SBIR-STTR Award

Utilization of specialized COTS processors for high-throughput functions of hyperspectral detection processing will enable the next generation of small, lightweight UAVs to provide target detection and identification currently only available on larger and more expensive aircraft. Next generation UAV platforms will require sensor systems with smaller footprints and lighter weight than the current generation of Hyperspectral sensor systems. Space Computer Corporation (SCC) proposes to enhance the computational performance of key HSI algorithms by utilizing the capabilities of Graphics Processor Units (GPUs). This proposal describes an approach that couples the power of GPUs with simple PC-based processing architectures to significantly reduce the size of airborne, real-time processors. This use of GPUs, coupled with the recent development of small HSI instruments, will enable cost-effective use of small, inexpensive platforms to support target detection and identification applications previously reserved for large UAV or airborne platforms.

Keywords:
Hyperspectral, Real-Time, Detection, Identification, Processing, Atr

Under this Phase II SBIR program Space Computer Corporation (SCC) will enhance the computational performance of key HSI algorithms by utilizing the capabilities of modern commercial Graphics Processor Units (GPUs). This proposal describes an approach that couples the power of GPUs with PC-based processing architectures to significantly shrink the size and weight of airborne, real-time HSI processors and enable powerful new techniques to be implemented on-board the platform. This novel use of GPUs, combined with the recent development of small HSI instruments, will enable cost-effective use of small, inexpensive platforms to support spectral target detection and identification missions previously reserved for large UAV or airborne platforms. We project that Phase II development of a GPU-based HSI processing system will reduce the size of typical on-board processor units to less than 200 cubic inches, compared to the current systems which are about 1,700 cubic inches in volume. This near order-of-magnitude reduction in size and a corresponding weight reduction of nearly a factor of 5 will facilitate the transition of advanced HSI exploitation to the next-generation fleet of small UAVs, putting the power of HSI technology in the hands of more warfighters.

Keywords:
Hyperspectral, Detection, Identification, Gpu, Real-Time Embedded Processor