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Intelligence, Surveillance and Reconnaissance

SDL develops state-of-the-art technologies for data acquisition, transmission and visualization applications. Specific areas of expertise include data compression, high-speed fiber-optic data transmission, and real-time data processing and display. These technologies are applicable in such wide-ranging areas as forestry, agriculture, and military intelligence.

  • SDL’s Advanced Reconnaissance Compression Hardware (ARCH) suite is used with a tactical imagery downlink to provide real-time transmission of digital image data from reconnaissance sensor platforms. This compression/decompression hardware suite is currently deployed in the US Navy’s Shared Reconnaissance Pod (SHARP) program.
  • SDL has developed cutting-edge Synchronous Optical Network (SONET) technology, which has emerged as a leading standard for connecting fiber-optic systems. SDL’s flexible designs, with high data rates and small footprints, offer a significant advancement in building large-scale, high-speed fiber-optic data transport systems.
  • SDL continues to lead the way in the development of real-time systems for processing, displaying and manipulating tactical reconnaissance imagery.
    • SDL’s display stations can be customized to support data from multiple sensor formats, including single- and multi-band electro-optical/infrared (EO/IR), synthetic aperture radar (SAR), hyperspectral (HSI) and UAV-based platforms.
    • The stations can be configured as rack-mounted stationary systems, portable systems in ruggedized transit cases, or desktop systems for distributed screening.
    • All systems include tailored image screening software that displays multi-INT image and targeting data in real-time, provides situational awareness, and includes a variety of data visualization, fusion, exploitation, and dissemination tools.
    • Current expansion efforts include support for open system net centric architecture, where a sensor on an aircraft appears as an IP address from distributed screening stations.