Chinese researchers have began to use advanced algorithms to detect space debris currently orbiting the earth, to try and provide safer routes for rocket launches and spacecraft maneuvers.
There has already been development of space junk identification systems, but it has proven tricky to pinpoint the small specks of space litter. A unique set of algorithms for laser ranging telescopes, described in the Journal of Laser Applications, has significantly improved the success rate of space debris detection.
To remedy this issue of inaccurate detection systems, a team of scientists created a set of algorithms for laser ranging telescopes that have significantly improved the rate of detection. Researchers say that after improving the pointing accuracy of the telescope by using a neural network, space debris with a cross-sectional area of 1 meter squared and a distance of 1,500 km can be detected. Previous algorithms allowed the detection of debris, but only to a 1km level.
The team of scientists trained a back propagation neural network to recognise space debris using two correcting algorithms. The Genetic Algorithm and Levenberg-Marquardt optimised the neural network’s thresholds for recognition of space debris, ensuring the network wasn’t too sensitive and could be trained on localised areas of space. The team demonstrated the improved accuracy by testing against three traditional methods at the Beijing Fangshen laser range telescope station.