Air-based anti-unmanned aerial vehicle system and non-cooperative unmanned aerial vehicle detection and countering method thereof

Abstract

The invention discloses an air-based anti-unmanned aerial vehicle system and a non-cooperative unmanned aerial vehicle detection and countering method thereof, and relates to the technical field of anti-unmanned aerial vehicle systems and methods. The system comprises an air-based flight platform which adopts a multi-rotor unmanned aerial vehicle structure and is used for rapidly taking off and landing in a limited space; the multi-mode detection and countering module is used for detecting a radio signal of a typical unmanned aerial vehicle, interfering communication of an illegal unmanned aerial vehicle and trapping the illegal unmanned aerial vehicle by sending a false navigation signal; the intelligent identification and tracking module is used for carrying out real-time analysis on the multi-modal detection data; the task planning and control module is used for automatically generating an optimal flight and countering strategy according to the detection information and a preset task; and the energy module is used for providing a working power supply for the air-based flight platform and other modules in the unmanned aerial vehicle system. The system can quickly respond in a complex urban environment, accurately detect and effectively counteract the non-cooperative unmanned aerial vehicle.

Description

Technical Field

[0001] The present invention relates to the technical field of anti-UAV methods, and in particular to an air-based anti-UAV system and a non-cooperative UAV detection and countermeasure method thereof. Background Art

[0002] The widespread adoption of drone technology has dramatically changed the landscape of modern air surveillance and defense. Existing anti-drone systems fall into two main categories: ground-based and vehicle-mounted. Ground-based systems are typically equipped with large radar and radio monitoring equipment, enabling continuous airspace monitoring. Vehicle-mounted systems offer a degree of mobility, allowing them to be deployed between locations to counter drone threats in diverse areas. The main drawbacks of both types are: 1) Ground-based systems have significant limitations in complex environments such as cities, particularly due to obstruction by buildings and electromagnetic interference, resulting in limited detection range and reduced accuracy. They struggle to cope with dynamically changing drone threats, especially in multi-target environments, prone to missed detections or misjudgments. 2) Vehicle-mounted systems are limited in range by ground conditions, making them difficult to deploy quickly in complex terrain. During movement, the stability of the detection equipment is compromised, resulting in reduced detection accuracy and identification capabilities. 3) Common drawbacks: Existing anti-drone systems still have room for improvement in detection accuracy, target identification, and countermeasure efficiency, making them unable to meet the urgent needs of urban low-altitude security and control. The countermeasure capability against non-cooperative drones is limited, especially in complex electromagnetic environments and multi-target scenarios, where the countermeasure success rate is not high. Summary of the Invention

[0003] The technical problem to be solved by the present invention is how to provide a system and method that can quickly respond, accurately detect and effectively counter non-cooperative drones in complex urban environments.

[0004] In order to solve the above technical problems, the technical solution adopted by the present invention is: an air-based anti-UAV system, comprising: an air-based flight platform, a non-cooperative UAV monitoring and countermeasure integrated module and an energy module;

[0005] Air-based flight platform: adopts a multi-rotor drone structure, which is used for rapid takeoff and landing in confined space;

[0006] The non-cooperative drone monitoring and countermeasure integrated module includes a multimodal detection and countermeasure module, an intelligent identification and tracking module, and a mission planning and control module. The multimodal detection and countermeasure module is used to detect the radio signals of typical drones, interfere with the communications of illegal drones, and lure illegal drones by sending false navigation signals. The intelligent identification and tracking module is used to perform real-time analysis of multimodal detection data. The mission planning and control module is used to automatically generate optimal flight and countermeasure strategies based on detection information and preset tasks.

[0007] Energy module: used to provide working power for the air-based flight platform and the non-cooperative UAV monitoring and countermeasure integrated module in the UAV system.

