Radar Data Fusion for Single Integrated Air Picture (SIAP)-Data Fusion and Registration System (DataFusR)

Timely fusion of data collected from a variety of radars that acquire information from multiple perspectives and/or different frequencies, may provide a more accurate picture of the adversary threat cloud than any single radar or group of radars operating independently. Algorithms, software, and/or hardware that enable this synergistic fusion and interpretation of data from disparate GMD radars should enhance system acquisition, tracking and discrimination of threat objects in a cluttered environment and provide enhanced battle space awareness. Fusion of data at several levels may be required. Technical issues that must be addressed include: spatial and temporal registration of radars, data throughput within and between sensor platforms, processing speed and capacity, and sensor calibration. This effort is to develop algorithms, software, and/or hardware necessary to collect, process, and fuse information from multiple radars (either at the same or different frequency) to form a single integrated air picture (SIAP). The research to be performed in this effort will be in direct support of the BMDS-MDA/GM (Ground Based Midcourse) acquisition program to provide effective DataFusR technologies which would enable sensor and battlespace systems to autonomously perform real time data registration and fusion of multispectral and multiresolution radar data for precision target geolocation and identification. The DataFusR approach will apply a multisource data fusion (MSDF) simulation methodology to assess the viability of candidate registration/fusion schemes and to select the best one(s) to achieve the objectives of forming an SIAP.