Real-Time Ortho-Mosaicing for Awareness and Navigation (ROMAN)

Given the availability of FMV-equipped UAS, the Navy wants to use those assets to capture up-to-the-minute imagery and generate broad area ortho-mosaic maps of the sea surface to aid in real-time situational awareness (SA), even in GPS denied areas. The Existing algorithms and software products can generate broad area ortho-mosaics, but they suffer from several limitations. First, the algorithms rely on landmarks and other fixed features that are usually not present in a maritime environment. The sea surface is relatively featureless and constantly changing, rendering any kind of landmark-based solution unusable. Second, the existing software requires considerable post-processing. By the time ortho-mosaics are available, they are based on data that is several hours old and no longer actionable. Third, In GPS denied environments, an aircraftÆs position is not reliable, so vision based approaches using visual odometry are necessary to help maintain accurate aircraft and sensor field of view position. Once a system generates a usable ortho-mosaic and updates it in real-time as new UAS imagery is received, it must also disseminate the data. Imagery, objects, threats, or other phenomena detected by the aerial survey must be communicable to other systems using standard data formats and protocols, such as Keyhole Markup Language (KML) or shape files. Charles River Analytics proposes to design and prototype Real-Time Ortho-Mosaicking for Awareness and Navigation (ROMAN) as a platform-agnostic system for real-time broad area sea surface ortho-mosaicking and object detection with visual odometry using EO and IR imagery from small UAS to improve maritime situational awareness (SA).