[0008] The present invention also discloses a non-cooperative UAV detection and countermeasure method, comprising the following steps:

[0009] S1, air-based flight platform startup and takeoff: The operator sets the air-based flight platform startup and takeoff parameters through the mission planning and control module. After self-test, the air-based flight platform takes off vertically to the preset altitude;

[0010] S2, radio spectrum monitoring: The high-frequency radio spectrum sensor in the multimodal detection and countermeasure module is activated to monitor and analyze radio signals within the set frequency band in real time;

[0011] S3, target detection and identification: The intelligent identification and tracking module uses deep learning algorithms combined with spectrum data to lock and mark non-cooperative drone targets and assess the threat level;

[0012] S4, Path Planning and Flight Control: The mission planning and control module plans the optimal flight path in real time based on the target location information and controls the airborne flight platform to quickly approach the target UAV;

[0013] S5, Tracking and Countermeasure Execution: The intelligent identification and tracking module continuously tracks the target drone, and the multimodal detection and countermeasure module selects and executes appropriate countermeasures based on the target characteristics;

[0014] S6, mission completion and data processing: After completing the countermeasure mission, the air-based flight platform returns along the preset route, organizes the flight, detection and countermeasure data, generates a mission report, and the operator optimizes the mission parameters based on the mission report.

[0015] The beneficial effects of adopting the above-mentioned technical solution include: the system's ability to respond quickly in complex urban environments, overcome ground obstacles, achieve full airspace coverage, and ensure effective operation in diverse terrain conditions. By combining multimodal detection technology with intelligent algorithms, the accuracy of identifying non-cooperative drone targets is significantly improved, effectively reducing misjudgments and missed detections, and ensuring reliable monitoring. The system is equipped with a variety of countermeasures and can flexibly select appropriate countermeasure strategies based on different non-cooperative drone types and scenarios, thereby improving countermeasure success and reducing potential impacts on the surrounding environment. The optimized air-based flight platform design and energy management system ensure the system has a long single-mission endurance. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0017] Figure 1 is a principle block diagram of the system according to an embodiment of the present invention;

[0018] Figure 2 2 is a schematic structural diagram of an air-based flight platform in a system according to an embodiment of the present invention;

[0019] Figure 3 is a principle block diagram of a task planning and control module in the system according to an embodiment of the present invention;

[0020] Figure 4 is a flow chart of the method according to an embodiment of the present invention;

[0021] Among them: 1. Air-based flight platform; 2. Non-cooperative UAV monitoring and countermeasure integrated module; 3. Energy module. DETAILED DESCRIPTION

[0022] The following is a clear and complete description of the technical solutions in the embodiments of the present invention, in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts are within the scope of protection of the present invention.

[0023] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0024] Overall, such as Figure 1 As shown, an embodiment of the present invention discloses an air-based anti-UAV system, which includes: an air-based flight platform 1, a non-cooperative UAV monitoring and countermeasure integrated module 2 and an energy module 3. The non-cooperative UAV monitoring and countermeasure integrated module includes: a multi-modal detection and countermeasure module, an intelligent identification and tracking module and a mission planning and control module.

[0025] Among them, air-based flight platform 1: The air-based flight platform adopts a multi-rotor UAV design with vertical take-off and landing capabilities. It can take off and land quickly in a limited space. The platform structure design is optimized to adapt to long-term flight missions. At the same time, it has good stability and anti-interference capabilities. Its structural diagram is as follows Figure 2 As shown;

[0026] The multimodal detection and countermeasure module detects typical drone radio signals, jams the communications of illegal drones, and decoys them by sending false navigation signals. It integrates a high-frequency radio spectrum sensor, a Ku-band two-dimensional phased array radar, and an optical infrared imaging system for all-round, multi-dimensional detection of non-cooperative drones. The high-frequency radio spectrum sensor covers the 0.4-6 GHz frequency band and can detect typical drone radio signals. The radio jammer covers the entire 0.4-6 GHz frequency band and can jam the communications of illegal drones. The navigation deception unit covers navigation bands such as GPS, BD, GLONASS, and GALILEO and can decoy drones by sending false navigation signals.

[0027] Intelligent Identification and Tracking Module: Based on deep learning algorithms, the Intelligent Identification and Tracking Module performs real-time analysis of multimodal detection data. The module includes: A Multi-Sensor Data Fusion Unit: This unit fuses spectral and optical data to improve target identification accuracy. A Target Recognition Unit: This unit leverages a trained deep learning model to quickly identify the characteristics of non-cooperative drones. A Tracking Unit: This unit updates the target's position in real time to ensure stable tracking.

