Richard Dikeman (Lockheed Martin Hawaii), John Reagan (Lockheed Martin Space Systems Co.), Mr. Gerran Ueyama (Lockheed Martin Hawaii)
Keywords: NROC, Non-resolved Object Characterization
Abstract:
Lockheed Martin Hawaii presents the application of the combination of two novel signal processing algorithm for non-resolved object characterization. We introduce the Super Resolved Harmonic Structure Function (SR-HSF) and demonstrate its utility in providing “fingerprints” for space based objects. The work presented here is making a major impact in the Missile Defense Agency’s Project Hercules group but the results presented here are shown in an unclassified form. First, the SR-HSF algorithm is detailed. The SR-HSF is shown to pull out key space situational awareness fingerprints from a minimal set of observations. Next, the mathematical definition of the SR-HSF is detailed. SR-HSF is shown to be both optimal, and also applicable in the real-time sense. Then, applications to both simulations and unclassified data collected at AMOS of space based bodies are used for analysis. The SR-HSF is then used to analyze these fidelity simulations. It is shown that the SR-HSF is capable of “tagging” an object with a minimal set of observations – a previously impossible result. This analysis yield important considerations for sensor developers, SSA systems, and operators.
Date of Conference: September 12-15, 2007
Track: Non-resolved Object Characterization