Faced with the threat of drone invasion, what is the current development status of anti-drone systems?
Where there are contradictions, there are shields. Drones are used all over the world. Naturally, there are anti-drone systems. The so-called anti-drone system refers to a system or device that can legally and safely disable, interfere with or control a drone or drone system.
After development in recent years, anti-UAV systems are mainly working in two directions: one is to detect UAVs; the other is to mitigate UAVs. Today, detection technologies are mainly based on acoustics, vision, passive radio frequency, radar and data fusion, while mitigation technologies include physical capture, interference, etc.
1. About UAV detection technology
There are five main types: acoustic, visual, passive radio frequency, radar and data fusion.
——Acoustic-based drone detection. This uses acoustic sensors to capture the sound of drones, identifying and tracking drones through audio. Current acoustic-based drone detection technology can accurately identify and locate drones to meet the accuracy requirements of drone detection.
——Radio frequency based passive detection. When a drone is working, there is usually at least one radio frequency (RF) communication data link connected to its remote controller to receive control commands or transmit aerial images. In view of the spectrum pattern of UAVs, artificial neural network (ANN) detection algorithms, data traffic patterns and other methods have emerged to identify UAVs.
——Vision-based drone detection. This technology mainly focuses on image processing. The images of the drone are captured through photography equipment, and then the relevant videos and pictures are calculated and compared through the ground station. The difference between the drone and the environment in the image is used to determine whether there is a drone in the restricted area. The current state-of-the-art image segmentation method uses neural networks to directly identify the appearance of drones.
——Radar-based drone detection. There are currently three main types of radar-based UAV detection technologies: active detection, passive detection and posterior signal processing. Typical representatives of active detection radar include noise radar, multi-mode radar based on SDR, etc.; passive detection radar is passive radar, which is mainly divided into single-station passive radar and distributed synthetic passive radar;
Posterior signal processing radar obtains the weak sparse reflection signal of the target from the noise output of the radio frequency front-end. It is mainly divided into traditional signal feature-based detection and learning-based pattern recognition.
——UAV detection based on data fusion. Data fusion methods can leverage the strengths of each method to obtain combined results that are more robust, accurate, and efficient than a single method. For drone detection, data fusion can be used to improve the performance of the drone detection system to overcome the shortcomings of a single method in certain specific scenarios.
2. About drone mitigation technology
Currently, foreign countries have developed the architecture of drone defense systems. According to the description of the architecture, it can be divided into three categories: the first is to use physical methods to capture the drone; the second is to use a noise generator to interfere with the system or sensor, making the drone controller unable to operate the drone; the second is to use a noise generator to interfere with the system or sensor, making the drone controller unable to operate the drone; Three are to exploit system or sensor vulnerabilities to gain control priority.
——Physical capture. Mainly relies on the network to capture and direct electromagnetic pulses. Network capture is a physical method of eliminating drones by using a gun or some specific weapon to trigger the network to capture the drone; electromagnetic pulse is mainly used to combat illegal electronic facilities in the vehicle, which may restart or Disable the operation of the control system.
——Use of noise. This is the most common method of suppressing drones entering restricted areas, by using noise signals to interfere with the operation of drone sensors or systems in order to neutralize them.
——Exploit vulnerabilities. Most exploit efforts focus on GPS control using sensors and communication protocols. Defenders use deception to locate GPS and sensors for control, using sensors and communication protocols for modification and intrusion control.
3. About the future trend of anti-UAV systems
Radar detection and data fusion methods are considered to be the most promising trends in future UAV detection; physical capture is considered to be The most practical and reliable way to deal with drones; hacking and deception will also be a very effective solution with a low footprint and low collateral damage. However, there are still many challenges that need to be solved in the future to develop mature, scalable, modular, and affordable UAV detection and negation methods.