[0028] The intelligent recognition and tracking module first uses a lightweight CNN module to extract intermediate layer features from the RF time-frequency map and optical image, respectively, and then fuses them in real time through attention weighting. The fused features are then fed into YOLOv8-nano for 30FPS target detection. The detection results are then connected to ByteTrack-M multi-target tracking, and the positions are updated through EKF, achieving real-time recognition and stable tracking with an end-to-end latency of 30ms.

[0029] Mission planning and control module: used to automatically generate the optimal flight and countermeasure strategies based on detection information and preset tasks; including mission planning unit: used to generate the optimal flight path and countermeasure strategies based on preset tasks and real-time detection information. Automatic control unit: used to control the flight attitude of the flight platform and the execution of the countermeasure module. Remote control unit: used to provide a manual intervention interface to ensure the flexibility and controllability of the system. Its principle block diagram is as follows Figure 3 shown.

[0030] Energy module 3: used to provide working power for the air-based flight platform and other modules in the UAV system.

[0031] For the purposes of this application, non-cooperative drones are defined as drones that do not carry standard cooperative transponder equipment (e.g., ADS-B, remote beacon), do not actively transmit identity, location, or intent information, and require passive detection methods (radar, optoelectronics, radio, acoustics, etc.) for detection and identification. Simply put, these drones are drones that have not been registered in a designated airspace.

[0032] Corresponding to the system, Figure 4 As shown, an embodiment of the present invention further discloses a non-cooperative UAV detection and countermeasure method, which uses the air-based counter-UAV system and includes the following steps:

[0033] S1, flight platform start-up and take-off:

[0034] The operator sets parameters such as the patrol area through the mission planning and control module. After the system self-checks, the air-based flight platform takes off vertically to the preset altitude.

[0035] S2, Radio spectrum monitoring:

[0036] The high-frequency radio spectrum sensor in the multimodal detection and countermeasure module is activated to monitor and analyze radio signals in the 0.4 to 6 GHz frequency band in real time.

[0037] During the analysis process, the entire 0.4GHz–6GHz radio signal is divided into several 25kHz segments and stepped. A 1024-point FFT is performed to obtain a time-frequency diagram. A lightweight CNN network is used to classify the signal type and estimate the direction in real time. An alarm is triggered when abnormal drone remote control or image transmission characteristics are detected.

[0038] S3, target detection and recognition:

[0039] The intelligent identification and tracking module uses deep learning algorithms combined with spectrum data to accurately lock and mark non-cooperative drone targets, while also assessing the threat level.

[0040] The method of combining spectrum data includes the following steps:

[0041] The front-end performs real-time scanning from 0.4GHz to 6GHz, generates I / Q streams, and then performs a 1024-point FFT to generate a time-frequency plot (waterfall plot). The back-end fuses the time-frequency plot with the optical frame at the same moment at the feature layer. Two lightweight CNN branches extract features, which are dynamically weighted using an attention weight α before being fed into the object detection network (YOLOv8-nano). This allows the drone to be locked onto based on spectral characteristics even when the optical system is obstructed.

[0042] In addition, the threat level of this application is flexibly divided according to whether the non-cooperative drone carries malicious payloads and its spatial location with respect to critical facilities.

[0043] S4, path planning and flight control:

[0044] The mission planning and control module plans the optimal flight path in real time based on the target location information and controls the flight platform to quickly approach the target UAV.

[0045] Real-time Path Planning: As the aircraft approaches the target drone, it continuously updates the target drone's position and motion status via the spectrum sensing system and phased array radar. Based on this real-time feedback, the flight control module dynamically adjusts the flight path to counteract potential maneuvers or trajectory changes by the target drone. This ensures the airborne platform maintains the optimal tracking position and posture, gradually reducing the distance to the target drone until it reaches the preset interference range.

[0046] S5, tracking and countermeasure execution:

[0047] The intelligent identification and tracking module continuously tracks the target drone, and the multi-means countermeasure module selects and executes appropriate countermeasures based on the target characteristics.

[0048] The radio jammer covers the entire 0.4GHz to 6GHz frequency band and can disrupt communications with illegal drones. The navigation deception unit covers GPS / BD / GLONASS / GALILEO frequency bands and can deceive drones by sending fake navigation signals.

[0049] S6, task completion and data processing:

[0050] After completing the countermeasure mission, the system returns along the preset route, organizes flight, detection and countermeasure data, and generates a mission report. The operator can then optimize the mission parameters.

