Optical measurements association using optimized boundary value initial orbit determination coupled with Markov clustering algorithm

Abstract : Identification of new circumterrestrial space objects is essential for building up and maintaining a catalogue of resident space objects (RSO). It is a recurrent task that we have to deal with in a day-to-day catalogue maintenance and that will become more intensive with the increasing awareness on space debris risks as more sensors get dedicated to the space surveillance effort. Robust algorithms are therefore needed in order to envisage automatic measurements associations that enable us to process large quantities of sensors data. This paper addresses this problem combining a method for optical tracklets association [1] with a clustering method [7] used in big data problems. Performance of this approach is assessed in real scenarios using measurements taken by a ground based robotic telescope located at Chile that belongs to the TAROT (Rapid Response Telescopes for Transient Objects) network.