A particle filter for orbit determination of space debris based on mono- and multi-static laser ranging

Orbit determination of space debris is typically complicated by rather imprecise and ill-distributed tracking data. Mono- and multi-static laser ranging are promising techniques to overcome such issues. To properly process their precise but sparse data we present a particle filter, which fully captures system nonlinearities and is capable of considering process noise characteristics. For statistical consistency our particle filter is provided with a probabilistic initialization obtained by Monte Carlo runs of initial orbit determination (IOD). We propose a method to obtain such IOD solutions based on data from several simultaneously observing stations. Eventually, we analyze the resulting state probability density functions with regard to the considered observation techniques and tracking scenarios.