantum key between the drone and the trusted node as the drone passes by.

[0036] This embodiment deploys multiple quantum ground stations across the entire region and configures trusted nodes in key airspace and no-fly zones, enabling UAVs and detection and sensing terminals in each region to obtain initial quantum keys when powered on and automatically update quantum keys when passing trusted nodes during flight. This ensures that key coverage is available across the entire region while achieving real-time updates of key-to-flight location dynamic binding.

[0037] It should be noted that the quantum-secure transmission layer is the underlying secure communication unit. This layer serves as the data transmission and security foundation for the entire system, comprising four main functional modules: a quantum key distribution module, a quantum encrypted communication module, a data transmission module, and a key management center. All modules are interconnected via an internal communication bus. This layer provides comprehensive access to all detection equipment, including passive / active radar detection devices, radio signal detection devices, visible / infrared multi-channel photoelectric imaging detection devices, ADS-B, RemoteID, multi-line lidar detection devices, acoustic drone detection devices, 5G-A sensing base stations, the BeiDou navigation satellite network monitoring system, and general-purpose satellite remote sensing monitoring terminals. All detection data, equipment control commands, and drone commands are encrypted and quantum digitally signed by this layer before transmission, eliminating the risk of data tampering, forgery, and theft.

[0038] In some embodiments of the present invention, the UAV onboard terminal corresponding to the quantum ground station integrates a free-space QKD terminal module. This module structurally and hardware-level binds a single-photon transmitter and receiver unit, a two-dimensional high-precision tracking gimbal, a polarization adaptive correction module, and a flight attitude sensor to form a compact airborne QKD terminal. During operation, the tracking gimbal reads the GPS position and attitude data output by the UAV flight control system in real time, and, combined with the angular deviation information fed back from the ground beacon light, dynamically adjusts the emission direction of the quantum beam to stably lock the beam within the receiving aperture of the ground base station; the polarization correction module is used to compensate for photon polarization state drift caused by atmospheric turbulence and flight vibrations. The entire terminal is adapted to the payload limitations of small UAVs in terms of power consumption, size, and weight.

[0039] In some embodiments of the present invention, such as Figure 2 As shown, the quantum-secure transmission module 100 includes: The quantum key distribution module is used to adaptively adjust the key update frequency according to the key scheduling instructions output by the AI ​​intelligent analysis module; The quantum encryption communication module is used to encrypt and quantum digitally sign the flight data collected by the UAV and the multi-source heterogeneous detection data collected by various detection and sensing terminals to obtain trusted multi-source data; and to encrypt and quantum digitally sign the control commands to obtain trusted control commands. The key management module is used for the full lifecycle management of global quantum keys, including generation, storage, authorization distribution, and expiration destruction.

[0040] In some embodiments of the present invention, the quantum key distribution module is implemented as follows: ① Deployment Location: The main deployment is in quantum key distribution ground stations deployed throughout the region, with trusted nodes deployed in key airspace and no-fly zones; the UAV terminal integrates an airborne key receiving unit; all detection equipment, including passive / active radar detection equipment, radio signal detection equipment, visible light / infrared multi-channel photoelectric imaging detection equipment, ADS-B, RemoteID, multi-line lidar detection equipment, acoustic UAV detection equipment, 5G-A sensing base station, Beidou navigation satellite network monitoring system, and general satellite remote sensing monitoring terminal, have built-in device-side key units; ②Connection relationship: The ground station and the key management center are bidirectionally connected, and trusted nodes are respectively connected to the ground station and passing UAVs and various surrounding detection devices; the UAV onboard unit and the key unit of the detection device are all connected to the quantum encryption communication module; ③ Structure and Implementation: An improved BB84 quantum key protocol is adopted, and a quantum key relay device is used to build a global quantum key distribution (QKD) network; ④ Working Principle: Before starting up, the UAV and various detection equipment request a key from the nearest ground station. After identity verification, the ground station distributes the initial quantum key. During the flight of the UAV and the operation of the detection equipment, the key is automatically updated dynamically each time a trusted node is passed or covered. When the UAV lands after its mission or the detection equipment is shut down for maintenance, the locally stored quantum key is automatically destroyed. At the same time, this module receives scheduling instructions from the AI ​​intelligent analysis layer and adaptively adjusts the key update frequency and transmission path according to the flight risk level, communication load, and various detection data traffic.

[0041] This embodiment achieves initial key distribution and dynamic updates for UAVs and various detection and sensing terminals by deploying quantum key distribution ground stations and trusted nodes across the entire domain. It also constructs a global QKD network by combining an improved BB84 protocol and quantum key relay equipment, ensuring the security of the key distribution process. At the same time, the AI ​​intelligent analysis layer adaptively adjusts the key update frequency and transmission path according to the risk level and communication load, improving the utilization efficiency of key resources while ensuring communication security. The local key is automatically destroyed after the task is completed, forming a complete closed-loop management of the key lifecycle from distribution, update to destruction.

[0042] In some embodiments of the present invention, the specific implementation of the quantum encrypted communication module is as follows: ① Deployment Location: Integrated into UAV airborne equipment, ground stations, control center terminals, as well as passive / active radar detection equipment, radio signal detection equipment, visible light / infrared multi-channel photoelectric imaging detection equipment, ADS-B, RemoteID, multi-line lidar detection equipment, acoustic UAV detection equipment, 5G-A sensing base stations, Beidou navigation satellite network monitoring system, and all local terminals of general satellite remote sensing monitoring terminals; ② Connection relationship: The input end is connected to the quantum key distribution module, and the output end is connected to the data transmission module; ③ Structure and Implementation: Equipped with a "one-time pad" encryption algorithm and a quantum digital signature unit; ④ Working principle: The system uses a local quantum key to encrypt all business data and equipment control commands, including radar echoes, time difference of arrival (TDOA) positioning and direction finding data, photoelectric image data, ADS-B / RemoteID identity broadcast data, lidar 3D point clouds, acoustic audio data, 5G-A sensing data, satellite remote sensing positioning data, UAV flight control commands, and telemetry data. Simultaneously, a quantum digital signature is added to each set of transmitted data for downstream module data integrity and authenticity verification, preventing data tampering and forgery, and ensuring the reliability of all types of detection and sensing data.

