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    Neural Networks Train Lasers to Spot Space Junk

    Article obtained from Photonics RSS Feed.

    A set of algorithms for laser ranging telescopes, developed by scientists from the Chinese Academy of Surveying and Mapping and the Liaoning Technical University, is improving the success rate of space debris detection in Earth’s orbit by significantly improving the pointing accuracy of the telescope.

    After more than half a century of space activity, collisions between jettisoned engines and disintegrated satellites have created a celestial scrapheap that can be difficult for spacecraft to evade. Scientists have developed space junk identification systems, but it has proven tricky to pinpoint the swift, small specks of space litter.

    Beijing Fangshan Satellite Laser Observatory. Courtesy of Beijing Fangshan Satellite Laser…

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    Dec, 31 2019 |

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