La\u00a0Oficina Ejecutiva del Programa de Inteligencia, Guerra Electr\u00f3nica y Sensores del Ej\u00e9rcito, que administra sistemas que brindan vistas del campo de batalla, est\u00e1 buscando incorporar inteligencia artificial, automatizaci\u00f3n y aprendizaje autom\u00e1tico para permitir estas necesidades de toma de decisiones r\u00e1pidas. La Oficina del Programa de Sensores e Inteligencia A\u00e9rea (SAI) de la oficina trabaja con cuatro tipos de sensores ISR a\u00e9reos, dijo el Director del Proyecto SAI, Dennis Teefy, a GovCIO Media & Research.\u00a0Esto incluye sistemas de c\u00e1maras que usan im\u00e1genes en tiempo real de d\u00eda o de noche y en todas las condiciones clim\u00e1ticas, sensores de inteligencia de comunicaciones (COMINT) que interceptan frecuencias de radio, llamadas telef\u00f3nicas y mensajes de texto, sensores de inteligencia electr\u00f3nica (ELINT) que interceptan se\u00f1ales electr\u00f3nicas (incluidos radares) que no incluyen voz ni texto, y sensores de radar de inteligencia, que identifican objetivos estacionarios o en movimiento utilizando el reflejo de las ondas electr\u00f3nicas emitidas por el radar.<\/p>\n
Amid a Defense Department initiative to connect all components’ sensors into a single network via the\u00a0Joint All Domain Command and Control (JADC2)<\/a>\u00a0concept, the Army is taking a closer look at some of the data-sharing challenges that would hinder fast decision-making \u2014 one of JADC2’s core tenets.<\/p>\n DOD employs sensors everywhere \u2014 under the sea, on land, in the air. They can be present in thermographic cameras to sense infrared radiation. There are sensors that can detect projectiles from weapons, facial recognition sensors, sensors on communication devices, even underground sensors to detect mines.<\/p>\n DOD also uses aerial sensors to collect intelligence, surveillance and reconnaissance (ISR) data. But challenges with connecting sensor data could arise from latency, lag times, data quality and data prioritization and thus hinder fast decision-making.<\/p>\n The Army’s\u00a0Program Executive Office for Intelligence Electronic Warfare & Sensors,\u00a0which manages systems that provide views of the battlefield, is looking into incorporating artificial intelligence, automation and machine learning to enable these fast decision-making needs.<\/p>\n The office’s Sensors and Aerial Intelligence (SAI) Program Office works with four types of\u00a0aerial ISR sensors, SAI Project Director Dennis Teefy told GovCIO Media & Research. This includes camera systems that use real-time imagery day or night and in all-weather conditions, communication intelligence (COMINT) sensors that intercept radio frequencies, phone calls and text messages, electronic intelligence (ELINT) sensors that intercept electronic signals (including radar) that don\u2019t include speech or text, and intelligence radar sensors, which identify stationary or moving targets using the reflection of electronic waves emitted by the radar.<\/p>\n Some of these types of sensors are mounted on fixed-wing and unmanned aircraft systems.<\/p>\n Sensors, working as part of a larger network architecture, emit or gather data and collate it on a platform, which offloads or stores the data via satellite.<\/p>\n \u201cWhat that does is send all that data to an analyst,\u201d Teefy said. \u201cAfter that analyst looks at the data, they develop a report and share that information either with a strategic or tactical commander. The sensor is just the front end of an entire network architecture to get the data to the unit commander.\u201d<\/p>\n As technology modernizes, sensors gain the ability to gather more raw data, resulting in larger file sizes, which creates pain points when moving or delivering the data to analysts and then commanders, resulting in significant lag times.<\/p>\n \u201cAny time you move data, it’s a pain point,\u201d Teefy said. \u201cWhat we’re really working toward is how do we speed up and get that information to the commander is one of our main focuses in PDSAI, because it’s not just about the sensor, it’s about the entire system behind it.\u201d<\/p>\n Sometimes, sifting through sensor-collected data is like trying to find a needle in a haystack, so this is where AI and ML may help.