Dynamic 3-D Threat Mapping Using a Sensor Constellation Deployed on Mobile Platforms

In this effort, Physical Sciences Inc. will develop and implement algorithms and hardware to perform the fusion of information obtained from multiple LWIR passive hyperspectral sensors to provide the capability to determine the extent, absolute geo-location, and 3-D concentration distribution of chemical threat clouds from mobile platforms. The effort will be conducted in conjunction with Professor Thomas Strohmer of UC Davis. At the end of a successful Phase II STTR program, PSI will demonstrate a TRL 5 capability based on an extensible architecture. The implementation of the capability is driven by current Nuclear, Biological and Chemical Reconnaissance Vehicle operational tactics and CONOPs. The capability will consist of hardware for sensor pointing and attitude information which will be made available for streaming and aggregation as part of the data fusion process for threat characterization. Threat information (mass estimates, COM location estimate, 3-D concentration) will be generated via multi-sensor (2 or more) data processing employing novel Sparse Tomographic Reconstruction (STR) algorithms which achieve > 30% increase in threat reconstruction fidelity over standard methods. The STR algorithms are robust to limited number of projections (i.e. provided by only 2 sensors) and unfavorable geometries resulting from on-the-move operation.