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The number of spacecraft in the vicinity of the Earth is growing rapidly every year as a result of ongoing innovations in the space industry. It takes a lot of computing effort to calculate the likelihood of a collision between two space objects in order to avert one. But there are a number of uncertainties in the collision prediction procedure, which makes managing space safety more difficult.Since the collision probability is usually applied to evaluate a dangerously close encounter, improving the precision of orbit prediction and covariance prediction is key.In a research paper recently published in Space: Science & Technology, Zhaokui Wang, from Tsinghua University, proposed an efficient method with a back propagation (BP) neural network to improve the accuracy of orbit prediction and position error covariance.

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