Phan Dao, Air Force Research Laboratory, Dave Monet, United States Naval Observatory
Keywords: Photometric, astrometric, GEO, cross-tags
Abstract:
Data association in a congested area of the GEO belt with occasional visits by non-resident objects can be treated as a Multi-Target-Tracking (MTT) problem. For a stationary sensor surveilling the GEO belt, geosynchronous and near GEO objects are not completely motionless in the earth-fixed frame and can be observed as moving targets. In some clusters, metric or positional information is insufficiently accurate or up-to-date to associate the measurements. In the presence of measurements with uncertain origin, star tracks (residuals) and other sensor artifacts, heuristic techniques based on hard decision assignment do not perform adequately. In the MMT community, Bar-Shalom [2009 Bar-Shalom] was first in introducing the use of measurements to update the state of the target of interest in the tracking filter, e.g. Kalman filter. Following Bar-Shalom’s idea, we use the Probabilistic Data Association Filter (PDAF) but to make use of all information obtainable in the measurement of three-axis-stabilized GEO satellites, we combine photometric with metric measurements to update the filter. Therefore, our technique Concurrent Spatio- Temporal and Brightness (COSTB) has the stand-alone ability of associating a track with its identity –for resident objects. That is possible because the light curve of a stabilized GEO satellite changes minimally from night to night. We exercised COSTB on camera cadence data to associate measurements, correct mistags and detect non-residents in a simulated near real time cadence. Data on GEO clusters were used.
Date of Conference: September 19-22, 2017
Track: Poster