Urban Illumination for Soldier Simulations and Close-Combat Target Acquisition

JRM Technologies proposes to develop a high-performance physics-based algorithm for prediction of urban scene EO/NIR light levels, as seen from arbitrary vantage points. The algorithms will start with the complicated geometry of buildings, roads, etc., to perform a Monte-Carlo radiance calculation for the scene, yielding a global solution which can subsequently be sampled from arbitrary viewpoints with very little additional computation. These calculated scene radiances will then provide the basis for predicting target contrast signatures and expected systems performance. Atmospheric parameters will be extracted (automatically) from MODTRAN® calculations. The surface albedo model for scene elements will allow user selection from the JRM library of surface materials. We will develop a module to develop detection statistics based on multiple LOS calculations of target contrast signatures. These statistics will be based on a user-requested ensemble of sensor-target viewing geometries. Scene elements and our parameterization trade-offs for them will be evaluated using the MCScene Monte Carlo model. In addition we will obtain scene data from a DARPA program (or elsewhere) for a realistic validation case. Thus, the delivered model will be operational for the urban environment, have interfaces for TAWS, and be validated against realistic field data.