289 Drone-based SAR capabilities: study cases related to the BIOMASS mission

Job title:

289 Drone-based SAR capabilities: study cases related to the BIOMASS mission

Company:

Centre National d’Etudes Spatiales

Job description

25-289 Drone-based SAR capabilities: study cases related to the BIOMASS missionPostuler25-289 Drone-based SAR capabilities: study cases related to the BIOMASS mission

• Doctorat, 36 mois
• Temps plein
• Indifférent
• Maitrise, IEP, IUP, Bac+4
• Continental biosphere

PostulerMissionDevelopment and use of low-frequency (VHF/UHF) imaging radars has increased in recent years, driven by the presence of flagship scientific programs at European level, such as the BIOMASS mission aiming to map forest height and above ground biomass globally (to be launched in the early 2024), or by various civilian and military applications requiring to solve FOPEN (Foliage Penetration) issues. In this context, the high manoeuvrability and cost effectiveness of drone based SAR generate an increasing interest. Indeed, potential uses in the frame of BIOMASS mission could be related to the consolidation of calibration/validation activities, especially through the spatialization of in situ or LiDAR measurements, and more generally to bring support for the characterization of dense forest cover and the underlying surface, whether for trafficability studies in case of disasters or the detection of hidden activities or buried structures related to military operations.Although promising, low-frequency SAR remains an emerging technology onboard low cost drones, given antenna size, power consumption and flying performances required for SAR imaging and repeat-pass interferometric and tomographic measurements. Since the end of 2019, the TSRE unit of DEMR (ONERA) has been developing a program of miniaturized sensors intended for radar acquisition from a light drone (SAR-Light program). After previous developments in X-band and then C-band, the addition of a low-frequency component is underway (600MHz- 200MHz) and will allow investigations in these low frequency ranges. Together with this technological advances, ONERA and CESBIO/ISAE teams have a strong expertise in radar data processing and analysis, and have been part on key airborne (TropiSAR, AfriSAR) or tower-based (TropiScat 1&2, AfriScat) experiments conducted in the preparation phases of BIOMASS.Based on this working environment, the PhD student will participate to the design of new experiments, together with the development of ad-hoc processing methods, data analysis and reporting related to the above-mentioned topics and especially the capabilities of drone based SAR to characterize forest structure and the underlying surface.More specifically, the PhD work shall focus on the following parallel tasks:Design of new experiments:Specific experiments will be achieved according to several objectives, starting from proof of concept demonstration, validation campaigns and data acquisitions for the above-mentioned applications. Among the targeted test sites, Paracou (French Guiana) where the TropiScat-2 tower-based experiment is operating will be of major importance, giving the possibilities on the one hand to validate and cross-compare tower- and drone-based systems, and on the second hand to spatialize some of the results which have been of highest importance for the BIOMASS mission, in spite of their intrinsic limitations to a specific area. Following the control phase focused on the closest configuration to TropiScat-2, various headings and flying heights will be achieved over the same forest area. This flight campaign in French Guiana will be also extended to other test sites, taking benefit from our collaboration with the local INRAE teams and their expertise on many forest plots (based on in situ data over 85 ha on regular basis, in addition to airborne, drone based and terrestrial LiDAR measurements, including the BIOMASS super site concepts).Processing methods development:Based on our team expertise, the PhD will take control on existing methods and codes, aiming at generating synthetic aperture 2D and 3D imaging, considering a relevant resolution in order to characterize forest structure and the underlying terrain topography. Given the specificities of drone-based system and flying performances, the expected new processing developments and code optimization will mainly target the minimization of decorrelation sources (related to system, geometrical and temporal effects), and the ability to separate them.Data analysis:Considering the measurements specificities from the drone-based SAR, the analysis work will primarily focus on isolating system and physical effects, from which the cross-comparison with the TropiScat-2 results will be highly relevant. Further steps will then target the spatialization of these results, considering the ability of the drone measurements to estimate the so-called ground to volume ratio (related to the proportion of backscattered energy from the ground, the vegetation structure and their mutual interaction), and to see their impacts on the temporal insightsbrought by the tower-based experiment. These advances related to the characterization of forest structure and terrain topography will also come with the ability to detect anomalies, paving the way to innovative FOPEN methods to monitorillegal of military activities under dense vegetation cover.Reporting:Participation to various scientific meetings and papers writing.For more Information about the topics and the co-financial partner (found by the lab !);contact Directeur de thèse –Then, prepare a resume, a recent transcript and a reference letter from your M2 supervisor/ engineering school director and you will be ready to apply online before March 14th, 2025 Midnight Paris time !ProfilM2 / Engineering student with signal processing skills and/or an experimental profile.

Expected salary

Location

Salon-de-Provence, Bouches-du-Rhône

Job date

Wed, 05 Feb 2025 05:41:27 GMT

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