Automatic Signature Collection for Tracking and Identification

Ground target tracking performance can be improved through the use of appropriately collected target signatures. In particular, associating reports and tracks is especially enhanced in dense target environments and move-stop-move scenarios. To supportassociation, the signatures need to be collected at a diverse set of geometries so that a report signature can be associated with a signature collected previously at a comparable geometry. The collection of appropriate signature data is possible with theuse of new agile multi-mode radars, such as RTIP. Such radars can collect position reports with MTI and short-dwell SAR modes and can collect signature information with HRR and SAR modes. Position information can generally be collected faster thansignatures. Since signature information collection generally requires substantial radar resources, sensor management algorithms need to be developed to assure efficient use of these resources. We propose to build on our existing sensor managementalgorithms and our detailed knowledge of signature-aided tracking to create new algorithms for efficiently collecting the desired signatures The algorithms will utilize limited lookahead and stochastic models of tracking performance to value candidatesensor schedules and select the best one. ALPHATECH envisions that enabling the automatic collection of signatures to support tracking would be of interest to a large customer base. In particular, ALPHATECH has participated in numerous programs involvingthe integration of signature-aided tracking (SAT) technology into the Navy's Hairy Buffalo platform. We foresee considerable future interest, on the part of ONR, in continuing to integrate SAT technology into the Hairy Buffalo as well as furtherdeveloping and integrating the capability to manage the collection of HRR profiles to support SAT.