[0043] This embodiment ensures the confidentiality and integrity of data transmission by overlaying one-time pad encryption and quantum digital signatures on all business data and device control commands, preventing data from being eavesdropped on, tampered with, or forged, and providing a reliable data source for downstream AI analysis.

[0044] It should be noted that, as Figure 2 As shown, the quantum-safe transmission module also includes a data transmission module.

[0045] In some embodiments of the present invention, the data transmission module is implemented as follows: ① Deployment location: Deployed in pairs with the quantum encryption communication module to cover all communication nodes and all-domain detection equipment; ②Connection relationship: The input end receives encrypted data, and the output end is divided into two paths: one path connects to the AI ​​intelligent analysis layer, and the other path connects to external 5G / 6G, satellite, and wireless self-organizing network equipment; ③Working principle: Real-time monitoring of signal strength, delay, and packet loss rate of each communication link, and automatic switching of the optimal transmission channel; at the same time, compression and fragmentation of large-capacity detection data generated by radar, lidar, photoelectric, satellite, etc., to improve the transmission efficiency of encrypted data.

[0046] This embodiment improves the reliability and continuity of encrypted data transmission through real-time link status monitoring and adaptive gating; at the same time, it improves the transmission efficiency of large-capacity probe data through compression and fragmentation preprocessing.

[0047] It should be noted that the key management module is the corresponding module of the key management center at the functional level. The two are actually different dimensions of the same functional entity. The key management module focuses on the logical functional division, while the key management center focuses on the physical deployment entity.

[0048] In some embodiments of the present invention, the key management center is implemented as follows: ① Deployment location: Centrally deployed in the core control room; ② Connectivity: Maintain long-term connections with all quantum ground stations, trusted nodes, and various remote detection devices across the entire domain; ③Working principle: It is responsible for the entire lifecycle management of quantum key generation, storage, authorization distribution, and expiration destruction, and establishes a key ledger to ensure unified scheduling and security control of keys across the network and keys of all detection devices.

[0049] This embodiment achieves unified scheduling and security control of quantum keys across the entire domain through centralized deployment and full lifecycle management of the key management center, ensuring the traceability and controllability of keys from generation to destruction.

[0050] In some embodiments of the present invention Figure 3 A schematic diagram of a quantum key management process is provided for this invention; as shown. Figure 3 As shown, the basic process of electronic key management is as follows: After the drone or detection device is started, it first sends a key request to the ground station. After the ground station completes the identity verification, it distributes an initial quantum key. The detection device and the drone then enter normal operation and use the key for encrypted communication. During operation, the system continuously detects whether the drone passes through a trusted node. If it does, the trusted node automatically triggers a quantum key update to ensure continuous communication security; if it does not pass through, it continues to use the current key for normal operation. When the mission ends, the device stops, or the drone lands, the system automatically destroys the locally stored quantum key, completing the closed-loop management of the key lifecycle. The entire process achieves full lifecycle security control from key request, initial distribution, dynamic update to final destruction.

[0051] It should be noted that traditional key management uses a fixed-period rotation strategy (e.g., changing the key every 2 minutes), which does not consider the varying security requirements of the aircraft at different flight phases. This invention proposes a dynamic key scheduling algorithm bound to the flight mission: In one embodiment, the algorithm breaks down a single flight mission into six phases: takeoff, climb, cruise, operation, emergency response, and landing, with different key update parameters preset for each phase. During takeoff and landing, the airspace is relatively closed and controllable, and the key rotation frequency is appropriately reduced to save onboard computing power and key generation resources. After entering the long-distance cruise phase, the airspace becomes more complex and security threats increase, so the system automatically increases the key generation rate and rotation frequency. When the aircraft enters the vicinity of a sensitive no-fly zone, the key security level is further enhanced. The entire process is controlled by the flight mission management system issuing phase switching signals, which the quantum security gateway dynamically adjusts the key scheduling strategy accordingly.

[0052] It should be noted that during large-scale UAV swarm collaborative operations (such as formation flying, collaborative mapping, and swarm search and rescue), the aircraft within the swarm need to frequently exchange collaborative commands and sensor data. If all communication is relayed through the ground control center, it not only increases latency but also makes the ground link a bottleneck for system capacity. This invention designs a low-altitude Mesh quantum routing negotiation process to address this problem: In one embodiment, any two drones within a swarm equipped with free-space QKD terminals can directly establish a temporary quantum key link without requiring all key negotiation traffic to flow back to the ground. Each drone periodically broadcasts its QKD link status to its neighbors (other nearby drones). When secure communication with another drone not within direct range is needed, end-to-end key establishment is achieved through hop-by-hop quantum relays via intermediate drones. If a QKD link is interrupted due to obstruction or drone maneuvering, the routing protocol automatically switches to a backup relay path, completing link convergence within seconds without affecting the continuity of upper-layer encrypted communication.

[0053] In one embodiment, at the wireless communication layer, this invention designs a physical channel-level isolation scheme to defend against air interface attacks. The 5G public network or ad hoc network radio frequency channel between the drone and the ground only carries encrypted ciphertext data, while quantum key distribution uses an independent optical free-space channel. The two channels are completely separated in terms of physical medium. The security effect of this design is that even if an attacker intercepts all radio frequency communication content, the intercepted ciphertext cannot be decrypted because there is no key distributed on the quantum channel.

[0054] Based on this, the system continuously monitors the quantum error rate (QBER) and single-photon count statistics of the quantum channel. The inputs to the judgment model include the real-time QBER (Quantum Bit Error Rate) value of the air-to-ground quantum link, statistical fluctuations in the single-photon detector count rate, and real-time measurement data of atmospheric channel parameters. The model decomposes QBER changes into environmental factor contributions and potential eavesdropping contributions, setting a dynamic threshold: when the QBER exceeds the range explainable by environmental fluctuations and persists for more than a preset time window, it is judged as a suspected eavesdropping event. The handling process adopts a three-level linkage: first, the current batch of quantum keys is marked and destroyed in the key management module; second, alarm information is uploaded to the ground control center, including the event timestamp, aircraft number, GPS coordinates, and abnormal QBER value; third, a quantum key-encrypted forced return or hovering command is simultaneously issued to remove the aircraft from the eavesdropped airspace. The entire judgment and handling link is executed simultaneously on both the aircraft and the ground control center.

