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Science and Technology Development The new regulations of the National Civil Aviation Department's "250 gram or more drones need real-name registration" implementation is less than 20 days. In recent days, the "anti-drug anti-black fly" system was first disclosed to the public and the news caught the attention of the whole country. June 19 was informed that the R&D team of the system came from the University of Electronic Science and Technology of Chengdu. How is this system developed? How does it become the "buster" of the black flying drone? During this visit, Luo Junhai, the deputy professor of Electronic Science and Technology at the R&D team’s main person in charge, opened the mystery of the “anti-drone drone anti-black fly systemâ€.
"Black fly flocks" come? Intelligent identification of drone types and their manufacturers
Up to now, there are two common methods to deal with drone black fly, one is the airport and other places, the use of radar for a given range of monitoring, this method has a drawback is that it is susceptible to clutter, weather or haze influences. Another way is to control from the end of the drone. For example, if a cloud system is installed on a drone, the limited flight area can be set through the continuous update of the cloud system. The new rules require real-name system, to a certain extent, in order to regulate and control the use of the end.
Luo Junhai introduced that “the anti-UAV anti-black fly system†is controlled from airports and other places. Unlike radar monitoring, the system integrates radar, visible light, and infrared technologies to achieve coverage coverage. , Synchronously transfer any monitored information to the big data center of "multi-source heterogeneous data fusion decision-making" and recognize it intelligently through machine learning, which can quickly identify the size, type, and company of the "invader". "We continuously updated the samples of the drones and promoted them through intelligent learning. By the time of maturity, we can identify information from various outsiders by capturing information," said Luo Junhai.
How many cows? It is also possible to counter "unobedient" drones
In the interview, it was found that the function of the system is more than this. Through effective multi-dimensional detection mechanisms, UAV images, video, radar, sound, and time series data are merged to realize multi-modal intelligent fusion detection of multiple drones. The system is open to the current domestic and international mainstream methods of countermeasures for UAVs, including physical countermeasures for UAVs, such as network capture, hot weapon shot down, acoustic wave down, laser down; secondly, the use of electromagnetic counter technology for remote control chain Road interference and deception, and radio positioning and arresting of flying hands, counter-measured "unobedient" drones.
At present, the research results of this project are being applied for at the national level. According to reports, some domestic airports and research institutes have also conducted consultation and cooperation with Luo Junhai.
Regarding the original intention of researching and developing the project, Luo Junhai explained that the real name system for drones is mainly to supervise drone companies and consumers. However, to completely eliminate the risks of “black flying†to airports, the real name system is not enough. However, the fundamental solution still depends on active defense at the airport.
Luo Junhai said that he and the entire team of the University of Electronic Science and Technology are specializing in multi-sensor intelligent data fusion. Last year he began to realize that UAV's impact on the airport was too great. At present, there are more than 100 products claiming to have products in the country, but they are not mature. The products are in the stage of trial production and verification. They haven't given persuasive test results satisfactory to the users. The team carried out research and development of anti-UAV systems based on the previous research basis. Recently, this project only achieved a phased breakthrough. "From the research results to mature transformation still needs a stage, all the current progress is very smooth." Luo Junhai said.
Character business card
Luo Junhai: Ph.D. (later), Associate Professor, Master's Tutor, University of Electronic Science and Technology, Visiting Scholar, University of Tennessee, USA, IEEE, IEICE and ACM members, Senior Member of China Electronics Association, Sichuan Provincial Academic Leader Reserve candidate. He has hosted the National Natural Science Foundation of China, Sichuan Province Science and Technology Support Program II, Sichuan Provincial International Cooperation Project and Central University Fund. He won the second prize and third prize for scientific and technological progress in Sichuan province.
Cover news reporter Li Xiujiang