Multiple Hypothesis Correlation for Space Situational Awareness
Aubrey B. Poore, Joshua T. Horwood · 2011
Abstract : The primary objective of this program is to perform the necessary basic research to support the development of a statistical, multiple hypothesis tracker (MHT) for space surveillance. Such a MHT framework can serve as the next generation space surveillance system to maintain the space catalog, to identify uncorrelated tracks, and to support conjunction analysis and sensor resource management. Key components in such a system include a consistent characterization of uncertainty, physical modeling, multiple model filtering, and the association problem of determining which tracklets/measurements emanate from which object. To achieve a consistent characterization of uncertainty, Numerica has developed an adaptive Gaussian sum filter which correctly represents and propagates uncertainties and adaptively selects the correct the number of Gaussians in the mixture. Realtime online metrics support the coarsening and refining of the filter to maintain consistent uncertainty.