DSA Volume 1 Issue 4 December 2010 - Defence Science and ...

DEFENCE SCIENCE AUSTRALIA
to be depicted as PPI display screens.
These include a two-dimensional map
of bathymetry (seafloor depth), seafloor
sediment type, speed of sound at the
water surface, surface water temperature,
wave height and wind speed.
Each variable is viewable one at a time,
depicted in shades of black and white.
The modelled probability of detection
performance for the sonar system,
meanwhile, is depicted in hues ranging
from red to blue. This clearly delineates
the two kinds of information and allows
for easy reference between them.
“Any areas of the display coloured red
indicate sonar propagation conditions
under which there is a very high probability
that active sonar emissions will detect a
submarine target, while those in blue indicate
a very low probability,” explains Exelby.
This probability of detection information is
also displayed in graph form as functions
of depth and range, with the options of
viewing this for just the upper 300 metres
of water, or the entire water body.
A further graph presents a prediction of
bottom and total reverberation levels over
the range of sonar detection distances.
The demonstrator overall enables active
sonar returns arising from features such
as canyon walls, seamounts or slopes to
be more readily identified and discounted,
while extra vigilance can be given to
just those parts of the display where
targets of interest may be found.
The system on trial
The performance of the DSTO system was
put to test using data gathered in 2003
off the coast of Western Australia in water
depths extending to around 5,000 metres.
This information was collected with an active
towed array system deployed to detect a
human-generated sonar signal that simulated
return emissions from a submarine target.
During the data gathering exercise, the range
between the towed array and the echorepeater
target was slowly increased over
time, with the position of the simulated target
being logged at constant time intervals.
Meanwhile, XBT measurements of
in situ temperature profiles were taken
at various times during the exercise
and BLUElink hindcasts of sea surface
temperature were obtained later.
Post-event analysis was then conducted
to compare target detection performance
using three different inputs for the
prediction of sound speed in water; single
point measurements obtained via XBT, the
same form of data provided by BLUElink
estimates, and spatially varying data similarly
provided by BLUElink. For all three cases,
wind speed, bathymetry and sediment
type inputs were the same or similar.
The point of comparing single-point data
obtained by the XBT and BLUElink was to
evaluate how well BLUElink predictions
compared against measured in situ data.
The findings overall were that the use
of BLUElink inputs of temporally and
spatially varying kind gave significantly
improved assistance for target detection
over the other two approaches.
Further studies were undertaken
involving at-sea data more recently
gathered by a hull-mounted active
sonar system, with these findings
corroborating those of the earlier study.
The researchers conclude that the ideal form
of support for sonar operators is likely to be
delivered by use of XBT measurements for the
immediate locality of their vessel along with
forecast inputs from BLUElink for the area.
“By incorporating timely and relevant
environmental data into sonar operator aids,
we see this will lead to increased operator
confidence, environmental awareness,
system performance understanding,
and ultimately, better anti-submarine
warfare capability,” says Exelby.
Top left: DSTO’s concept demonstrator PPI display showing
probability of detection data overlying bathymetry.
Top right: BLUElink predictions for the DSTO trials area off Western Australia in 2003.
Above: PPI readings based on single-point ocean measurements obtained with XBT (left)
and readings for the same trial point based on BLUElink inputs (right).
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