Ballistic Debris Coherent Discrimination and Modeling

Significant interest exists in developing radar algorithms to screen debris and small fragments from objects of interest in a ballistic missile defense threat complex. RCS statistics alone may not be sufficiently reliable to perform this screening function. A statistical model of radar debris fragments with realistic phase and amplitude variations suitable for large scale Monte-Carlo testing of discrimination algorithms and architectures is to be developed. We propose to estimate the size, spin rate, and relative velocity of debris fragments using Single-Range Doppler Interferometry. We also propose to draw upon and extend SSCI's Hypothesis Density (PHD) tracking and classification approach for the prescreening function. To support these investigations, a statistical debris model will be developed that simulates both phase and amplitude for debris fragments. A kinematic and RCS model previously developed by SSCI to support tracking and classification will be extended to incorporate coherent debris signatures. Phase II will demonstrate the effectiveness of the debris prescreener using available measured radar data, and demonstrate the fidelity of the coherent statistical debris model under broader radar operating conditions. Phase III will integrate the debris prescreening algorithms into BMD midcourse ballistic missile defense radars and demonstrate the total capability of the updated system.