Successful SBIR projects by Goleta Star and UtopiaCompression Corporation
Two SBIR success stories have been posted to the Publications section of this web site (see the Innovation success story folder).
The Air Force seeks to develop and implement innovative processing techniques that hybridize synthetic aperture radar (SAR) and ground moving target indication (GMTI) modes to detect, identify, track, and locate moving targets. Goleta Star LLC, located in Torrance, California, made significant progress on the SAR moving target indication (MTI) algorithm development, applying its algorithms to three different types of SAR databases in order to demonstrate their utility across a variety of collection scenarios. With a staring SAR system, previous passes will be available and, thus, change detection products may be formed such as coherent change detection (CCD); incorporating information from previous passes into SAR MTI algorithms ensures that all available information is exploited for the detection and tracking of targets of interest. A fully developed capability for detecting, tracking, and displaying moving targets via an efficient, powerful, and readily implementable algorithm would be an invaluable component of a deployable staring SAR system, such as that being developed through the Air Force Gotcha Radar Program. The AFRL Sensors Directorate manages this SBIR project.
The Air Force SBIR requirement was to develop an electro-optical (EO) camera-based cloud detection and avoidance capability for Unmanned Aircraft Systems (UAS). This would enable UAS to remain in Visual Meteorological Conditions when operating in the National Airspace. UtopiaCompression Corporation (UC), located in Los Angeles, California, developed a unique technology for autonomous detection and avoidance of cloud formations for UAS using EO sensors only. The technology can detect clouds in passive imagery and reconstruct their three-dimensional shape and locations without requiring any UAS maneuver. The primary application of this technology is to enable UAS to autonomously detect and avoid clouds so that they can fly with due regard for the safety of other air traffic; secondary applications include detection and avoidance of man-made obstacles in low-flying urban environments and natural obstacles such as terrains and mountains. UC, in close collaboration with a major contractor, developed a framework known as Jointly Optimal Cloud and Collision Avoidance (JOCCA) that can autonomously avoid clouds and other air traffic simultaneously. This SBIR project is managed by the AFRL Air Vehicles Directorate.