In this paper a norm-constrained unscented Kalman filter that enforces a state norm-constraint is presented. This filter is an extension of the norm-constrained Kalman filter presented by Zanetti et al. The proposed norm-constrained Kalman Filter is used to estimate the pose of a High Area-to-Mass Ratio (HAMR) space-debris object. In much of the literature, the pose and other properties of space-debris objects are estimated assuming that the debris object being observed is a cuboid or some other convex multifaceted object. However, the literature also makes the case that a portion of the HAMR objects found near the Geosynchronous orbit (GEO) belt are fragments of multi-layered insulation (MLI) blankets that have separated from their parent satellites. These objects are slender and are appropriately modeled as thin plates. In this paper, simulated estimation results are presented demonstrating that the tumbling motion of these plate-like objects cannot be reasonably captured by light curve observations from a single observation site. However, by combining together measurements from multiple observation sites, estimation of these tumbling motions is possible. This observation further motivates the development of projects like DARPA's OrbitOutlook program to add more diverse locations for sensors and implement a central database to collect this data.
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