Improved Track Accuracy for Missile Engagements

In this project, Reservoir Labs continues to prototype and refine our Kinematic Invariant Space Maximum Entropy Tracker (KISMET) algorithm. KISMET takes an innovative approach to the problem of orbital track reconstruction and discrimination from radar data. In this Phase II effort, the approach is extended to handle fusion of data from multiple, geometrically diverse sensors, and to work with EO/IR sensors and Doppler radar measurements, in addition to range and angle measurements from radars. We extract key information related to ballistic missile break-up events by working in a state-space of orbital invariants only. The invariants account for the geopotential of the oblate earth to a high order of approximation. KISMET adopts a novel space-time viewpoint, where time is not measured by the counting of measurements, or by seconds on a clock, but by the accumulation of information. This line of thinking leads not to a conventional track filter, but to a set of static constrained optimization problems that we attack using new methods arising from research in the field of convex optimization. During Phase II of this program, we will continue to focus on developing and demonstrating our algorithms on measured data, as well as building an improved software prototype. Approved for Public Release | 19-MDA-9932 (21 Feb 19)