Super Resolved Harmonic Structure Function for Space Applications

Lockheed Martin IS&GS (Hawaii) has combined two novel signal processing algorithms in order to characterize non-resolved objects viewed by electro-optical sensors. The combined algorithm is termed the Super Resolved Harmonic Structure Function (SR-HSF). This paper introduces the SR-HSF algorithm and demonstrates its utility for creating "fingerprints" of space-based objects. The work presented here offers promise for enhancing the performance of several Missile Defense Agency sensor systems. An overview of the SR-HSF algorithm is initially presented. SR-HSF is shown to extract key space situational awareness (SSA) fingerprints from a minimal set of observations. Mathematical details of the SR-HSF algorithm are then described. SR-HSF has been shown to be both optimal and suited for real-time processing. This HSF method is extended to operate for cases where beating harmonic sets occur; i.e., the so-called Beat Structure Function (BSF). BSF processing results are then presented from both simulated data and unclassified data collected at AMOS from objects in space. These analytical results show that SR-HSF is capable of uniquely "tagging" an object with a minimal set of observations. The SR-HSF algorithm's capabilities provide important new considerations for sensor developers, SSA systems, and operators.