The earth's orbit is nowhere near as dangerous, but after more than half a century of space activity, collisions between jettisoned engines and disintegrated spacecraft have formed a planetary scrap heap that spacecraft need to evade.
Scientists have developed space junk identification systems, but it has proven tricky to pinpoint the swift, small specks of space litter.
But a unique set of algorithms for laser ranging telescopes has significantly improved the success rate of space debris detection, said a study published in the Journal of Laser Applications.
"After improving the pointing accuracy of the telescope through a neural network, space debris with a cross sectional area of 1 meter squared and a distance of 1,500 kilometres can be detected," said Tianming Ma from the Chinese Academy of Surveying and Mapping, Beijing and Liaoning Technical University, Fuxin, China.
Laser ranging technology uses laser reflection from objects to measure their distance. But the echo signal reflected from the surface of space debris is very weak, reducing the accuracy. Previous methods improved laser ranging pinpointing of debris but only to a 1-kilometre level.
The researchers involved in this study trained a neural network - algorithms modelled on the human brain's sensory inputs, processing and output levels - to recognise space debris using two correcting algorithms.
The team demonstrated the improved accuracy by testing against three traditional methods at the Beijing Fangshen laser range telescope station.
"Obtaining the precise orbit of space debris can provide effective help for the safe operation of spacecraft in orbit," Ma said.
( With inputs from IANS )