2020英语教学资源：时文阅读|中国科学家精确识别太空碎片

Chinese scientists     have used lasers（激光） to accurately     identify space debris（碎片）in the Earth’s     orbit.

The team applied a specially     developed set of rules to laser-ranging telescopes, which enabled them to     identify space junk more effectively than previous techniques. “After improving the pointing accuracy of the     telescope through a neural network（神经网络）,     space debris with a cross sectional area of one square meter at a distance     of 1500 kilometers can be detected,” Tianming Ma, an author of the study     from the Chinese Academy of Surveying and Mapping, said in a statement.

According to NASA,     orbital debris is any man-made object in orbit around the Earth that no     longer serves a useful function. Debris can include non-functional     spacecraft, abandoned launch vehicle stages, and other mission-related     space junk. It poses a significant risk to astronauts and spacecraft in     orbit above the Earth as it travels very fast — up to 18,000 miles per     hour, which is faster than a bullet. Worryingly, there are estimated to be     many millions of tiny debris pieces in low-Earth orbit, and tens of     thousands times larger than a softball, the space agency said. Fortunately,     there have been surprisingly few collisions.

In the study, Ma and     his team used two different neural networks to help identify space debris     with the laser-ranging telescope. They then tested this method against more     traditional techniques. According to the team, this is the first time that     neural networks have been used to significantly improve the pointing     accuracy of a laser-ranging telescope. They say the latest findings could     have significant implications for manoeuvring spacecraft in orbit.

Laser-ranging     technology has previously been used to detect space junk. However, these     systems have limitations when it comes to accurately identifying small,     fast-moving pieces. In fact, previous laser-ranging methods have only been     accurate to about 0.6 miles. In an attempt to overcome the inaccuracies of     laser-ranging techniques, the Chinese team used so-called neural networks     to improve the effectiveness of their telescope system. Neural networks are     computing systems which are inspired by biological networks in the brain     and have the ability to learn to become better at tasks without being given     a specific set of rules to follow.