[0055] In one embodiment, the QKD subnetworks of each department's control system are interconnected through trusted relay nodes. The trusted relay nodes use a hop-by-hop quantum key encryption and decryption method to complete the cross-network key transmission. The relay nodes cannot obtain the final session key at the end, ensuring the security of the key during the cross-domain exchange process.

[0056] This embodiment employs a combination of quantum key relay, trusted nodes, and AI dynamic scheduling to achieve dynamic quantum key distribution for all types of detection devices, including high-speed mobile drones, distributed radar detection equipment, radio signal detection equipment, and visible / infrared multi-channel photoelectric imaging detection equipment. This solves the industry problem that traditional QKD networks cannot adapt to mobile terminals and distributed heterogeneous sensing devices.

[0057] In some embodiments of the present invention, the quantum-secure transmission module interfaces with the low-altitude airspace management platform through a dual-gateway physical isolation architecture to reduce modifications to existing business systems. This architecture adds two independent hardware gateway modules to the front end of the low-altitude airspace management platform: a business gateway for handling the transmission, reception, and routing of regular low-altitude business messages, and a quantum-secure gateway directly connected to the local QKD node, independently performing quantum key negotiation, key caching, and encryption operations. The two gateways are physically isolated; the business gateway only delivers plaintext messages to be sent to the quantum-secure gateway for encryption and does not reverse the process to obtain the plaintext key. Existing low-altitude airspace management systems do not need to be aware of the quantum layer; all business messages entering and leaving the platform are automatically encrypted and decrypted by the quantum-secure gateway, and the original business processes and data formats remain unchanged.

[0058] In some embodiments of the present invention, the quantum encrypted communication module employs a layered hybrid encryption process to encrypt business data: a truly random quantum key generated by QKD is used as the root key; a short-lifespan session key is negotiated using the root key; and then the actual business data is encrypted using the SM4 national standard symmetric algorithm. The root key is consumed only during the session key negotiation phase; after negotiation, the session key can be used for rapid encryption and decryption of subsequent large volumes of data. The session key rotation cycle is tied to the flight phase, with shorter rotation intervals during critical phases and more relaxed intervals during non-critical phases. The quantum root key is used to protect the distribution process of the SM4 session key, ensuring that the security of the key negotiation process does not depend on computational complexity assumptions.

[0059] It should be noted that the AI ​​intelligent analysis layer is the core data processing and decision-making unit. This layer is the core of the system's intelligent judgment. Its input end receives encrypted, signed, and verified multi-source sensing data uploaded by the quantum-secure transmission layer, such as... Figure 2 As shown, the system incorporates four pre-processing units: multi-source heterogeneous data normalization, environmental perception and dynamic confidence assessment, AI multi-target tracking and trajectory fusion, and dynamic identity authentication and flight behavior analysis. Post-processing modules include multi-source data fusion, intelligent target recognition, flight trajectory prediction, and intelligent risk assessment. The output pushes analysis results, risk commands, and global detection device scheduling commands to the overall control execution layer, while simultaneously outputting key scheduling commands to the quantum secure transmission layer. All units and modules are connected in series according to the data flow direction.

[0060] In some embodiments of the present invention, after receiving trusted multi-source data, the AI ​​intelligent analysis module verifies the quantum digital signature of the trusted multi-source data, and obtains trusted verification data after the verification is successful.

[0061] This embodiment verifies the quantum digital signature before AI analysis to ensure that the probe data entering the analysis stage is authentic and its content has not been tampered with, thus guaranteeing the reliability of subsequent data fusion and risk assessment results from the source.

[0062] In some embodiments of the present invention, such as Figure 2 As shown, the AI ​​intelligent analysis module includes: The multi-source heterogeneous data normalization unit is used to convert reliable verification data with different data formats and coordinate systems into standardized detection data with a unified data format and coordinate system. The environmental perception and confidence dynamic assessment unit is used to assess the confidence of standardized detection data based on the current environmental conditions, and to assign fusion weights to the standardized detection data of each detection and sensing terminal based on the confidence assessment results, thereby generating standardized detection data with confidence labels.

[0063] In some embodiments of the present invention, the specific implementation of the multi-source heterogeneous data normalization unit is as follows: ① Deployment location: Deployed at the front end of the AI ​​server cluster; ②Connection relationship: The input end is connected to the quantum-safe transmission layer, and the output end is connected to the environmental perception and confidence dynamic assessment unit; ③Working Principle: A unified data model and standardized interface are established to uniformly convert, align, register coordinates, and unify dimensions heterogeneous sensing data of different standards, coordinate systems, and data formats, such as passive / active radar detection equipment, radio signal detection equipment, visible light / infrared multi-channel photoelectric imaging detection equipment, ADS-B, RemoteID, multi-line lidar detection equipment, acoustic fingerprint drone detection equipment, 5G-A sensing base stations, Beidou navigation satellite network monitoring systems, and general satellite remote sensing monitoring terminals. This enables standardized access and centralized management of all types of detection data, solving the problems of incompatibility and inability to conduct joint analysis of data from multiple devices.

[0064] This embodiment eliminates the problems of incompatible data formats and inability to perform linked analysis across multiple devices by establishing a unified data model and standardized interfaces, laying the foundation for subsequent data fusion processing.

[0065] In some embodiments of the present invention, the specific implementation of the environmental perception and confidence dynamic assessment unit is as follows: ①Connection relationship: The input end receives normalized data, and the output end is connected to the AI ​​multi-target tracking and trajectory fusion unit; ②Working principle: It connects to a 3D geographic information system to predict obstructed areas such as buildings, trees, and terrain in the city; combined with real-time weather, electromagnetic environment, and lighting conditions, it dynamically evaluates the confidence level of individual data sets based on the inherent defects of different detection devices: for example, it reduces the weight of photoelectric and lidar data in rainy weather, reduces the weight of radio detection data from time difference of arrival positioning technology in electromagnetically complex areas, and weakens the validity of ADS-B / RemoteID data in obstructed areas; it dynamically allocates data acceptance weights according to the confidence level to reduce the probability of false alarms and misjudgments from the source.

[0066] This embodiment reduces the probability of false alarms and misjudgments from the source by dynamically assessing the environment and confidence level, and adaptively allocating data weights according to the inherent defects of different detection devices and real-time environmental conditions.

