DARPA Super Resolution Vision System (SRVS) robust turbulence data collection and analysis

摘要

Atmospheric turbulence degrades the range performance of military imaging systems, specifically those intended for long range, ground-to-ground target identification. The recent Defense Advanced Research Projects Agency (DARPA) Super Resolution Vision System (SRVS) program developed novel post-processing system components to mitigate turbulence effects on visible and infrared sensor systems. As part of the program, the US Army RDECOM CERDEC NVESD and the US Army Research Laboratory Computational & Information Sciences Directorate (CISD) collaborated on a field collection and atmospheric characterization of a two-handed weapon identification dataset through a diurnal cycle for a variety of ranges and sensor systems. The robust dataset is useful in developing new models and simulations of turbulence, as well for providing as a standard baseline for comparison of sensor systems in the presence of turbulence degradation and mitigation. In this paper, we describe the field collection and atmospheric characterization and present the robust dataset to the defense, sensing, and security community. In addition, we present an expanded model validation of turbulence degradation using the field collected video sequences.