27 research outputs found
Object Image Linking of Earth Orbiting Objects in the Presence of Cosmics
In survey series of unknown Earth orbiting objects, no a priori orbital
elements are available. In surveys of wide field telescopes possibly many
nonresolved object images are present on the single frames of the series.
Reliable methods have to be found to associate the object images stemming from
the same object with each other, so-called linking. The presence of cosmic ray
events, so-called Cosmics, complicates reliable linking of non-resolved images.
The tracklets of object images allow to extract exact positions for a first
orbit determination. A two step method is used and tested on observation frames
of space debris surveys of the ESA Space Debris Telescope, located on Tenerife,
Spain: In a first step a cosmic filter is applied in the single observation
frames. Four different filter approaches are compared and tested in
performance. In a second step, the detected object images are linked on
observation series based on the assumption of a linear accelerated movement of
the objects over the frame during the series, which is updated with every
object image, that could be successfully linked.Comment: Accepted for Publication; Advances in Space Research, 201
Heuristic and Optimized Sensor Tasking Observation Strategies with Exemplification for Geosynchronous Objects
With the new space fence technology, the catalog of known space objects is expected to increase to the order of 100,000 objects. Objects need to be initially detected, and sufficient observations need to be collected to allow for a first orbit determination. Furthermore, the objects have to be reobserved regularly, to keep them in the catalog, because the position uncertainty of the objects increases over time, due to unmodeled dynamic effects. Only a small number of ground-based and even fewer space-based sensors are currently available that are able to collect observations,
compared to the large number of objects that need to be observed. This makes efficient sensor tasking, which takes into account the realistic ramifications of the problem, crucial in building up and maintaining a precise and accurate catalog of space objects. The time-varying sensor performance and specific sensor constraints are influenced by the
sensor location and observational environmental effects, sensor hardware, processing software, and observation modes. This paper shows a new method of solving sensor tasking as an optimization problem translating the heuristic principles that have been successfully applied in sensor tasking of actual space situational awareness networks in a rigorous mathematical framework. A computationally fast near-optimal solution is presented, outperforming traditional heuristic sensor tasking methods. Applications of the methodology are shown via the example of the geosynchronous objects listed in the US Strategic Command two-line element catalog. The results are compared to state-of-the-art observation strategies