Motivation:
The observation of the ocean surface using electromagnetic systems
(radars for instance) has always been a dynamic research area. The
stakes are very high for many applications: environmental monitoring,
military expertise, border control, seaborne trade... From a scientific
point of view, one of the main challenges is to understand the
interaction between electromagnetic waves and sea surfaces. This
difficult topic has already led to an abundant scientific literature for
several decades involving wave physics, signal processing and fluid
mechanics.
In the present project, the sea surface is supposed to be a
time-evolving random rough surface. Quite recently, different studies
showed that the dynamics of the electromagnetic wave scattered by such
rough surfaces can be described by stochastic differential equations.
More precisely, these new models are based upon nonlinear stochastic
differential systems. This new approach will probably be an
important source of innovation for maritime environment observation.
Expected Work:
The first purpose of the PhD thesis is to introduce the new stochastic
models into well-known signal processing algorithms dedicated to
maritime remote sensing systems (radar systems). The task will be to
highlight the performance enhancements obtained thanks to these new
models.
However, the actual aim is to develop new algorithms that take full
advantages of these stochastic models. Thus, the Phd student is expected
to develop innovative signal processing algorithms and new theoretical
contributions to improve the performances of the remote sensing systems.
Candidate profile:
Candidates should have great skills in applied mathematics, signal
processing theory, inverse problem and should be familiar with
stochastic calculus (Itô integral, Stratonovich integral, stochastic
differential equations...). A good knowledge in electromagnetics or
maritime environment would be appreciated.
Due to funding considerations, the candidate has to be French or from EU.
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