Tracking and Bias Estimation in Near Rectilinear Halo Orbit using Multiple Model Adaptive Estimation

Multiple model adaptive estimation is a recursive estimation technique that enables real time estimation of system models with low levels of observability. This technique is applied to the estimation of a range bias that results from two-way coherent tracking of satellites using the Deep Space Network. Specifically, when tracking satellites in Near Rectilinear Halo Orbit, the geometry between the range measurement and orbital motion result in a condition of low observability. The proposed approach is demonstrated to accurately estimate the range bias, and track the satellite states under conditions of both a constant, and changing range bias.