In recent years, the drone industry in my country has continued to develop rapidly, and the application of drones has penetrated into various fields of the national economy. From aerial photography, aerial surveying, line inspection, artificial rainfall, meteorological detection to coastal border patrol, security monitoring, emergency rescue, flight entertainment, emergency disaster reduction, police surveillance, etc., drones are everywhere. However, with the continuous expansion, popularization and generalization of drone applications, some serious safety hazards and management loopholes have been exposed. Frequent incidents of drone interference with aircraft, and even being used by criminals, have posed a very serious real threat to national security, public security and personal safety. There is an urgent need for a mature and complete drone regulation mechanism and management means to adapt to the safety management of drone flights in low-altitude airspace.
1. Implementation Background
The standardized management of drones is imperative. On July 1, 2019, the Ministry of Public Security’s Public Security Bureau and Counter-Terrorism Bureau jointly compiled and published the “Requirements for Public Security and Counter-Terrorism in the Petroleum and Petrochemical System Part 1: Oil and Gas Field Enterprises” (GA551.1-2019), “Requirements for Public Security and Counter-Terrorism in the Petroleum and Petrochemical System Part 2: Refining and Chemical Enterprises” (GA551.2-2019), and “Requirements for Public Security and Counter-Terrorism in the Petroleum and Petrochemical System Part 3: Refined Oil and Natural Gas Sales Enterprises” (GA551.3-2019) officially came into effect. In these standard requirements, it is clearly stated that key units of the petroleum and petrochemical industry should deploy anti-drone active defense systems, and the following three conditions must be met: the signal transmission power should be less than or equal to 10mW; the system should be able to work continuously for 24 hours without personnel on duty; the system should obtain a national recognized explosion-proof certificate. This sets a clear technical benchmark for drone regulation in critical infrastructures.
2. Integrated Drone Regulation and Control System Technology
The system takes the integrated management and control platform as the information processing core. Based on the target information fed back by spectrum detection equipment, after fusion optimization processing, it intelligently analyzes and displays targets arranged in descending order of threat level. The operator uses navigation spoofing equipment to achieve directional expulsion of the target according to the target and environment conditions. The overall architecture of the drone regulation system is designed to be modular and scalable.
2.1 Integrated Management and Control Platform
2.1.1 System Functions
The integrated management and control platform is a B/S structure system. It only requires a login account to view real-time information. The system can distinguish between friendly and hostile drones within the airspace, dividing the low-altitude defense task into two parts: management of legitimate drones and prevention and control of black-flying drones. Legitimate drones are relatively more reliable, stable, and controllable. Black-flying drones, due to their various uncertainties, can be dealt with and interfered with by linking front-end detection and spoofing equipment, minimizing the danger to the protected airspace. This dual-mode approach is a core concept of modern drone regulation.
2.1.2 System Design Architecture
The system adopts a front-end and back-end separated technology stack. The front end is responsible for displaying data, and the back end is responsible for processing and storing data. Front-end and back-end developers exchange data through interfaces. The front-end technology stack integrates Node.js, Vue.js, vuex, Webpack, WebSocket, and AMap (Gaode Map) as carriers. The back-end technology stack uses SpringBoot and Hibernate as carriers to effectively help system decoupling, lay a foundation for large-scale distributed architecture, and improve development efficiency.
The connection between front-end and back-end is realized by the back-end service providing a unified access entry for the front end (deploying a separate service) to provide HTTP services for front-end calls, thereby achieving front-end and back-end data transmission. The following table summarizes the key components:
| Layer | Technology | Purpose |
|---|---|---|
| Front-end Server | Node.js | Build a front-end web server |
| Front-end Framework | Vue.js + Vuex | Implement web page functions and state management |
| Module Bundler | Webpack | Package project for deployment simplicity and confidentiality |
| Real-time Communication | WebSocket | Achieve real-time communication for B/S mode |
| Map Service | AMap (Gaode) | Provide map interface carrier |
| Back-end Framework | SpringBoot | Simplify back-end development and provide RESTful APIs |
| ORM Framework | Hibernate | Object-relational mapping for database operations |
2.1.3 Management Modules
The platform includes several key modules for comprehensive drone regulation:
- User Management: Permission group management allows adding permission groups according to specified permissions, editing the corresponding permission group permissions (whether to have permission to use certain functions), managing users under the permission group, and deleting the permission group.
- Drone Management: Register drone information to accurately identify drone information when performing tasks. At the same time, manage cooperative drone manufacturers, which can be used to provide standardized classification for drone control in the future.
- No-Fly Zone Management: Manage special warning zones set for certain protection tasks, draw no-fly zone graphics in conjunction with the map, and operators can easily manage no-fly zones.
- Log Management: Record alarm records, login logs, operation logs, and interface logs generated during system operation. Logs record user operations and program exception stack records, providing a basis for data analysis.
