Assessment of Nighttime Airborne Visual ASW Capability

NPS NRP Project PosterHaving an unmanned aircraft to investigate possible surface and underwater contacts ahead of a transiting strike group is considered a valuable and urgently needed tool to complement other available sensors to identify a threat (in the case of Anti-Submarine Warfare (AFW)) and/or avoid collision. The hypothesis evaluated in this study is whether modern commercial off-the-shelf (COTS) small unmanned aerial system (sUAS) equipped with a miniaturized COTS low-light night-vision (LLNV) imagers could ultimately provide this capability. Ideally, this study would benefit from using a highly efficient electric vertical takeoff and landing fixed-wing COTS sUAS which can be launched even from a small ship deck, including those operated by Monterey Bay Aquarium Research Institute (MBARI). This sUAS features extremely low noise emission, can stay in the area for 90+ minutes, carry wide range of high precision sensors and cover large areas. It can transmit telemetry at up to 7 km C2 range, and can potentially provide encoded live video stream at 5mb/s (using an encrypted broadband mesh IP network). However, many constrains associated with cyber security, ship operations, airspace may prevent from employing sUAS in this study. The envisioned alternative platform to be used to evaluate feasibility of the overall concept is a general aviation aircraft equipped to collect low-light imagery. The research questions this study may address are as follows: 1. What are the limits of the current airborne LLNV sensors for nighttime detection of underwater objects? 2. Would the use of spectral, spatial and temporal filters would enhance target signature enough to create image database and use it for identification purposes? 3. What are the atmospheric / water condition contributing to emission of light from living organisms? 4. Whether it is feasible to integrate a COTS wavelength-optimized LLNV sensor with a COTS sUAS to provide a viable nighttime detection capability for shallow-swimming biologics and objects? The study will present the overall concept, discuss integration issues and issues associated with operating in the National airspace, specifically within the Monterey Bay area at nighttime; followed by assessing shallow-swimming whale imagery coming out of a typical COTS LLNV sensor. Based on the quality, quantity and variety of the collected samples, this study may include creating an image database and artificial-intelligence based qualifier to distinguish different objects (species) based on their bioluminescent signature. It is expected to collaborate with several external organizations; involve SE, OC and MR students; and summarize all the findings in the final report.Naval Surface and Mine Warfighting Development Center (SMWDC)U.S. Fleet Forces Command (USFF)This research is supported by funding from the Naval Postgraduate School, Naval Research Program (PE 0605853N/2098). https://nps.edu/nrpChief of Naval Operations (CNO)Approved for public release. Distribution is unlimited.

Excitation of zonal flow by the modulational instability in electron temperature gradient driven turbulence

The generation of large-scale zonal flows by small-scale electrostatic drift waves in electron temperature gradient(ETG) driven turbulence model is considered. The generation mechanism is based on the modulational instability of a finite amplitude monochromatic drift wave. The threshold and growth rate of the instability as well as the optimal spatial scale of zonal flow are obtained.Comment: 10 pages, 3 figure

Assessment of Nighttime Airborne Visual ASW Capability

NPS NRP Executive SummaryHaving an unmanned aircraft to investigate possible surface and underwater contacts ahead of a transiting strike group is considered a valuable and urgently needed tool to complement other available sensors to identify a threat (in the case of Anti-Submarine Warfare (AFW)) and/or avoid collision. The hypothesis evaluated in this study is whether modern commercial off-the-shelf (COTS) small unmanned aerial system (sUAS) equipped with a miniaturized COTS low-light night-vision (LLNV) imagers could ultimately provide this capability. Ideally, this study would benefit from using a highly efficient electric vertical takeoff and landing fixed-wing COTS sUAS which can be launched even from a small ship deck, including those operated by Monterey Bay Aquarium Research Institute (MBARI). This sUAS features extremely low noise emission, can stay in the area for 90+ minutes, carry wide range of high precision sensors and cover large areas. It can transmit telemetry at up to 7 km C2 range, and can potentially provide encoded live video stream at 5mb/s (using an encrypted broadband mesh IP network). However, many constrains associated with cyber security, ship operations, airspace may prevent from employing sUAS in this study. The envisioned alternative platform to be used to evaluate feasibility of the overall concept is a general aviation aircraft equipped to collect low-light imagery. The research questions this study may address are as follows: 1. What are the limits of the current airborne LLNV sensors for nighttime detection of underwater objects? 2. Would the use of spectral, spatial and temporal filters would enhance target signature enough to create image database and use it for identification purposes? 3. What are the atmospheric / water condition contributing to emission of light from living organisms? 4. Whether it is feasible to integrate a COTS wavelength-optimized LLNV sensor with a COTS sUAS to provide a viable nighttime detection capability for shallow-swimming biologics and objects? The study will present the overall concept, discuss integration issues and issues associated with operating in the National airspace, specifically within the Monterey Bay area at nighttime; followed by assessing shallow-swimming whale imagery coming out of a typical COTS LLNV sensor. Based on the quality, quantity and variety of the collected samples, this study may include creating an image database and artificial-intelligence based qualifier to distinguish different objects (species) based on their bioluminescent signature. It is expected to collaborate with several external organizations; involve SE, OC and MR students; and summarize all the findings in the final report.Naval Surface and Mine Warfighting Development Center (SMWDC)U.S. Fleet Forces Command (USFF)This research is supported by funding from the Naval Postgraduate School, Naval Research Program (PE 0605853N/2098). https://nps.edu/nrpChief of Naval Operations (CNO)Approved for public release. Distribution is unlimited.