Evaluation of forward looking infrared (FLIR) as a coast guard SAR sensor

Hover, G. L.; Mazour, T J; Osmer, S R; Nash, L

doi:10.1109/oceans.1982.1151782

Cited by 1 publication

(1 citation statement)

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“…For the ADAC maritime security and tracking missions, visible with LWIR fusion can combine thermal imaging cues for situational awareness with visible images and S-AIS so that agencies such as the U.S. Coast Guard can verify reported positions in S-AIS (or failure to report) with partially visible vessels in fog or darkness with expected thermal signatures of the engine systems similar to security examples noted in related research [10]. The U.S. Coast Guard has used forward looking infrared [38], specifically finding LWIR to be of most use during the day to find targets in the water with less clutter (reflection of visible light from waves) [37]. Studies related to expand use of long-wave infrared and infrared by the U.S. Coast Guard have included surface oil spill tracking [39] and through ADAC new uses are being investigated such as use in coastal erosion mapping from UAV platforms and use in Arctic ports and straits for vessel monitoring and ice tracking.…”

Section: Primary Arctic Domain Awareness Missionmentioning

confidence: 90%

Software defined multi-spectral imaging for Arctic sensor networks

et al. 2016

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Availability of off-the-shelf infrared sensors combined with high definition visible cameras has made possible the construction of a Software Defined Multi-Spectral Imager (SDMSI) combining long-wave, near-infrared and visible imaging. The SDMSI requires a real-time embedded processor to fuse images and to create real-time depth maps for opportunistic uplink in sensor networks. Researchers at Embry Riddle Aeronautical University working with University of Alaska Anchorage at the Arctic Domain Awareness Center and the University of Colorado Boulder have built several versions of a low-cost drop-in-place SDMSI to test alternatives for power efficient image fusion. The SDMSI is intended for use in field applications including marine security, search and rescue operations and environmental surveys in the Arctic region. Based on Arctic marine sensor network mission goals, the team has designed the SDMSI to include features to rank images based on saliency and to provide on camera fusion and depth mapping. A major challenge has been the design of the camera computing system to operate within a 10 to 20 Watt power budget. This paper presents a power analysis of three options: 1) multi-core, 2) field programmable gate array with multi-core, and 3) graphics processing units with multi-core. For each test, power consumed for common fusion workloads has been measured at a range of frame rates and resolutions. Detailed analyses from our power efficiency comparison for workloads specific to stereo depth mapping and sensor fusion are summarized. Preliminary mission feasibility results from testing with off-the-shelf long-wave infrared and visible cameras in Alaska and Arizona are also summarized to demonstrate the value of the SDMSI for applications such as ice tracking, ocean color, soil moisture, animal and marine vessel detection and tracking. The goal is to select the most power efficient solution for the SDMSI for use on UAVs (Unoccupied Aerial Vehicles) and other drop-in-place installations in the Arctic. The prototype selected will be field tested in Alaska in the summer of 2016.

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