2.1.4 System Security Management
Security is paramount in any drone regulation system. The following measures are implemented:
Database Security: Access control implements fine-grained autonomous access control, with access granularity at the library and table levels. Access auditing can audit database access behaviors, including database connection, login, logout, creation, deletion, and other operations, as well as table creation, selection, copy, import/export, etc., meeting backup and recovery requirements.
Data File Management: Access control implements fine-grained autonomous access control with access granularity at the file level. Access auditing can audit operations such as file creation, modification (including renaming), copy, deletion, import/export, printing, etc., with backup and recovery capabilities.
2.2 Drone Navigation Technology
Currently, drones commonly use GPS, BDS, and GLONASS navigation signals. Drone flight control frequencies often operate in the 900M, 1.4G, 2.4G bands. Taking a scenario where both flight control and image transmission signals work at 2.4GHz as an example: the flight control signal occupies a bandwidth of 2MHz with short duration, and the frequency point switches between channels; the image transmission signal occupies 10MHz, and the level value and frequency band are relatively stable over a period of time. The uplink flight control signal mostly uses Frequency Hopping Spread Spectrum (FHSS) + Direct Sequence Spread Spectrum (DSSS) technology, with high transmission stability and strong anti-interference ability. The downlink image transmission link uses MIMO multi-antenna technology and OFDM modulation; the downlink image transmission link monitors the interference status of each channel in real-time and dynamically selects the optimal channel for operation. Understanding these navigation technologies is crucial for developing effective countermeasures in drone regulation.
2.3 Drone Detection and Identification Technology
Commonly used drone detection technologies include visual reconnaissance, acoustic wave detection, image detection, electromagnetic frequency detection, and radar detection. From the perspective of detection capability, automation degree, and environmental adaptability, electromagnetic frequency detection and radar detection meet the requirements. We chose electromagnetic frequency detection technology. The following table compares the commonly used detection and identification technologies:
| Detection Technology | Detection Capability | Automation Degree | Environmental Adaptability | Conclusion |
|---|---|---|---|---|
| Visual Reconnaissance | Narrow field of view, short distance (within 150m) | Non-automated | Greatly affected by weather and light | Not acceptable |
| Acoustic Wave Detection | Large-angle stereo, distance less than 300m | Automated | All-weather, but severe noise interference | Not acceptable |
| Image Detection | Narrow field of view, requires coordinates, greatly affected by weather | Can be automated | Affected by darkness, rain, fog, snow | Not acceptable |
| Radar Detection | Large-angle stereo, distance over 2km, high power consumption and radiation | Automated | All-weather | Not acceptable |
| Electromagnetic Frequency Detection | Large-angle stereo, distance over 2km, but lacks capability for drones without control and image transmission signals | Automated | All-weather | Acceptable |
As the “nervous system” of drones, the radio remote control and telemetry equipment is continuously working after takeoff and continuously radiates radio signals. This can be used as an entry point for detection and disposal. The system uses radio signal detection methods to intercept the remote control signal of the target drone. Through comprehensive analysis and processing, it discovers and identifies the target, determines the azimuth of the target radiation source, and detects the drone.
The detection working principle is as follows: During flight, the drone needs to receive the remote control signal from the remote controller, and the remote control operator receives the downlink image transmission signal from the drone. All these wireless communication links occupy spectrum resources. The radio detection equipment can extract the signal characteristics of interest from them using signal detection technology, and then use spectrum feature identification technology to compare with the established spectrum feature database, thereby obtaining the drone model information.
The establishment of the drone signal feature database is performed by monitoring the 20M-6GHz band. If the spectrum of all signals in a certain frequency band is obtained, then through artificial observation of signal characteristics, drone signals can be easily distinguished. Then, a deep learning method is used to construct a deep network to extract signal features to achieve drone signal identification and establish a drone model signal feature database. This database is a critical asset for any drone regulation system.
2.4 Drone Countermeasure Technology
Currently, active drone defense technologies mainly include: physical attack, electromagnetic suppression, and navigation spoofing. Physical attack mainly uses net capture, laser, electromagnetic gun, etc. to dispose of drones, which is prone to secondary damage. Electromagnetic suppression products transmit high-power wireless voltage suppression signals to block the remote control and navigation links of drones, achieving the effect of forced landing or return. The following table compares commonly used countermeasure technologies:
| Method | Unattended Operation | All-Weather | Omnidirectional | Radiation | Environmental Impact | Cost |
|---|---|---|---|---|---|---|
| Net Capture | No | No | No | Low | None | High |
| Radar/Optoelectric | No | No | No | High | Large | High |
| Laser | No | No | No | High | Large | High |
| Microwave | No | No | No | High | Large | High |
| Radio Frequency Suppression | No | No | Yes | High | Large | High |
| Biological | No | No | No | Low | None | High |
| Navigation Spoofing | Yes | Yes | Yes | Low | Small | Low |
Drone navigation spoofing technology radiates low-power regenerative navigation satellite signals (power not greater than 10dBm) to intrude into the navigation system of “black-flying” drones, thereby achieving interception and control of drones that need to use the navigation system for flight control, making them unable to fly into the protected area and ensuring the low-altitude safety of the area. By regenerating satellite navigation deception signals of two frequencies, it performs deceptive jamming on the satellite navigation coordinate information received by drones using satellite navigation positioning, achieving no-fly zone projection or area denial functions. This technology is a key enabler of effective drone regulation.
