For the first time, a satellite orbiting Earth was able to look ahead along its flight path, analyze imagery using artificial intelligence, and then redirect its instruments without any input from people on the ground.<\/p>\n AI helps satellites think fast<\/p>\n Dynamic Targeting has been in development for over ten years. The core idea is simple: make spacecraft act less like passive cameras and more like quick-thinking observers. <\/p>\n During a test in July, the system ran on a commercial satellite, with a clear goal \u2013 prove that spacecraft<\/a> can pick better targets on their own.<\/p>\n Instead of just snapping photos of whatever is below, Dynamic Targeting helps satellites avoid common issues like clouds and focus on what matters. <\/p>\n In the future, the system could even track fast-changing events like wildfires, volcanic eruptions, and intense storms.<\/p>\n \u201cThe idea is to make the spacecraft act more like a human: Instead of just seeing data, it\u2019s thinking about what the data shows and how to respond,\u201d said Steve Chien, principal investigator for the Dynamic Targeting project. <\/p>\n \u201cWhen a human sees a picture of trees burning, they understand it may indicate a forest fire<\/a>, not just a collection of red and orange pixels. We\u2019re trying to make the spacecraft have the ability to say, \u2018That\u2019s a fire,\u2019 and then focus its sensors on the fire.\u201d<\/p>\n Teaching satellites to skip the clouds<\/p>\n In its first real-world test, Dynamic Targeting wasn\u2019t looking for fires or storms just yet. Its mission was to dodge something far more ordinary: clouds<\/a>.<\/p>\n For Earth-observing satellites<\/a>, clouds are a major obstacle. They block the view up to two-thirds of the time. Most sensors simply collect whatever\u2019s in front of them \u2013 even if it\u2019s just cloud cover. That wastes valuable storage and processing time.<\/p>\n Dynamic Targeting changes that. The system allows the satellite to scan 300 miles ahead to check for clear skies. If it sees clouds, the shot is canceled. If the coast is clear, it captures the image as it passes overhead.<\/p>\n \u201cIf you can be smart about what you\u2019re taking pictures of, then you only image the ground and skip the clouds. That way, you\u2019re not storing, processing, and downloading all this imagery researchers really can\u2019t use,\u201d said Ben Smith, an associate with NASA\u2019s Earth Science Technology Office.<\/p>\n Smith noted that the technology will help scientists get a much higher proportion of usable data.<\/p>\n How it works in orbit<\/p>\n The latest test flew aboard CogniSAT-6, a compact CubeSat launched in March 2024. It\u2019s built and operated by Open Cosmos and carries a payload from Ubotica featuring an off-the-shelf AI processor. <\/p>\n The processor was tested earlier on the International Space Station, using similar algorithms.<\/p>\n Because CogniSAT-6 doesn\u2019t have a dedicated forward-facing imager, it tilts forward by 40 to 50 degrees to take a peek ahead. The satellite uses a camera that sees in both visible and near-infrared light.<\/p>\n The onboard AI then analyzes that imagery to find clouds. If the view looks clear, the spacecraft turns back to look straight down and captures the scene below.<\/p>\n The whole cycle \u2013 scan, analyze, aim, and shoot \u2013 happens while the satellite hurtles through space at 17,000 miles per hour. And it all wraps up in under 90 seconds.<\/p>\n Avoiding clouds and targeting trouble<\/p>\n With the cloud-avoidance test complete, the team is already looking at what\u2019s next. Upcoming trials will flip the goal: instead of dodging clouds, the satellite will target them \u2013 particularly severe storm<\/a> systems. <\/p>\n Other tests will focus on heat anomalies like volcanic eruptions or active wildfires. Each task will use its own set of tailored algorithms.<\/p>\n \u201cThis initial deployment of Dynamic Targeting is a hugely important step,\u201d Chien said. \u201cThe end goal is operational use on a science mission, making for a very agile instrument taking novel measurements.\u201d<\/p>\n Ultimately, the technology could be used beyond Earth. The team actually drew inspiration from past work with ESA\u2019s Rosetta orbiter, which proved it was possible to track gas plumes from a comet without waiting for human commands. That same thinking now informs the Dynamic Targeting system.<\/p>\n AI can catch what we usually miss<\/p>\n Back on Earth, the team is thinking about new applications. One possibility is using radar instead of optical sensors. <\/p>\n Radar-equipped satellites with Dynamic Targeting could lock onto short-lived weather events like deep convective ice storms \u2013 rare and dangerous winter storms that are hard to catch with current systems.<\/p>\n There\u2019s also a bigger vision: satellite teamwork. In one idea, a lead satellite would process images and spot interesting targets. Then it would alert a trailing satellite to zoom in for closer study. <\/p>\n Eventually, a whole fleet of autonomous satellites could work together, sharing data in real time.<\/p>\n Chien and the team at JPL are already preparing a test of that concept, called Federated Autonomous MEasurement, that is scheduled to begin later this year.<\/p>\n \u2014\u2013<\/p>\n Like what you read? Subscribe to our newsletter<\/a> for engaging articles, exclusive content, and the latest updates.\u00a0<\/p>\n Check us out on EarthSnap<\/a>, a free app brought to you by Eric Ralls<\/a> and Earth.com.<\/p>\n \u2014\u2013<\/p>\n","protected":false},"excerpt":{"rendered":"A new kind of onboard AI gives satellites the power to think for themselves \u2013 deciding in under…\n","protected":false},"author":2,"featured_media":40970,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[45],"tags":[182,181,507,74],"class_list":["post-40969","post","type-post","status-publish","format-standard","has-post-thumbnail","category-artificial-intelligence","tag-ai","tag-artificial-intelligence","tag-artificialintelligence","tag-technology"],"_links":{"self":[{"href":"https:\/\/www.newsbeep.com\/us\/wp-json\/wp\/v2\/posts\/40969","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.newsbeep.com\/us\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.newsbeep.com\/us\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/us\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/us\/wp-json\/wp\/v2\/comments?post=40969"}],"version-history":[{"count":0,"href":"https:\/\/www.newsbeep.com\/us\/wp-json\/wp\/v2\/posts\/40969\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/us\/wp-json\/wp\/v2\/media\/40970"}],"wp:attachment":[{"href":"https:\/\/www.newsbeep.com\/us\/wp-json\/wp\/v2\/media?parent=40969"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.newsbeep.com\/us\/wp-json\/wp\/v2\/categories?post=40969"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.newsbeep.com\/us\/wp-json\/wp\/v2\/tags?post=40969"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}
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