Joshua Horwood, Numerica Corporation, Navraj Singh, Numerica Corporation, Jeffrey M. Aristoff, Numerica Corporation, Apoorva Bhopale, AFRL
Keywords: Space Situational Awareness, Conjunction Assessment, Collision Avoidance, Probability of Collision, Risk Assessment
Abstract:
KRATOS provides an innovative approach to computing the probability of collision (PC) between resident space objects that reduces misdetection and false alarms rates and supports the mission’s goal of performing conjunction assessment screening further out into the future. Although applicable to all regimes of space, KRATOS was designed to treat objects in the challenging non-linear and non-Gaussian regimes. KRATOS rivals the accuracy of Monte-Carlo methods but with little added computational cost relative to the traditional linearization (Foster) method. This paper provides an overview of the KRATOS algorithm and demonstrates its efficacy using real and simulated data. Scenarios are presented in which use of the Foster method would produce false alarms or misdetections, and hence would misinform the analyst. Use of KRATOS in these scenarios provides a reliable PC, as verified using Monte-Carlo simulation, and hence would better inform the analyst.
Date of Conference: September 20-23, 2016
Track: Astrodynamics