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The transducer embedded processing
theme was introduced to this DTC in recognition that
almost all sensors in operation today rely heavily on
signal processing methods to overcome limitations caused
by the environment of operation or the hardware used
to implement them. This theme concerns itself with embedded
processing, considered separate and distinct from general
signal processing methods or high-level data processing.
In other words it is processing needed at the transducer
in order to allow the maximum performance to be realised
from the sensor. Examples of embedded processing would
include electronic image stabilisation of an EO sensor
or the cancellation of jammers within a radar sensor.
It would not include data fusion of a number of sensors.
In order to provide a holistic view
of processing technology we have included both advancement
of processing itself and research into the tools needed
to exploit the advances in processing. This is in recognition
of the fact that there is an explosion in signal processing
options available to a sensor designer but many programmes
underestimate the time and costs associated with turning
algorithm ideas into low latency real-time processing
systems. As a result the full flexibility of emerging
technology is not fully exploited owing to the high
cost of development and proving of the resultant system.
Part of this programme will assess the possibility of
overcoming this limitation.
Another important factor which is
crucial to the effective use of processing within sensor
systems is to have a good understanding of processing
requirements and the likely availability of processing
capability. The well-known Moore's Law, expressing the
growth in available computing capacity, currently shows
no signs of reaching its limits, but it is less well
understood that whilst the growth in processing power
per unit volume continues unabated, the growth in processing
power per unit of power consumption is modest, indeed,
very modest. This fact has major implications for many
military sensor applications, as most military platforms
are severely constrained in availability of power and
cooling. This means that processing cannot be regarded
as an inexhaustible resource for future systems, and
this places a premium on developing processing algorithms
and software implementations which are highly efficient.
It is arguable indeed that the greatest barrier to progress
in the collection of data for military intelligence
is neither the inadequacy of sensor technology, nor
the shortage of processing power to crunch the numbers,
but, rather, the lack of understanding about what to
do with the data. Military intelligence is neither sensor-limited
nor processor power limited, but it is algorithm limited.
This is perhaps best illustrated by
the failure so far to capitalise on the richest, most
extensive source of free data that exists most of the
time in most places - the data that most informs human
and animal systems. Computer vision is the key to machine
intelligence. It is very difficult and remains an infant
technology, but there have been significant advances
in both 3D generic vision for structure analysis, and
scene interpretation in terms of 3D model-based processes,
which are promising real capabilities in autonomy. As
military thinking turns increasingly towards the use
of autonomous platforms, the development of computer
vision is becoming a matter of urgency.
Overall transducer embedded processing
sits on the interface between the analogue sensor input
and the digital output to the command and control system.
Clearly within the DTC the links to the EO and RF Systems
Research Themes will be vital in order to ensure that
the processing theme is tackling the real problems of
the sensor users and developers. By virtue of the close
working relationship within the DTC and the interests
of all the participants it is anticipated that the technical
direction of the work will continually be defined and
prioritised via a consensus of the key participants
within the DTC and Dstl.
In selecting the programmes for this
theme there has been careful consideration of the balance
between "quick win" year one projects and
longer term incremental projects, which aspire to make
a difference within what is recognised as a big topic
area. A major underlying theme of the first year work
is to baseline the current situation in order to allow
greater focus on priority issues in latter phases of
the DTC. The work has been grouped into a number of
sub-themes, which are summarised below, together with
the planned contributors to the research programme.
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