The power constraint is particularly important. The emitted spoofing signal power must satisfy:
$$P_{tx} \leq 10 \, \text{mW}$$
This ensures compliance with national standards and minimizes interference with other electronic systems. The effective protection distance is typically greater than 500m, with a 360° effective defense angle adjustable to directional defense as needed.
3. Application of Integrated Drone Regulation Technology in Large-Scale Stations
Taking a purification plant as an example, the surrounding terrain is flat and open, approximately 1.6km long from east to west and 1.3km wide from north to south. Considering the topographical features of the plant area and the layout of the process device area, the area with a radius of 500m from the center of the core device area is designated as the key defense area, and other areas are designated as general defense areas.
The goal is to achieve detection and identification of drones within a 3km monitoring range and an absolute no-fly zone within a 500m range. Deploy one set of spectrum detection equipment and three sets of navigation spoofing equipment. The system equipment meets the requirements of an effective action distance greater than 500m, signal transmission power ≤10mW, effective defense angle of 360°, adjustable to directional defense as needed, and meets national requirements for explosion protection, lightning protection, radio equipment certification, etc., with certificates issued by relevant qualified units.
The system is interconnected to form an integrated solution. All data converges to the integrated management and control platform to realize monitoring of the entire defense area. Duty personnel can grasp the drone situation in the surrounding area in real-time. When a target drone appears, the integrated management and control platform automatically issues processing commands.
The working process is set as follows: The drone navigation spoofing system is on standby, the spectrum detection equipment is always on, performing spectrum detection, early warning, and statistics. After an alarm, the system immediately links to start the drone navigation spoofing system to perform navigation spoofing countermeasures against the drone.
- Normal Mode: Can implement navigation guidance interference on intruding drones.
- Patrol Mode: The detection equipment and spoofing equipment can be linked to achieve 360° omnidirectional real-time detection and identification of drones, delineate the detection area, and perform 360° omnidirectional real-time protection of drones, delineate the protection area. After a spectrum detection alarm, the navigation spoofing equipment is immediately linked to quickly expel the drone. The interference automatically stops after the end, without affecting the positioning inspection equipment of the personnel in the storage area and the navigation of surrounding vehicles.
- Direction Detection: Depending on the specific application, it can realize the direction finding function of the drone threat direction, record and display the effect of drone countermeasures. It can set strategic active defense, optimize the expulsion trajectory according to the drone intrusion direction, avoid important buildings and densely populated areas, and quickly expel the drone.
The following table summarizes the key deployment parameters:
| Parameter | Value |
|---|---|
| Detection Range | 3 km |
| Effective Protection Distance (No-Fly Zone) | ≥ 500 m |
| Signal Transmission Power | ≤ 10 mW |
| Defense Angle | 360° (omnidirectional), adjustable to directional |
| Number of Spectrum Detection Units | 1 |
| Number of Navigation Spoofing Units | 3 |
| Degree of Automation | Fully automated, unattended 24/7 |
| Compliance Standards | Explosion-proof, lightning protection, radio equipment certification |
In this practical setting, the drone regulation system operates with minimal human intervention, automatically detecting and neutralizing threats. The integration of spectrum detection and navigation spoofing ensures that only hostile drones are affected, while legitimate drones operating outside the protected zone remain unaffected. The low-power nature of the spoofing signal also ensures that the system does not interfere with other critical infrastructure electronics.
4. Conclusion
In summary, under the premise of meeting current national standards, it is very important to use an integrated management and control system for drone management in large-scale oil and gas stations, forming a complete drone intelligent control system. Adhering to the concept of “passive detection, unattended operation, zero interference”, a complete management system has been formed from hardware to software, deeply applying technologies such as spatial information, signal processing, network security, and artificial intelligence, enabling machines to “recognize and judge”, promoting the application of low-altitude security technology in the security field, effectively helping managers to effectively perform low-altitude defense guarantee tasks in the target airspace, and playing a positive role in ensuring the safe production of oil and gas fields and stabilizing the social environment. The future of drone regulation lies in such intelligent, integrated, and low-power systems that can be deployed widely across critical infrastructures.
The successful implementation of this integrated drone regulation system in large-scale stations demonstrates its viability as a cost-effective, reliable, and compliant solution. As drone technology continues to evolve, the regulatory framework and countermeasure technologies must keep pace. The approach described here—combining spectrum detection, navigation spoofing, and a centralized management platform—provides a robust blueprint for safeguarding sensitive areas against unauthorized drone intrusions.