[0067] In some embodiments of the present invention, such as Figure 2 As shown, the AI ​​intelligent analysis module also includes: The multi-target tracking and trajectory fusion unit is used to associate, deduplicate, and fuse multiple target trajectories from various detection and sensing terminals within the same time period based on standardized detection data with confidence labels, so as to generate unique fused trajectory data for the same UAV target.

[0068] In some embodiments of the present invention, the specific implementation of the multi-target tracking and trajectory fusion unit (AI multi-target tracking and trajectory fusion unit) is as follows: ①Connection relationship: The input end receives the dataset after confidence labeling, and the output end is connected to the dynamic identity authentication and flight behavior analysis unit; ②Working principle: Based on deep learning algorithms, multiple target trajectories output by multiple devices are associated, deduplicated, and fused to eliminate multi-trajectory conflicts and repeated tracking problems, generating a unique and reliable track for the same UAV target, and integrating the detection advantages of different devices to make up for the shortcomings of a single device.

[0069] It should be noted that the "multi-target tracking and trajectory fusion unit" and the "AI multi-target tracking and trajectory fusion unit" are the same module. They utilize deep learning algorithms to correlate, deduplicate, and fuse multi-source target trajectories, generating a unique fused trajectory. Deep learning, as a method of AI implementation, refers to the same technical concept in this invention.

[0070] This embodiment eliminates multi-track conflicts and repeated tracking problems by associating, deduplicating, and fusing target trajectories from multiple devices, generating a unique track, thereby integrating the advantages of multi-device detection and making up for the shortcomings of single-device capabilities.

[0071] In some embodiments of the present invention, the specific implementation of the dynamic identity authentication and flight behavior analysis unit is as follows: ①Connection relationship: The input end receives fused track data, and the output end is connected to the multi-source data fusion module; ②Working principle: Dynamic identity verification is carried out by combining ADS-B / RemoteID identity information, device identification code, pre-reported flight plan, and electronic fence airspace rules; behavioral analysis is carried out by comprehensively considering the target's flight speed, altitude, route, stopping area, and maneuvering characteristics to accurately distinguish between compliant flights, illegal flights, and "black flights" targets.

[0072] This embodiment combines dynamic identity verification with flight behavior analysis to accurately distinguish between compliant flights, illegal flights, and unauthorized flights, thus solving the regulatory blind spot problem caused by the ease with which single identity recognition can be forged or disabled.

[0073] In some embodiments of the present invention, such as Figure 2 As shown, the AI ​​intelligent analysis module also includes: The multi-source data fusion module is used to fuse multi-source heterogeneous detection data collected by different types of detection and sensing terminals based on the fused trajectory data, and generate multi-source fused sensing data. The target identification unit is used to identify the aircraft type and flight attitude of the target based on multi-source fusion sensing data and generate target identification results; The flight trajectory prediction unit is used to predict the target's flight trajectory within a preset time period based on multi-source fusion sensing data and real-time environmental information, and generate flight trajectory prediction results.

[0074] In some embodiments of the present invention, the specific implementation of the multi-source data fusion module is as follows: ① Deployment location: Deployed on the AI ​​server cluster; ② Connection relationship: The input end connects to the dynamic identity authentication and behavior analysis unit, and the output end connects to the intelligent target recognition module; ③Working principle: Employing a Transformer-based multimodal fusion algorithm, it integrates the data advantages of all detection devices across the entire domain to form complementary sensing capabilities. —Radar (Low-altitude gap-filling / phased array radar): Leveraging its advantages of all-weather and all-day operation, long detection range, measurable position / velocity / altitude, and multi-target tracking, it is responsible for coarse detection of targets over a wide area; addressing the problem of weak identification of low-altitude clutter and slow-moving small targets, it works in conjunction with other equipment for supplementary verification. —Time difference of arrival positioning technology / radio detection: It leverages the characteristics of passive detection, wide frequency coverage, and the ability to identify equipment models / serial numbers to capture UAV remote control and image transmission signals, supplementing positioning and identification information, and making up for the deficiency in detecting silent flying targets; — Photoelectric (visible light + infrared): Utilizing the advantages of intuitive imaging, evidence collection, and identification of aircraft type and mount, it completes visual verification of close-range targets, making up for the difficulty of radar in distinguishing between drones, birds, and kites; it is greatly affected by weather and obstruction, and only valid data within line of sight is accepted; —ADS-B / RemoteID: Relying on proactive identity reporting, high positioning accuracy, and real-name traceability capabilities, it completes the identity verification of compliant drones; addressing the shortcomings of easy forgery and reliance on satellite navigation, it combines cross-verification with other devices; —LiDAR: Leveraging its advantages of high three-dimensional precision and resistance to frequency interference, it is used for refined monitoring of high-density near-field areas; —Acoustic detection: With its passive detection capabilities, ability to identify low-altitude, low-speed, silent targets, and flexible deployment, it supplements the perception of near-field low-speed, small targets and reduces the interference caused by urban noise. ——5G-A Sensing Base Station: Leveraging the advantages of integrated communication and sensing, wide coverage, and easy networking, it fills gaps in coverage of non-cooperative targets over a large area; —Satellite / BeiDou space-based equipment: Utilizing the characteristics of no terrain obstruction and wide-area coverage, it can fill in the situational awareness gaps in remote areas and maritime airspace, and make up for the coverage blind spots of ground equipment.

[0075] This embodiment integrates the complementary advantages of all types of detection equipment through a multimodal fusion algorithm, making up for the inherent shortcomings of single equipment in scenarios such as clutter interference, silent targets, and environmental obstruction, and improving the comprehensive perception capability of low-altitude targets in complex environments.

[0076] In some embodiments of the present invention, the target recognition module (intelligent target recognition unit) is implemented as follows: ①Connection relationship: The input end receives the fused sensing data, and the output end is connected to the flight trajectory prediction module; ②Working principle: The improved YOLOv8 target detection algorithm is adopted, combined with industry knowledge graph, and integrates feature data from multiple devices to jointly identify the aircraft type, subject, real-time flight attitude, and flight parameters of low-altitude targets, and output accurate identification results.

[0077] This embodiment improves the accuracy and dimensionality of aircraft type identification for low-altitude targets by combining an improved YOLOv8 algorithm with industry knowledge graphs and multi-device feature fusion.