<\/p>\n “We think AI and ML are going to be critical in increasing the effectiveness of the sensors,\u201d he said. \u201cSensor performance is always kind of limited by the laws of physics. As we improve the analysis gathered by the sensors, we think that’s an area to grow, explore and exploit.\u201d<\/p>\n During an ExecutiveBiz event on dual-use technology, Army Futures Command Director of the Assured Positioning, Navigation and Timing\/Space (APNT\/Space) William Nelson said all of DOD is still working on collecting, moving and analyzing data quickly to meet the speed of mission relevancy.<\/p>\n \u201cAutomated target recognition can be a huge time saver in the kill chain,\u201d Nelson said at the event. \u201cImage quality and timeliness matters. The app generation of the iPhone and Android has shown us that huge files can clog up the network. Data needs to be chipped and moved very quickly to the tactical edge. Images over a gigabyte are really tough on a network \u2026 we have a little more work to do in this area.\u201d<\/p>\n Maj. Gen. Aaron Prupas, director for defense intelligence warfighter support at the Air Force, said data prioritization can fundamentally transform workflow. AI and ML can help prioritize data collected by ISR sensors to reduce analysts\u2019 workloads and slash lag times.<\/p>\n \u201cOnly move the data you need to move, sometimes moving that downlink to the user is all you need,\u201d Prupas said during the event.<\/p>\n Joseph Rouge, deputy director of intelligence, surveillance and reconnaissance at the Space Force, echoed Teefy\u2019s comments about modernizing network architectures and sensors together, instead of focusing on sensors alone.<\/p>\n \u201cDon’t think a sensor will solve your problems, think of architectures of sensors and people as solving your problems,\u201d Rouge said during the event. \u201cIt’s architecture that has to be done. Different users and functions will have different architectural functions.\u201d<\/p>\n While a sensor\u2019s network architecture is critical for delivering high-quality, data-driven insights to decision-makers, modernizing sensors can go a long way. The SS-4000, which is an update to a 25-year-old guardrail system ELINT sensor mounted on aircraft, gathers more data more accurately via radar.<\/p>\n SAI delivered the SS-4000 to the Army in December 2020, and the Army deployed the sensor in April 2021.<\/p>\n \u201cThe increase in capability is above and beyond the existing ELINT (electronic intelligence) system on the guardrail, is a true gamechanger,\u201d Teefy told GovCIO Media & Research. \u201cWe’re able to both see farther as well as identify new signals that we were not able to on the existing ELINT system. When you can see further and see new signals of interest, that provides the commander on the field a better battlespace awareness than the sensor they had before.\u201d<\/p>\n The recently updated Common SIGINT Chassis-Army sensor (CSC-R) is SAI\u2019s first attempt to use an open systems architecture approach, in line with\u00a0DOD\u2019s wholesale shift<\/a>\u00a0toward open systems architecture. Updating the CSC-R to be compatible with opens systems architecture saves time and resources that otherwise may have been used to buy or build a new sensor.<\/p>\n \u201cWhat this does is allow us to integrate existing common capabilities on a common hardware form factor,\u201d Teefy said. \u201cWe’re able to take existing common systems and port them into this chassis \u2026 without having to go back and build a whole new sensor.\u201d<\/p>\n For Teefy and SAI, efforts to modernize sensors and their network architectures dovetail with JADC2 as well as\u00a0the Army\u2019s\u00a0digital transformation strategy<\/a>\u00a0and data interoperability and sharing across military service branches like the Air Force and Space Force.<\/p>\n \u201cWe are forward-thinking,\u201d Teefy said. \u201cSAI supports the Army’s ISR task force and the Army’s modernization goals. We are part of a coalition organization making sure the aerial ISR fleet is relevant against our near-peers and multi-domain operations front.\u201d<\/p>\n