Context: The CEA DAM is a research center which exploits and analyses the infrasound data in view of the development of the International Monitoring System (IMS) being set up by the Comprehensive Test-Ban Treaty (CTBT).
So far, the PMCC (Progressive Multi-Channel Correlation) method, developed by the CEA, is used by the CTBT organization to analyze the infrasound signals recorded within the different stations of the IMS.
In the frequency bandwidth of interest, the real data analysis within the current operational system has shown the existence of several interfering (non-desired) signals which have to be taken into account. The measurement of the angle of arrival and propagation velocity of coherent infrasound sources is achieved via propagation delays estimation (between different sensors) and by using an appropriate time frequency grid. It is observed that such interference signals lead to erroneous detections and inaccurate estimations. Indeed the PMCC method has been essentially developed to detect and localize a single coherent source signal within a given time-frequency cell.
In order, to overcome this limitation, one needs to consider a kind of ‘source separation’ processing to get rid or mitigate the impact of the interfering signals.
Thesis objectives: The main objectives of this thesis would be to elaborate new detection and localization methods and validate and test them on both (controlled) real as well as simulated infrasound data. More precisely we will investigate the following items:
The use of high resolution methods like MUSIC (Multiple SIgnal Classification) to localize several narrow-band sources within the same time frequency cell.
Develop detection and localization methods for sources that are relatively wideband (i.e. may exist in several time frequency cells).
Develop new methods for the mitigation of spatially distributed (wide spread) interference sources.
Consider statistical criteria for the estimation of the number of sources via a penalized maximum likelihood approach.
Eventually, consider the use of learning methods for a better mitigation of certain ‘known’ ambient interference sources.
For the performance assessment and validation of the different methods under investigation, we will develop and enrich databases of controlled real-life data or synthetic data that would be representative of the genuine conditions and different scenarios for infrasound source detection. In particular, these data should well represent the diversity and variability of the infrasound signals and noise/interference sources as well as the different array configurations we might have in the current base stations.
The outcomes for the CEA/DASE, would be the improvement of the existing operational tools for the detection, localization and characterization of the infrasound sources of interest from noisy measurements and in the presence of interfering signals.
Thesis organization: The PhD student will join the CEA DAM center in Arpajon (Paris suburb, France) and will be registered at the University of Orléans (Doctorate school MIPTIS) under the supervision of Pr. Karim Abed-Meraim from PRISME laboratory. The thesis will involve the expertise of Maurice Charbit (Emeritus professor of Telecom ParisTech) and Dr. Alexis Le Pichon (CEA-DAM). Collaborations between CEA/DASE and its partner institutes will be most probably required to constitute the labelled databases necessary for the testing and validation tasks. In brief all required expertise will be used to achieve the outcomes of an improved operational detection/localization tool.
Pr. Karim Abed-Meraim (Université d’Orléans)
Pr. Maurice Charbit (Telecom ParisTech)
(c) GdR 720 ISIS - CNRS - 2011-2020.