Data Association Algorithms for Tracking Satellites
Final rept. 1 Mar-30 Nov 2007
COLORADO UNIV AT BOULDER
Pagination or Media Count:
The problem addressed in this project is that of tracking a single satellite in the neighborhood of several other closely spaced, similar satellites where there is measurement mixing between satellites observed at a ground based sensor. This situation has been referred to as the furball problem. Tracking a single object or a group of objects in formation are both well studied and understood processes. What makes the furball problem unique is that the problem of tracking a single object in a formation is a generally undeveloped capability, especially with the type of sensor considered for this particular case. The ground based sensor considered takes a single measurement per sampling period. This single measurement can potentially be from any of the satellites in the sensors measurement region. This implies that the sensor returns a single stream of measurements that are mixed in the sense that the satellite from which the measurement originated is not known to the sensor. The purpose of this report is to formally address the furball problem and present several effective data association methods for finding a viable solution. As will be shown, these data association techniques can be used to effectively sort out measurements and provide reliable tracking.
- Spacecraft Trajectories and Reentry