[0078] In some embodiments of the present invention, the specific implementation of the flight trajectory prediction unit (flight trajectory prediction module) is as follows: ①Connection relationship: The input end connects to the intelligent target recognition module, and the output end connects to the intelligent risk assessment module; ②Working principle: The LSTM-Attention time-series prediction algorithm is used, combined with continuous positioning data from multiple devices, historical flight data, real-time weather, and airspace geographic information, to predict the flight trajectory of the UAV in the next 5 to 10 minutes.

[0079] This embodiment uses the LSTM-Attention temporal prediction algorithm combined with multi-dimensional data to achieve forward prediction of future flight trajectories, changing the passive situation of traditional systems that can only issue warnings after the fact.

[0080] In some embodiments of the present invention, such as Figure 2 As shown, the AI ​​intelligent analysis module also includes: The risk assessment module is used to classify the risk of each UAV’s airspace attributes, identity authentication results and behavioral characteristics based on the target identification results, flight trajectory prediction results and fused flight trajectory data, and in combination with preset airspace rules, and generate risk assessment results.

[0081] In some embodiments of the present invention, the risk assessment module (intelligent risk assessment module) is implemented as follows: ①Connection relationship: The input end receives trajectory prediction data, and the output end is divided into two paths: one path connects to the global control and execution layer, and the other path connects in reverse to the quantum secure transmission layer; ②Working principle: Based on the risk knowledge graph model, the risk is divided into four levels: low, medium, high, and extremely high, by comprehensively considering multiple parameters such as flight position, altitude, speed, trajectory, airspace attributes, identity authentication results, behavioral characteristics, and data confidence. Risk assessment reports, early warning instructions, and coordinated scheduling instructions for all-domain detection equipment are generated. At the same time, based on the risk level, communication traffic, and detection data volume, key adjustment instructions are issued to the quantum secure transmission layer.

[0082] This embodiment achieves a four-level risk classification through multi-dimensional parameter fusion and knowledge graph risk assessment; at the same time, it realizes bidirectional collaborative linkage between AI and quantum encryption by reverse scheduling the quantum key update strategy according to the risk level and communication load.

[0083] In some embodiments of the present invention Figure 4 This is a schematic diagram of an embodiment of the AI ​​intelligent analysis provided by the present invention; as follows: Figure 4 As shown, the AI ​​intelligent analysis module first receives all types of detection data and performs quantum digital signature verification. After successful verification, it sequentially performs multi-source heterogeneous data normalization, environmental perception, and dynamic confidence assessment to generate standardized detection data with confidence labels. Subsequently, it generates a unique fused flight track through AI multi-target tracking fusion, and performs dynamic identity authentication and flight behavior analysis based on this flight track. On this basis, it calls a multi-modal data fusion algorithm to deeply fuse all types of detection data, and performs intelligent target recognition and flight trajectory prediction respectively. Finally, the intelligent risk assessment model generates a risk assessment result by integrating multi-dimensional parameters. Based on the assessment result, it synchronously outputs disposal warning instructions, equipment scheduling instructions to the overall control execution layer, and key scheduling instructions to the quantum secure transmission layer, realizing the coordinated linkage of AI intelligent analysis and quantum key scheduling, and continuously executing the above process in real time.

[0084] This invention establishes a standardized model and unified interface for the normalization of multi-source heterogeneous data. It combines environmental perception and dynamic confidence assessment, AI multi-target tracking trajectory fusion, dynamic identity authentication and flight behavior analysis technologies to achieve comprehensive governance of multi-device data. Based on quantum digital signatures, it completes the verification of detection data for all categories. Combined with Transformer multimodal fusion algorithm and knowledge graph, it integrates heterogeneous data from multiple devices to build an AI risk analysis system based on trusted data, thereby avoiding analysis errors caused by data tampering and data conflicts from the source.

[0085] It should be noted that the overall control execution layer is the terminal execution and visualization unit. This layer is the final execution unit of the system, receiving risk assessment results and equipment scheduling instructions from the AI ​​intelligent analysis layer, and completing actions such as early warning, overall detection equipment scheduling, emergency response, and data display. All control instructions issued externally (including drone instructions and detection equipment parameter instructions) are transmitted back to the quantum-secure transmission layer for encryption before being sent out. It includes a risk early warning module, an intelligent emergency response module, a drone scheduling module, an overall detection equipment unified scheduling module, and a data visualization module.

[0086] In some embodiments of the present invention, such as Figure 2 As shown, the global control execution module includes: The risk warning module is used to output corresponding warning information based on the risk assessment results output by the AI ​​intelligent analysis module, and send the warning information to the regulatory terminal through at least one of the following methods: sound and light, SMS, APP push or large screen display. The emergency response module is used to execute corresponding emergency response actions based on the risk level in the risk assessment results. When the risk level is low, a warning message is sent to the pilot. When the risk level is medium, the jamming equipment is activated and surrounding detection equipment is dispatched to enhance monitoring; When the risk level is high, intercept drones will be dispatched to intercept illegal targets; When the risk level is extremely high, multiple departments will work together to handle the violations across the entire region.

[0087] In some embodiments of the present invention, the risk warning module is implemented as follows: ① Deployment locations: Control center, various monitoring substations, and mobile terminals; ②Connectivity: The input end connects to the AI ​​intelligent analysis layer, and externally connects to sound and light alarm devices, SMS platform, mobile APP, and electronic map terminal; ③Working principle: Based on the risk level, warnings are issued through multiple channels such as sound and light, SMS, APP push, and large screen prompts; the location, risk level, target identity, behavioral characteristics, monitoring status and data confidence level of all surrounding detection devices are simultaneously marked on the electronic map.

[0088] This embodiment combines multi-channel early warning dissemination with electronic map visualization, enabling regulators to quickly locate risk targets and grasp the surrounding situation, thereby improving the efficiency of early warning information transmission and the intuitiveness of situational awareness.

