researResearch - Télécom Bretagne

h Research
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RESEARCH
Main achievements of the project
Underwater seismic reflection
Radar activity
The project is carried out in accordance with
previous research methods, such as the lateral
continuity of reflectors in the case of submarine
seismic images and the use of texture attributes
for the identification of seismic properties. The
use of active contours has been introduced to
localize seismic salient features. Generalized
cumulative entropy properties have been studied
and its use as a new texture attribute as been
tested.
Classification
As far as classification is considered, a new
project concerns the development of weakly
supervised segmentation methods applied to
fishing. Two studies have been carried out: one is
devoted to the production of large scale
cartography including sonar images of a whole
region, as well as occasional samples obtained
from trawling. The second one concerns the
characterization of mixtures of fish species on the
sonar images.
Weakly supervised learning algorithms, using as
information the proportion of species (Bayesian
method, SVM and SVM +Kernel) have been
adapted to the case of images coming from a
halieutics depth sounder. To compensate for the
absence of « real-life field» data, we generated
synthetic data to test our algorithms. We
performed this task by making use of software
developed by IFREMER. Several methods were
tested to assess the abundance of species in a
given geographical location from the observation
of acoustic images at this location, with only the
prior knowledge resulting from trawling at
geographically neighbouring points.
Another project is intended to classify signals
issued from electric motors on vessels to improve
preventive maintenance. After a comparison of
several classification methods the SVM method
was selected to classify electric motors and the
classifier was optimised on the basis of provided
data.
A significant part of the activity has been devoted
to radar waveforms design. Global optimisation
methods, such as simulated annealing, have been
considered for designing pseudo-random binary
sequences with low level of sidelobes of the
ambiguity function. The results obtained show the
usefulness of these techniques whose
performance remains nevertheless limited given
the significant rejection requirements of these
lobes in many radar applications.
Spherical codes have been considered as a
technique for the generation of waveforms.
Standard pseudo-random sequences based on
Galois fields have also been considered. The study
and implementation of binary and polyphase
Golay sequences has been carried out: we have
shown that it is easy to extract Golay sequences
presenting highly efficient ambiguity functions.
We are currently investigating
FMCW like waveforms have been studied for low
cost car ACC (Automatic Cruise Control) radars
development. Matlab software, including radar
radiolink budget, RF transmitter/receiver
characteristics integration and targets detection
strategies has been developed. Comparisons with
ADS simulations have been conducted showing
the good behaviour of both platforms. This work
has been done together with the microwave
department of Télécom Bretagne. The study of
waveform properties in relation with their
parameter estimation variance performance has
also been studied. Given the over-optimistic
results provided by Cramer-Rao bounds,
Barankin bounds are considered as performance
indicators. These results have been used to justify
practical choice of detection threshold in ACC
radars.
A robust detector for the detection of small
objects in sea clutter has been proposed and we
have developed a radar image filter associating
wavelets and MAP filtering.
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