BRDF Analysis of LADAR-based Target Surface Characterization

LADAR light reflection from a target is highly dependent of the spectral reflectivity and texture properties of the surface. Such dependencies could be exploited for target recognition based on surface characterization with appropriate imaging conditions and processing algorithms. Target surface light reflection is characterized by the Bidirectional Reflectance Distribution Function (BRDF), which is embedded in LADAR reflected returns. We propose to develop an extended LADAR capability for characterizing and classifying surface material and texture by exploiting multispectral polarimetric LADAR signatures based on the BRDF. The key innovation in this proposal is the comprehensive unified application of waveband spectra, polarization, tomographic reconstruction, and material science to LADAR-based remote target classification. The proposed system incorporating these advances is called LADAR-based Surface Analysis by Reflectance (LASAR). Key features of LASAR include BRDF modeling, a database of target and ground materials, range profile simulation, and material inversion algorithms. The results from Phase I will be used to define real-time algorithms for remote target recognition applications in Phase II.