[0089] In some embodiments of the present invention, the specific implementation of the emergency response module (intelligent emergency response module) is as follows: ①Connectivity: The input end connects to the risk warning module, and externally connects to drone jamming equipment, drone interception devices, and terminals of collaborative departments such as public security / civil aviation / fire departments; ②Working principle: Different levels of risk are handled in a tiered manner, such as... Figure 5 As shown: —Low risk: Automatically sends alerts to the pilot and maintains routine equipment monitoring; —Medium risk: Automatically activate jamming equipment, dispatch surrounding radars, time difference of arrival positioning technology, and optoelectronic equipment to enhance network monitoring; —High risk: Automatic dispatching and interception of drones, and coordinated cross-regional multi-type detection equipment to track targets; —Extremely high risk: Automatically activates emergency response plan, linking multiple departments and a full-domain perception network to lock and track targets in all dimensions; all disposal instructions and equipment control instructions are transmitted after being encrypted through a quantum-secure transmission layer.

[0090] In some embodiments of the present invention, such as Figure 2 As shown, the global control and execution module also includes a drone scheduling module.

[0091] This embodiment improves the efficiency and reliability of emergency response in sudden scenarios by using a hierarchical automated handling logic to match differentiated emergency strategies and relying on quantum-encrypted command transmission to ensure the security and reliability of handling commands.

[0092] In some embodiments of the present invention, the specific implementation of the UAV scheduling module is as follows: ① Connectivity: Connects to compliant drones and emergency interception equipment across the entire domain; ②Working principle: Combines airspace status and flight mission to intelligently plan flight routes and avoid collision risks; supports issuing remote control and forced landing commands to illegal drones.

[0093] This embodiment is based on a four-level risk classification standard, matching the corresponding automated emergency response logic with the linkage scheduling logic of all types of detection equipment, and combining quantum encrypted command transmission to achieve cross-departmental, cross-regional, and cross-equipment full-domain intelligent emergency linkage.

[0094] In some embodiments of the present invention, such as Figure 2 As shown, the global control execution module also includes: The unified scheduling module for all-domain detection equipment is used to issue control commands to each detection and sensing terminal. The control commands include at least one of the following: equipment start / stop, angle adjustment, power adjustment, network linkage, or mode switching.

[0095] In some embodiments of the present invention, the specific implementation of the unified scheduling module for global detection equipment is as follows: ①Connectivity: The input end receives device scheduling commands from the AI ​​layer, and the output end connects to all detection devices such as passive / active radar detection devices, radio signal detection devices, visible light / infrared multi-channel photoelectric imaging detection devices, ADS-B, RemoteID, multi-line lidar detection devices, acoustic drone detection devices, 5G-A sensing base stations, Beidou navigation satellite network monitoring systems, and general satellite remote sensing monitoring terminals; ②Working principle: Based on the risk area, target movement trajectory, environmental obstruction and weather conditions, remotely complete the start-up and shutdown of detection equipment, angle adjustment, power adjustment, network linkage and mode switching; when the target leaves the monitoring range of a single device, it automatically switches to adjacent areas and different types of detection equipment to track in turn, combining the advantages and disadvantages of various devices to form a complementary network, and realizes seamless connection of the whole-domain perception network.

[0096] This embodiment achieves collaborative networking and seamless connection between detection devices through remote unified scheduling and dynamic relay tracking of AI-driven global detection devices, effectively eliminating monitoring blind spots caused by the limited coverage of a single device and improving the continuous tracking capability of low-altitude targets in complex environments.

[0097] In some embodiments of the present invention, such as Figure 2 As shown, the overall control and execution module also includes a data visualization module.

[0098] In some embodiments of the present invention, the data visualization module is implemented as follows: ①Connectivity: Access to full system operation data, AI analysis data, operating status of all detection devices, collected data, data confidence level, and fused tracks; ②Working principle: Based on 3DGIS three-dimensional geographic information technology, it displays the flight status of UAVs across the entire area, the distribution of all types of detection equipment, their operating status, monitoring images and data confidence levels in real time; it automatically generates statistical reports, equipment operation ledgers, target identity ledgers and incident handling ledgers to support regulatory decision-making.

[0099] This embodiment uses 3DGIS three-dimensional geographic information technology to visualize the overall flight situation, equipment status and confidence information in real time, and automatically generates statistical reports and operation and maintenance ledgers, providing intuitive and comprehensive data support for regulatory decision-making, and improving the situational awareness capability and operation and maintenance management efficiency of low-altitude airspace.

[0100] The quantum-secure transmission layer provides trusted data for the AI ​​intelligent analysis layer. All detection and flight data of all categories entering the AI ​​analysis stage carry quantum digital signatures. The AI ​​module verifies the signatures before analysis, completely avoiding analysis errors caused by data tampering or data poisoning.

[0101] Building upon this foundation, the AI-powered intelligent analysis layer enables end-to-end data processing and bidirectional optimization. It addresses the issue of fragmented data across multiple devices through multi-source data normalization, confidence assessment, trajectory fusion, and identity and behavior analysis. Simultaneously, it dynamically adjusts the quantum key update strategy based on risk level, communication load, and probe data flow, resolving the "security versus efficiency" conflict inherent in traditional quantum communication.

[0102] Furthermore, the overall control execution layer relies on a two-layer capability for implementation and control. Both execution commands and detection equipment scheduling commands are generated by AI and transmitted encrypted via quantum links, achieving a fully closed-loop linkage of "multi-device collaborative perception, data integration, intelligent analysis, secure transmission, and precise execution," rather than a simple superposition of various technologies or devices.

[0103] In addition, all types of detection equipment are deeply integrated with the three-layer architecture: various detection devices serve as the front-end perception entry point of the system, data is transmitted with encryption throughout the entire link, the operating status and working mode are uniformly scheduled by the control layer, and the perception results feed back into AI to complete the fusion analysis, making full use of the advantages and disadvantages of different devices to form complementarity, and eliminating the shortcomings and blind spots of single device monitoring.

[0104] This invention establishes an integrated closed-loop architecture encompassing quantum secure transmission, multi-source collaborative sensing, AI data governance and intelligent analysis, and full-domain execution and handling. This architecture achieves deep coupling and bidirectional linkage among four major modules: quantum communication, AI, full-domain control, and all types of detection equipment, rather than simply piecing together functions.

