Tomographic SAR reconstruction (ESR8)
The closing date for this job submission has passed.
Applying tomographic SAR inversion using compressive sensing is well established in the SAR community. In contrast to state of the art approaches applied to satellite data novel CS reconstruction approaches combining sparsity with prior information will be researched and implemented. We intend to use high resolution airborne data sets from FHR and later, from our own sensor platform. The data is superior to satellite data concerning resolution und SNR. The main goal is the evaluation of the used CS methods for remote sensing 3-D imaging. Additionally, the performance in layover areas and the super-resolution properties will be checked. The developed methods will be compared with the state of the art.
The successful candidate will be employed for a maximum period of three years full-time equivalent and receives a generous financial package plus an additional mobility and family allowance according to the rules for Early Stage Researchers (ESRs) in an EU Marie Sklodowska-Curie Actions Innovative Training Networks (ITN). A career development plan will be prepared for each fellow in accordance with his/her supervisor and will include training, planned secondments and outreach activities in partner institutions of the network. The ESR fellows are supposed to complete their PhD thesis by the end of the 3rd year of their employment. For more information please visit the Marie Sklodowska-Curie Actions Innovative Training Networks website.
Simulation and evaluation of the theoretical limits regarding coherence and resolution using CS in tomographic SAR for the used configurations
Design of the signal and noise model of the tomographic geometry for sparse reconstruction.
Development of novel CS reconstruction algorithms incorporating prior information.
Working with real data including high resolution SAR processing and 3D scene reconstruction.
Planning and realization of tomographic experiments using the SAR sensor of ZESS.
identify advantages and limitations by synthetic and experimental tests.
Master of Science in Electrical Engineering, Electronics Technology, Electrical Engineering Technology, Electrical and Computer Engineering, Physics, Industrial Engineering, Information Technologies or related fields
ESRs must demonstrate that their ability to understand and express themselves in both written and spoken English is sufficiently high for them to derive the full benefit from the network training. Non-native English speakers are required to provide evidence of English language competency. (TOEFL … )
Some basic knowledge on signal processing and radar technology
FHG (FHR), Wachtberg, Germany, Dr. P. Berens, 5 months, working with real airborne TomoSAR data.
WIS (SAMPL) , Israel, Prof. Dr. Yonina Eldar, 2 months, work on CS reconstruction algorithms and compare with own approaches.
GAMMA, Bern, Switzerland, Dr. U. Wegmüller, 2 months, CS algorithm refinement, optimization, and analysis.
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