What is the development status of anti-UAV system?

Facing the threat of UAV invasion, what is the development status of anti-UAV system?

Where there is a spear, there is a shield. Drones are used all over the world. Naturally, there are anti-UAV systems. The so-called anti-UAV system refers to the system or equipment that can legally and safely disable, interfere or control the UAV or UAV system.

After the development in recent years, the anti-UAV system mainly works in two directions: one is to detect UAVs; The second is to alleviate drones. The current detection technology is mainly based on acoustics, vision, passive radio frequency, radar and data fusion. Mitigation technologies include physical capture and interference.

First of all, about UAV detection technology.

There are five main types: acoustics, vision, passive radio frequency, radar and data fusion.

-Acoustic-based UAV detection. This is to use acoustic sensors to capture the sound of drones and identify and track drones through audio. At present, the UAV detection technology based on acoustics can accurately identify and locate the UAV, and meet the accuracy requirements of UAV detection.

-Passive detection based on radio frequency. When the UAV is working, usually at least one radio frequency (RF) communication data link is connected to its remote controller to receive control commands or transmit aerial images. Aiming at the spectrum pattern of UAV, artificial neural network (ANN) detection algorithm, data traffic pattern and other methods have appeared to identify UAV.

-Vision-based UAV detection. This technology mainly focuses on image processing. The image of UAV is captured by camera equipment, and then the related videos and pictures are calculated and compared by the ground station. Judging whether there is a drone in the restricted area by using the difference between the drone and the environment in the image. At present, the most advanced image segmentation method is to directly identify the appearance of UAV by using neural network.

-Radar-based UAV detection. At present, there are three kinds of UAV detection technologies based on radar: active detection, passive detection and posterior signal processing. Typical representatives of active detection radar include noise radar and multimode radar based on software radio. Passive detection radar is passive radar, which is mainly divided into single observer 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 RF front end, which is mainly divided into traditional signal feature-based detection and learning-based pattern recognition.

-UAV detection based on data fusion. Data fusion method can make use of the advantages of various methods to obtain more robust, accurate and efficient combined results than single method. For UAV detection, data fusion can be used to improve the performance of UAV detection system, so as to overcome the shortcomings of single method in some specific scenarios.

Second, about UAV disaster reduction technology

At present, the architecture of UAV defense system has been developed abroad. According to the description of the architecture, it can be divided into three categories: the first category is to capture drones by physical methods; The second is to use the noise generator to interfere with the system or sensor, so that the UAV controller can not operate the UAV; The third way is to gain control priority by exploiting system or sensor vulnerabilities.

-Physical capture. Mainly rely on the network to capture and orient electromagnetic pulse. Network capture is a physical method to eliminate drones, using guns or some specific weapons to trigger network capture of drones; Electromagnetic pulse is mainly used to attack illegal electronic facilities in the car, which may restart or invalidate the operation of the control system.

-Use noise. This is the most commonly used method to suppress drones from entering the restricted area. Noise signals are used to interfere with the work of UAV sensors or systems to counteract them.

-drilling loopholes. Most vulnerability exploitation work focuses on GPS control using sensors and communication protocols. Defenders use deception to locate GPS, use sensors to control GPS, and use sensors and communication protocols to modify and control intrusion.

Thirdly, the future trend of anti-UAV system.

Radar detection and data fusion methods are considered to be the most promising development trend of UAV detection in the future. Physical capture is considered to be the most practical and reliable method to deal with drones; Hacking and cheating will also become a very effective solution, occupying less space and causing less collateral damage. However, there are still many challenges to be solved in the future to develop mature, extensible, modular and reasonable-priced UAV detection and rejection methods.