Waqar H. Zaidi, Applied Defense Solutions, Weston. R. Faber, Applied Defense Solutions, Islam. I. Hussein, Applied Defense Solutions, Michael Mercurio, Applied Defense Solutions, Christopher W. T. Roscoe, Applied Defense Solutions, Matthew P. Wilkins, Applied Defense Solutions
Keywords: Data association, catalog correlation, information theory, type 1 errors, type 2 errors, sequential probability ratio test
Abstract:
One of the most challenging problems in treating space debris is the characterization of the orbit of a newly detected and uncorrelated measurement. The admissible region is defined as the set of physically acceptable orbits (i.e. orbits with negative energies) consistent with one or more measurements of a Resident Space Object (RSO). Given additional constraints on the orbital semi-major axis, eccentricity, etc., the admissible region can be constrained, resulting in the constrained admissible region (CAR). Based on known statistics of the measurement process, one can replace hard constraints with a Probabilistic Admissible Region (PAR), a concept introduced in 2014 as a Monte Carlo uncertainty representation approach using topocentric spherical coordinates. Ultimately, a PAR can be used to initialize a sequential Bayesian estimator and to prioritize orbital propagations in a multiple hypothesis tracking framework such as Finite Set Statistics (FISST). To date, measurements used to build the PAR have been collected concurrently and by the same sensor. In this paper, we allow measurements to have different time stamps. We also allow for non-collocated sensor collections; optical data can be collected by one sensor at a given time and radar data collected by another sensor located elsewhere. We then revisit first principles to link asynchronous optical and radar measurements using both the conservation of specific orbital energy and specific orbital angular momentum. The result from the proposed algorithm is an implicit-Bayesian and non-Gaussian representation of orbital state uncertainty.
Date of Conference: September 19-22, 2017
Track: Poster