[0105] In some embodiments of the present invention, the complete working process of the system is as follows: Before takeoff of the UAV and before the activation of various detection devices across the entire area, initial quantum keys are applied for and obtained from the nearest quantum ground station. During UAV flight and operation of detection equipment, all data collected, equipment control commands, and flight commands from passive / active radar detection equipment, radio signal detection equipment, visible light / infrared multi-channel photoelectric imaging detection equipment, ADS-B, RemoteID, multi-line lidar detection equipment, acoustic UAV detection equipment, 5G-A sensing base stations, BeiDou navigation satellite network monitoring systems, and general satellite remote sensing monitoring terminals are quantum encrypted and quantum digitally signed before being uploaded through the data transmission module.

[0106] The quantum-secure transmission layer pushes multi-source trusted detection data to the AI ​​intelligent analysis layer, which sequentially performs multi-source heterogeneous data normalization, environmental perception and confidence assessment, AI multi-target trajectory fusion, dynamic identity authentication and behavior analysis, multi-modal data fusion, target recognition, trajectory prediction, and risk classification, while simultaneously generating global detection device scheduling instructions. The AI ​​module outputs the risk classification results and device scheduling instructions to the global control execution layer, and simultaneously sends key scheduling instructions to the quantum-secure transmission layer.

[0107] The control and execution layer implements tiered early warnings, coordinated scheduling of all types of detection equipment, drone scheduling, and emergency response based on risk levels. All external commands are transmitted with unified encryption. After an incident is handled, the system automatically archives all process data, equipment operation records, and handling logs. When a drone lands and stops flying or a detection device is shut down for maintenance, the device automatically destroys the quantum key stored on its own.

[0108] In some embodiments of the present invention, taking the urban low-altitude drone management scenario as an example, the system deployment and operation are as follows: 1) Deploy three quantum key distribution ground stations throughout the city, and configure trusted nodes with key relay capabilities in key areas such as airports, government districts, and business districts to build a local quantum communication network; configure quantum encryption and key units for all compliant drones, all-area passive / active radar detection equipment, radio signal detection equipment, visible light / infrared multi-channel photoelectric imaging detection equipment, ADS-B, RemoteID, multi-line lidar detection equipment, acoustic drone detection equipment, 5G-A sensing base stations, Beidou navigation satellite network monitoring systems, and general satellite remote sensing monitoring terminals.

[0109] The parameters "3 ground stations" are for illustrative purposes only. The specific number and location of deployments should be flexibly adjusted according to the actual airspace range and control requirements, and should not limit the scope of protection of this invention.

[0110] 2) Deploy an AI server cluster in the control center, build a unified data model and standard interface, and connect to a full range of data sources, including passive / active radar detection equipment, radio signal detection equipment, visible light / infrared multi-channel photoelectric imaging detection equipment, ADS-B, RemoteID, multi-line lidar detection equipment, acoustic drone detection equipment, 5G-A sensing base stations, Beidou navigation satellite network monitoring system, and general satellite remote sensing monitoring terminals; complete the deployment of Transformer fusion algorithm, YOLOv8, LSTM-Attention, and knowledge graph, and build multi-source data normalization, confidence assessment, trajectory fusion, and identity and behavior analysis functional modules.

[0111] 3) Establish a control and command center, deploy 3DGIS three-dimensional visualization screens, early warning terminals, drone jamming equipment, and drone interception equipment, and build a centralized control platform for all types of detection equipment.

[0112] 4) After the system goes online, the above-mentioned workflow will be followed to achieve routine monitoring of drones across the entire area and unified operation and maintenance of detection equipment. When a drone is detected to have entered the airport's no-fly zone (extremely high risk), the system will immediately issue a red alert across the entire area, automatically send a drive-away command, activate jamming equipment, and dispatch interceptor drones. Simultaneously, the system will link up with multiple types of equipment, such as passive / active radar detection equipment, radio signal detection equipment, visible light / infrared multi-channel photoelectric imaging detection equipment, and ADS-B / RemoteID, to conduct network tracking. The system will combine the complementary monitoring of equipment characteristics and rely on AI behavior analysis to determine the nature of unauthorized flights. The system will also coordinate with multiple departments, such as airports and public security, to handle the situation. After the handling is completed, a review report and a full-dimensional ledger will be automatically generated.

[0113] Compared to existing single encryption systems, single AI early warning systems, traditional regional control systems, and independent operation modes of detection equipment, this invention deeply integrates quantum encryption, artificial intelligence, all-domain control, and a full range of low-altitude detection and sensing equipment. It also incorporates multi-source data normalization, trajectory fusion, identity and behavior analysis, and confidence assessment capabilities to form a complete closed-loop system with the following advantages: 1) Communication security: This invention uses quantum key distribution combined with one-time pad encryption and quantum digital signature mechanism to encrypt the entire domain detection data and control commands, which can resist attacks such as quantum computing cracking, data tampering and command hijacking; at the same time, relying on the artificial intelligence module to dynamically adjust the key update strategy according to the communication load and risk level, it can effectively reduce the bandwidth loss of quantum communication links in the conventional electromagnetic environment of urban low-altitude.

[0114] 2) In terms of collaborative perception: integrate multiple detection devices such as radar, lidar, photoelectric, and radio detection, and utilize the complementary detection characteristics of different devices to eliminate the monitoring blind spots and false alarms of single devices, thereby improving the all-domain detection capability of low, slow and small UAV targets.

[0115] 3) Data processing and early warning: Through multi-source heterogeneous data normalization, confidence dynamic assessment and trajectory fusion technology, the data format and coordinate system of multiple devices are unified; combined with multimodal artificial intelligence algorithms, target recognition and trajectory prediction are realized, effectively reducing the probability of target misjudgment and omission in urban low-altitude scenarios, and realizing early warning of flight risks.

[0116] 4) Emergency response: The system realizes fully automated data analysis, risk assessment and instruction issuance, eliminating the need for manual data collection and assessment, and significantly shortening the emergency response time for low-altitude illegal drone incidents.

[0117] 5) Comprehensive attack resistance: AI monitors quantum links and various detection devices for data anomalies in real time and quickly blocks attacks. The full-domain redundant backup architecture avoids single points of failure and improves comprehensive attack resistance.

[0118] 6) Scalability and compatibility: Adopting a modular design, it can seamlessly connect with existing civil aviation ADS-B systems, security radars, drone RemoteID monitoring platforms, radio monitoring systems, public security command platforms, and various mainstream detection equipment. The standard interface facilitates future function upgrades and module expansion, and is suitable for low-altitude control needs in all scenarios.

