Ricerc@Sapienza

In the last years, the increasing number of space debris has triggered the need of a distributed monitoring system for the prevention of possible space collisions. Space surveillance based on ground telescope allows the monitoring of the traffic of the Resident Space Objects (RSOs) in the Earth orbit. This space debris surveillance has several applications such as orbit prediction and conjunction assessment. In this paper is proposed an optimized and performance-oriented pipeline for sources extraction intended to the automatic detection of space debris in optical data.

The increasing number of small satellite cluster launches leads to a greater risk of confusion and collision soon after their deployment in orbit. In particular, the possibility to identify each CubeSat and to monitor their trajectories with passive optical methods could allow mitigating the possibilities of impacts among them. Thus, several researches in this field are currently on-going to improve the capabilities in space surveillance for satellite early identification.

The tracking of LEO objects, by means of large field of view (FOV) optical telescopes, is very challenging. Generally, optical tracking is only possible when the LEO satellite is in sunlight and the ground station is in darkness. This limits the tracking availability to morning and evening twilight for maximum five minutes at a pass. At worldwide level, several activities and studies are currently under development in order to improve the space surveillance capabilities.

The optical orbit determination is one of the most important ways for noncooperative object tracking. One of the main problems with noncooperative object tracking is its recognition through different nights. In this study, the conditions that ensure the recognition of a geostationary satellite inside a cluster were assessed through a hard real case study. This study was developed through a three-phase approach. The first phase was the observation campaign for the images acquisition.

The growing quantity of debris in Earth orbit poses a danger to users of the orbital environment, such as spacecraft. It also increases the risk that humans or manmade structures could be impacted when objects reenter Earth's atmosphere. During the design of a spacecraft, a requirement may be specified for the surviv-ability of the spacecraft against Meteoroid / Orbital Debris (M/OD) impacts throughout the mission; further-more, the structure of a spacecraft is designed to insure its integrity during the launch and, if it is reusable, during descent, re-entry and landing.

The paper describes a method based on virtual reality tools to achieve the attitude determination of an orbiting object using lightcurve measurements. A virtual model of the orbiting object is propagated in order to reproduce its lightcurve. The differences between the real and simulated lightcurves is used as the cost function to be minimized through a multiobjective genetic algorithm. Lightcurve measurements in different spectral bands, both with monostatic and multistatic optical observations can be used.