{"id":6221,"date":"2020-07-13T09:15:10","date_gmt":"2020-07-13T12:15:10","guid":{"rendered":"https:\/\/www.nachodelatorre.com.ar\/mosconi\/?p=6221"},"modified":"2020-07-13T09:15:10","modified_gmt":"2020-07-13T12:15:10","slug":"israel-desarrolla-un-sistema-para-neutralizar-a-los-operadores-de-drones","status":"publish","type":"post","link":"https:\/\/www.fie.undef.edu.ar\/ceptm\/?p=6221","title":{"rendered":"Israel desarrolla un sistema para neutralizar a los operadores de drones"},"content":{"rendered":"

Despu\u00e9s del ataque masivo con drones por parte de Ir\u00e1n en Marzo de 2019, investigadores Israel\u00edes de la Ben Gurion University<\/strong>, han desarrollado un sistema que a partir de la trayectoria realizada por los UAV en su ataque, se puede determinar con precisi\u00f3n la ubicaci\u00f3n exacta del operador \u00a0y\u00a0 neutralizarlo. Esto debilita la capacidad del oponente, ya que es m\u00e1s sencillo obtener nuevos drones que desarrollar operadores entrenados y eficientes.<\/p>\n

\n

TEL AVIV:\u00a0In March 2019, the Iranian Revolutionary Guards Corps (IRGC) held a drill codenamed \u201cTowards Jerusalem 1,\u201d near the strategic Strait of Hormuz.<\/p>\n

The IRGC flew about 50 \u201coffensive and combat\u201d drones in the Persian Gulf, including the Saegheh drone, supposedly based on the American RQ-170. According to sources here, the drone flew for about 1,000 kilometers between designated targets.<\/p>\n

Now Israeli scientists are developing a system they believe will let them accurately locate the operator of hostile drones and neutralize him.<\/p>\n

Researchers at Ben Gurion University in Beer Sheva in southern Israel, Gera Weiss and Eliyahu Mashhadi, are using a realistic simulation environment to collect the path of the drone when flown from launch point and monitor it its flight path. \u201cWe insert all the points along the flight path into a deep neural network that was trained to be able to predict the exact launch point and the location of the drone operator,\u201d Mashhadi said.<\/p>\n

Testing the model with the flight simulator, the team were able to locate and target the drone operator 78% of the time.<\/p>\n

Today, counter-drone systems<\/a> use radio frequency to locate the operators, while using electro-optical, radar and other sensors to track the drones. \u201cAll the approaches that we are aware of for locating operators, not just the drones, use RF sensors\u201d. Mashhadi explained that there are automatic and semi-automatic methods for locating the operators based on radio communications between the drone and its operator. \u201cThere are a number of problems with this approach. Firstly, such methods are usually tailored to a specific brand of drones,\u201d he said. \u201cFurthermore, the radio signal can only be recorded near the drone. Finally, there are ways for malicious drone designers to apply cryptography and electronic warfare techniques to make localization by analysis of radio signals very difficult.\u201d<\/p>\n

Mashhadi explained that their experiments show the reactions of the operator due to environmental and physical conditions , give away enough information to obtain substantial information about the location of the operator by analyzing the drone\u2019s path in the sky.<\/p>\n

\u201cTo allow for a controlled environment, we conducted all our experiments with a flight simulator that provides a realistic flight experience for the operator that includes sun gazes, obstructions, and other visual effects that produce the reactions of the operators that allow us to identify their location,\u201d he said.<\/p>\n

The research team used AirSim (Aerial Informatics and Robotics Simulation), an open-source, cross-platform simulator for drones, ground vehicles and other objects.<\/p>\n

\u201cThe neural network that we have designed was able to take advantage of these relations when we asked it to use only position or only rotation information,\u201d Mashhadi said.<\/p>\n

Israeli sources say a system able to find the operator in real time will become critical because, in most cases, the operator is flying more than one drone. There\u2019s other work underway, including an effort by Israel Aerospace Industries (IAI) and an Israeli start-up. They have signed a cooperation agreement for the integration of interception capabilities into IAI\u2019s advanced anti-drone system, Drone Guard. The intercepting drone can be launched day or night from a docking station that hosts several ready-to-use drones. Several intercepting drones can be launched simultaneously to address several targets or swarms.<\/p>\n

To date, IAI\u2019s ELTA Systems, which develops and manufactures Drone Guard anti-drone systems, has sold more than 100 units that detect, identify and disrupt the operation of malicious drones. ELTA\u2019s collaboration with Iron Drone is part of its strategy to collaborate with startups to leverage their innovative technologies for their existing systems to improve performance.<\/p>\n

The radar detects drones as they enter Israeli airspace and an intercepting drone is launched and steered to the target with the help of the radar. The system uses sensors and computer vision to home and lock on the target. The entire process is autonomous, requiring no human intervention. According to IAI the new joint venture allows customers to react in areas where other defense systems cannot because of environmental factors such as airports, populated areas, power plants, sensitive facilities, and other infrastructures.<\/p>\n

Fuente:<\/strong> https:\/\/breakingdefense.com<\/em><\/a><\/p>\n","protected":false},"excerpt":{"rendered":"

Despu\u00e9s del ataque masivo con drones por parte de Ir\u00e1n en Marzo de 2019, investigadores Israel\u00edes de la Ben Gurion University, han desarrollado un sistema… <\/p>\n","protected":false},"author":1,"featured_media":6222,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":[],"categories":[18,2],"tags":[],"_links":{"self":[{"href":"https:\/\/www.fie.undef.edu.ar\/ceptm\/index.php?rest_route=\/wp\/v2\/posts\/6221"}],"collection":[{"href":"https:\/\/www.fie.undef.edu.ar\/ceptm\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.fie.undef.edu.ar\/ceptm\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.fie.undef.edu.ar\/ceptm\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.fie.undef.edu.ar\/ceptm\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=6221"}],"version-history":[{"count":0,"href":"https:\/\/www.fie.undef.edu.ar\/ceptm\/index.php?rest_route=\/wp\/v2\/posts\/6221\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.fie.undef.edu.ar\/ceptm\/index.php?rest_route=\/wp\/v2\/media\/6222"}],"wp:attachment":[{"href":"https:\/\/www.fie.undef.edu.ar\/ceptm\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=6221"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.fie.undef.edu.ar\/ceptm\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=6221"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.fie.undef.edu.ar\/ceptm\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=6221"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}