Unmanned Systems
Maritime Search and Rescue (SAR)
Underwater search and rescue operations present
significant risks to the human element as well as to the underwater operating
platform. However, recent technological
improvements in unmanned underwater vehicles (UUVs)/autonomous underwater
vehicles (AUVs) are proving to be viable mitigations to the dull, dirty,
dangerous and deep (D4) risks associated with these operations. Underwater search and rescue operations, by
definition, assume that after a thorough search has been conducted to locate a
specific target that a rescue follows. Unfortunately, in deep water operations,
rescues are rarely realized and recovery operations become the norm. Recent headlines have highlighted these facts
and operating platforms with specific capabilities are chosen to conduct these
search and recovery operations.
This research paper presents an UUV/AUV that was deployed
to assist in locating the wreckage of Malaysia Flight MH370, which was presumed
to have disappeared in deep waters off the southern Indian Ocean (Varandani, 2018) .
A description of the UUV/AUV is provided as well as a
detailed description of the systems sensors and how they were designed
specifically for the maritime environment.
In conclusion, questions regarding system and operational
enhancements, and any advantages of UUV/AUV systems to those of manned
platforms are addressed.
Bluefin-21
AUV
The Bluefin-21 (Figure 1) built by General Dynamics, is
a self-contained autonomous vehicle equipped with a highly accurate sensory
payload capable of extended deep water operations, typically realized by larger
more cumbersome platforms (General Dynamics, 2018) .
Figure 1 Bluefin-21 Autonomous Underwater Vehicle (AUV) adapted from
http://d2fuv70sajz51d.cloudfront.net/publish/3495-b4EKktiE/Bluefin-21.png
With operating speeds between 2 – 4.5 knots, the
Bluefin-21 is capable of operating at depths of 1500 meters for approximately
20 hours at an average speed of approximately 3 knots (Chand, 2014) .
Its exteroceptive sensory payload
consists of side scan sonar, sub-bottom profiler, multi-beam echo- sounder and
digital camera (Chand, 2014) .
A suite of proprioceptive sensors provides
data essential to the onboard inertial navigation system and an ultra-short
baseline system supporting autonomous navigation and positioning of the vehicle
(Chand, 2014) .
Sensors
Like
other unmanned systems the Bluefin-21 is equipped with both proprioceptive and exteroceptive
sensors essential to supporting SAR operations.
Exteroceptive sensors collect/analyze data significant to the operating
domain of the unmanned vehicle. The
Side-Scan Sonar
The
EdgeTech 2200-M 120/410 kHz is an acoustic sensing technology that supports GPS
mapping applications at depths between 0.5 and 11,000 meters (Bloss, 2013) . These types of sensors are specifically
adapted for use in water applications where visibility and zero-low light
conditions limit typical camera capabilities.
Using sound the side scan sonar displays an image based on the strength
of the returning echo (NOAA, 2017) .
Sub-Bottom Profiler
Also
a sonar based sensor, the EdgeTech DW-216 sub-bottom profiler is used to define
and characterize layers of sediment, rock and other objects buried beneath the
seafloor. Using reflected and refracted
sound pulses this system uses low-frequency pulses in order to deeply penetrate
the sea floor but provides lower resolution pictures compared to that of high
frequency systems that provide better imagery but are limited in the depth of
scan (Substructure, n.d.) .
Multi-beam Echo Sounder
A
significant improvement over that of side-scan sonar, the Reson
7125 400 kHz multi-beam echo-sounder employs numerous sonar beams to provide
ultra-high resolution images of the seafloor (Substructure 2, n.d.) In their online article, Multibeam Sonar (n.d.), Substructure noted:
Multibeam SONAR offers
considerable advantages over conventional systems, including increased detail
of the seafloor (100 percent coverage), confidence that all features and
hazards are mapped without voids, the ability to map inaccessible areas (e.g.,
under jetties, structures, and vessels near breakwaters, in shoal areas, and
adjacent to retaining walls), fewer survey lines (which shortens survey time),
optimum seafloor detail for route and dredge programs, and the ability to
comply with the highest order International Hydrographic Organization (IHO) and
US Army Corps of Engineers (USACE) hydrographic standards.
Digital Camera
Configured
with a Prosilica GE1900 camera systems, the bluefin-21 is capable of capturing
high-resolution black and white images at up to three fps (Naval Technology, 2018) , the ensuing images
are used to provide a visual perspective of target data.
Navigation and Communication
As
previously noted, the Bluefin-21 is also equipped with a robust set of
proprioceptive sensors used to support navigation and communication. Positive stability and control is realized
using an inertial navigation systems (INS) which is further enhanced with a Doppler
velocity log (DVL), sound velocity sensors (SVS) and state of the art global
positioning system (GPS) (Naval Technology, 2018) . Communications with outside entities is
facilitated using an externally mounted antenna supported by GPS and communication
systems employing acoustic modems, Radio frequency (RF) serial links and Iridium
satellite modem and Ethernet direct (Naval Technology, 2018) .
Conclusion
Risks associated with
manned deep water operations are apparent, and mitigations to those risks are
realized using unmanned/autonomous underwater vehicles. Unfortunately, search and rescue operations
in extreme/deep operating domains inevitably become search and recovery
operations. The Bluefin-21 is especially
suited to meet the specific needs of these types of operations, on the other hand,
timely target acquisition and recovery in shallower waters would more likely be
accomplished using tethered remotely operated vehicles (ROVs) that enable
real-time situational awareness and supported by a robotic arm. Further ROV
discussions are saved for another time and assignment.
References
Bloss, R. (2013). Lasers, radar, acoustics and
magnetic sensors come to the aid of unmanned vehicles. Sensor review, 33(3),
197-201. Retrieved from https://search-proquest-com.ezproxy.libproxy.db.erau.edu/docview/1365745582/fulltextPDF?accountid=27203
Chand, N. (2014). Unmanned/Autonomous Underwater
Vehicles. Retrieved from SP's Naval Forces: http://www.spsnavalforces.com/story/?id=328
General Dynamics. (2018). Bluefin-21 Autonomous
Underwater Vehicle (AUV). Retrieved from Mission Systems: https://gdmissionsystems.com/products/underwater-vehicles/bluefin-21-autonomous-underwater-vehicle
Naval Technology. (2018). Bluefin-21 Autonomous
Underwater Vehicle (AUV). Retrieved from Naval Technology:
https://www.naval-technology.com/projects/bluefin-21-autonomous-underwater-vehicle-auv/
NOAA. (2017, July 06). Side Scan Sonar.
Retrieved from NOAA Ocean Service Education: https://oceanservice.noaa.gov/education/seafloor-mapping/how_sidescansonar.html
Substructure 2. (n.d.). Multibeam SONAR.
Retrieved from Substructure - Hydrographic Surveys. Diving. Marine Services: http://substructure.com/about/marine-services-information/hydrographic-surveys/what-is-sonar/multibeam-sonar/
Substructure. (n.d.). Sub-Bottom Profiling.
Retrieved from Substructure-Hydro Graphic Surveys. Diving. Marine SErvices.: http://substructure.com/about/marine-services-information/hydrographic-surveys/tools-used-to-examine-the-area-below-the-seafloor/
Varandani, S. (2018, June 05). MH370 Search Vessel
Still Scanning Area Of Suspected Black Box Pings: Report. Retrieved from
International Business Times: http://www.ibtimes.com/mh370-search-vessel-still-scanning-area-suspected-black-box-pings-report-2687462