[0119] 7) Technological integration achieves synergistic efficiency; quantum encryption provides AI with a trusted data source for detection, and AI completes multi-source data governance, optimizes quantum key scheduling, and intelligently schedules all-domain detection devices. The application value of the two technologies and the sensing network is realized in the implementation of all-domain control. The four empower each other, with a comprehensive control efficiency of ≥98%, a security incident handling success rate of ≥98.5%, and an overall efficiency of 2 to 3 times that of a single technology or single device system.

[0120] The above provides a detailed description of the quantum encryption and AI-assisted low-altitude UAV full-domain control system provided by this invention. Specific examples have been used to illustrate the principles and implementation methods of this invention. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of this invention. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this invention. Therefore, the content of this specification should not be construed as a limitation of this invention.

Claims

1. A low-altitude unmanned aerial vehicle (UAV) all-domain control system that combines quantum encryption and AI, characterized in that: include: The quantum-secure transmission module is used to distribute quantum keys to the UAV and various detection and sensing terminals, and to encrypt and quantum digitally sign the flight data collected by the UAV and the multi-source heterogeneous detection data collected by various detection and sensing terminals based on the quantum keys, so as to obtain trusted multi-source data. The AI ​​intelligent analysis module is communicatively connected to the quantum secure transmission module and is used to predict flight trajectories based on the trusted multi-source data, and output risk assessment results and key scheduling instructions. The quantum-secure transmission module is also used to respond to the key scheduling instruction to adjust the key update frequency; The global control execution module is communicatively connected to the quantum-secure transmission module and the AI ​​intelligent analysis module. It is used to generate control instructions based on the risk assessment results, and then send the control instructions to the drone and various detection and sensing terminals for execution after being encrypted and quantum digitally signed by the quantum-secure transmission module.

2. The quantum encryption and AI-assisted low-altitude UAV full-domain control system according to claim 1, characterized in that, The quantum secure transmission module includes multiple quantum ground stations deployed across the entire region, among which the quantum ground stations located in key airspace and no-fly zones are configured as trusted nodes; The quantum ground station is used to distribute an initial quantum key to the UAV and each detection and sensing terminal when they are powered on. The trusted node is used to automatically update the quantum key between the drone and the trusted node when the drone passes by.

3. The quantum encryption and AI-assisted low-altitude UAV full-domain control system according to claim 1, characterized in that, The quantum-secure transmission module includes: The quantum key distribution module is used to adaptively adjust the key update frequency according to the key scheduling instructions output by the AI ​​intelligent analysis module; The quantum encryption communication module is used to encrypt and quantum digitally sign the flight data collected by the UAV and the multi-source heterogeneous detection data collected by each of the aforementioned detection and sensing terminals to obtain trusted multi-source data; and to encrypt and quantum digitally sign the control commands to obtain trusted control commands. The key management module is used for the full lifecycle management of global quantum keys, including generation, storage, authorization distribution, and expiration destruction.

4. The quantum encryption and AI-assisted low-altitude UAV full-domain control system according to claim 1, characterized in that, After receiving the trusted multi-source data, the AI ​​intelligent analysis module verifies the quantum digital signature of the trusted multi-source data. Once the verification is successful, trusted verification data is obtained.

5. The quantum encryption and AI-assisted low-altitude UAV full-domain control system according to claim 4, characterized in that, The AI ​​intelligent analysis module includes: A multi-source heterogeneous data normalization unit is used to convert the trusted verification data with different data formats and coordinate systems into standardized detection data with a unified data format and coordinate system. The environmental perception and confidence dynamic evaluation unit is used to evaluate the confidence of the standardized detection data according to the current environmental conditions, and to assign fusion weights to the standardized detection data of each detection and perception terminal according to the confidence evaluation results, so as to generate standardized detection data with confidence labels.

6. The quantum encryption and AI-assisted low-altitude drone full-domain control system according to claim 5, characterized in that, The AI ​​intelligent analysis module also includes: The multi-target tracking and trajectory fusion unit is used to associate, deduplicate, and fuse multiple target trajectories from various detection and sensing terminals within the same time period based on the standardized detection data with confidence labels, so as to generate unique fused trajectory data for the same UAV target.

7. The quantum encryption and AI-assisted low-altitude UAV full-domain control system according to claim 6, characterized in that, The AI ​​intelligent analysis module also includes: The multi-source data fusion module is used to fuse multi-source heterogeneous detection data collected by different types of detection and sensing terminals based on the fused trajectory data to generate multi-source fused sensing data. The target identification unit is used to identify the aircraft type and flight attitude of the target based on the multi-source fusion sensing data, and generate a target identification result; The flight trajectory prediction unit is used to predict the flight trajectory of the target within a preset time period based on the multi-source fusion sensing data and real-time environmental information, and generate a flight trajectory prediction result.

8. The quantum encryption and AI-assisted low-altitude drone full-domain control system according to claim 7, characterized in that, The AI ​​intelligent analysis module also includes: The risk assessment module is used to classify the airspace attributes, identity authentication results, and behavioral characteristics of each UAV based on the target identity recognition results, the flight trajectory prediction results, and the fused flight trajectory data, and in combination with preset airspace rules, and generate risk assessment results.

9. The quantum encryption and AI-assisted low-altitude drone full-domain control system according to claim 1, characterized in that, The global control execution module includes: The risk warning module is used to output corresponding warning information based on the risk assessment results output by the AI ​​intelligent analysis module, and send the warning information to the regulatory terminal through at least one of the following methods: sound and light, SMS, APP push or large screen display. The emergency response module is used to execute corresponding emergency response actions based on the risk level in the risk assessment results: When the risk level is low, a warning message is sent to the pilot. When the risk level is medium risk, the jamming equipment is activated and surrounding detection equipment is dispatched to enhance monitoring; When the risk level is high, intercept drones will be dispatched to intercept the illegal targets. When the risk level is extremely high, multiple departments will work together to handle the violations across the entire region.

10. The quantum encryption and AI-assisted low-altitude UAV full-domain control system according to claim 1, characterized in that, The global control execution module also includes: The unified scheduling module for all-domain detection equipment is used to issue control commands to each detection and sensing terminal. The control commands include at least one of the following: equipment start / stop, angle adjustment, power adjustment, network linkage, or mode switching.

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