Moriba Jah (Oceanit Laboratories, Inc.), Ronald A. Madler (Embry-Riddle Aeronautical University)
Keywords: NROC, Non-resolved Object Characterization
Abstract:
One of the challenges of satellite characterization is the ability to not only determine the spacecraft orbit but also the spacecraft orientation, size, and material properties. A substantial amount of research has been conducted in using photometry and spectroscopy to give insight into these spacecraft properties, but this work has been traditionally decoupled from the orbit determination process. Data fusion is an eventual goal in the spacecraft characterization community. The reality is that the spacecraft non-gravitational dynamics are influenced by the effects of solar radiation pressure, which are precisely a function of the heliocentric spacecraft position and orientation with associated material properties. By using data types that are sensitive to spacecraft position, attitude, and material properties, not only should orbit determination be possible, but this may constrain the estimates of spacecraft properties yielding more realistic results. Another benefit of the data fusion in the estimation process is that the correlations between spacecraft states and associated properties are captured within the covariance matrix. Hence, the uncertainties in these parameters are readily available. Errors in the spacecraft modeling are able to be mapped into spacecraft state errors and vice versa. This work describes the capability of satellite characterization achieved by fusing angles and light curve data in a sigma-point filter framework. Since this filter strategy is a current-state filter, this capability reflects what can be achieved in near-real time.
Date of Conference: September 12-15, 2007
Track: Non-resolved Object Characterization