[0051] The system and method integrate multimodal detection, intelligent identification and tracking, multi-means countermeasures, and mission planning and control functions, and achieve efficient monitoring and countermeasures of non-cooperative drones through an aerial platform. It can quickly respond, accurately detect, and effectively counter non-cooperative drones in complex urban environments.

Claims

1. An air-based anti-UAV system, characterized in that include: Air-based flight platform (1), non-cooperative UAV monitoring and countermeasure integrated module (2) and energy module (3); Air-based flight platform (1): uses a multi-rotor drone structure for rapid takeoff and landing in a confined space; The non-cooperative UAV monitoring and countermeasure integrated module (2) comprises a multi-modal detection and countermeasure module, an intelligent identification and tracking module, and a mission planning and control module. The multi-modal detection and countermeasure module is used to detect the radio signals of typical UAVs, interfere with the communication of illegal UAVs, and lure illegal UAVs by sending false navigation signals; the intelligent identification and tracking module is used to perform real-time analysis on the multi-modal detection data; and the mission planning and control module is used to automatically generate the optimal flight and countermeasure strategy based on the detection information and the preset mission. Energy module (3): used to provide working power for the air-based flight platform (1) and the non-cooperative UAV monitoring and countermeasure integrated module (2) in the UAV system.

2. The air-based anti-UAV system according to claim 1, characterized in that: The multimodal detection and countermeasure module includes: UAV detection unit: used to detect relevant signals of UAVs; Radio jamming unit: used to interfere with the communications of illegal drones; Navigation decoy unit: covers multiple navigation frequency bands and lures illegal drones by sending false navigation signals.

3. The air-based anti-UAV system according to claim 2, characterized in that: The drone detection unit includes a high-frequency radio spectrum sensor, a Ku-band two-dimensional phased array radar and an optical infrared imaging system, which is used for all-round and multi-dimensional detection of non-cooperative drones.

4. The air-based anti-UAV system according to claim 3, characterized in that: High-frequency radio spectrum sensor: covers the 0.4-6 GHz frequency band and is used to detect radio signals from typical drones; Radio jammer: covers the entire frequency band from 0.4 to 6 GHz and is used to jam the communications of illegal drones. Navigation decoy unit: covers GPS, BD, GLONASS and GALILEO navigation bands, and deceives drones by sending fake navigation signals.

5. The air-based anti-UAV system according to claim 1, characterized in that: The intelligent identification and tracking module includes: Multi-sensor data fusion unit: used to fuse the collected spectrum and optical data; Target recognition unit: used to quickly identify the characteristics of non-cooperative drones using deep learning models; Tracking unit: used to update the target position in real time.

6. The air-based anti-UAV system according to claim 1, characterized in that: The mission planning and control module includes: Mission planning unit: used to generate the optimal flight path and countermeasure strategy based on preset missions and real-time detection information; Automatic control unit: used to control the flight attitude of the air-based flight platform and the execution of the multi-modal detection and countermeasure module; Remote control unit: used to provide a manual intervention interface.

7. A non-cooperative drone detection and countermeasure method, characterized in that The steps include: S1, air-based flight platform startup and takeoff: The operator sets the air-based flight platform startup and takeoff parameters through the mission planning and control module. After self-test, the air-based flight platform takes off vertically to the preset altitude; S2, radio spectrum monitoring: The high-frequency radio spectrum sensor in the multimodal detection and countermeasure module is activated to monitor and analyze radio signals within the set frequency band in real time; S3, target detection and identification: The intelligent identification and tracking module uses deep learning algorithms combined with spectrum data to lock and mark non-cooperative drone targets and assess the threat level; S4, Path Planning and Flight Control: The mission planning and control module plans the optimal flight path in real time based on the target location information and controls the airborne flight platform to quickly approach the target UAV; S5, Tracking and Countermeasure Execution: The intelligent identification and tracking module continuously tracks the target drone, and the multimodal detection and countermeasure module selects and executes appropriate countermeasures based on the target characteristics; S6, mission completion and data processing: After completing the countermeasure mission, the air-based flight platform returns along the preset route, organizes the flight, detection and countermeasure data, generates a mission report, and the operator optimizes the mission parameters based on the mission report.

Images