Compressive 2D/3D SAR (ComSAR)

• Applicants: Professor Dr.-Ing. Joachim Ender; Professor Dr.-Ing. Otmar Loffeld (†)
• Subject Area: Electronic Semiconductors, Components and Circuits, Integrated Systems, Sensor Technology, Theoretical Electrical Engineering
• Term: from 2015 to 2020
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 271711851

• Final Report Year: 2020

Final Report Abstract

No abstract available

Publications

• A nullspace based L1 minimizing Kalman filter approach to sparse CS reconstruction, in EUSAR 2016: 11th European Conference on Synthetic Aperture Radar, Proceedings of, 2016, pp. 1-5
  O. Loffeld, A. Seel, M. H. Conde, and L. Wang
  
• ISAR Imaging using A Greedy Kalman Filtering Method with Sparse Constraints, in EUSAR 2016: 11th European Conference on Synthetic Aperture Radar, Proceedings of, 2016, pp. 1-5
  L. Wang, O. Loffeld, and Y. Qian
  
• ISAR imaging using a nullspace ℓ1 minimizing Kalman filter approach, in Compressed Sensing Theory and its Applications to Radar, Sonar and Remote Sensing (CoSeRa), 2016 4th International Workshop on, 2016, pp. 232-236
  L. Wang and O. Loffeld
  (See online at https://doi.org/10.1109/CoSeRa.2016.7745735)
• Norm-minimized scattering data from intensities, in Communications (COMM), 2016 International Conference on, 2016, pp. 455-460
  A. Seel, A. Davtyan, U. Pietsch, and O. Loffeld
  (See online at https://doi.org/10.1109/ICComm.2016.7528205)
• Norm-Minimized Scattering Data from Intensity Spectra, Mathematical Problems in Engineering, vol. 2016, 2016
  A. Seel, A. Davtyan, U. Pietsch, and O. Loffeld
  (See online at https://doi.org/10.1155/2016/9853714)
• Sparse CS reconstruction by nullspace based ℓ1 minimizing Kalman filtering, in Communications (COMM), 2016 International Conference on, 2016, pp. 449-454
  O. Loffeld, A. Seel, M. H. Conde, and L. Wang
  (See online at https://doi.org/10.1109/ICComm.2016.7528204)
• A null-space-based genetic algorithm for constrained ℓ1 minimization, IEEE International Symposium on Signal Processing and Information Technology (ISSPIT), Bilbao, Spain, pp. 294-299, 18-20 Dec., 2017
  M. Heredia Conde, D.A. Hage, O. Loffeld
  (See online at https://doi.org/10.1109/ISSPIT.2017.8388658)
• Sparse ISAR imaging using a greedy Kalman filtering approach, Signal Processing, vol. 138, pp. 1-10, 2017
  L. Wang, O. Loffeld, K. Ma, and Y. Qian
  (See online at https://doi.org/10.1016/j.sigpro.2017.03.002)
• Convergence Accelerator for ℓ1 -Minimizing Kalman Filter, 5th International Workshop on Compressed Sensing applied to Radar, Multimodal Sensing, and Imaging (CoSeRa 2018), Siegen, September 10-13, 2018
  D.A. Hage, M. Heredia Conde, O. Loffeld
  
• From L1 Minimization to Entropy Minimization: A Novel Approach for Sparse Signal Recovery in Compressive Sensing, 26th European Signal Processing Conference (EUSIPCO), pp. 568-572, 3-7 Sept. 2018
  M. Heredia Conde, O. Loffeld
  (See online at https://doi.org/10.23919/EUSIPCO.2018.8553245)
• Some New Results on ℓ1 -Minimizing Nullspace Kalman Filtering for Remote Sensing Applications, arXiv
  O. Loffeld, D.A. Hage, M. Heredia Conde, L. Wang
  (See online at https://doi.org/10.48550/arXiv.1808.06538)
• Some new Results on ℓ1 Minimizing Nullspace Kalman Filtering, EUSAR 2018; 12th European Conference on Synthetic Aperture Radar, Aachen, Germany, pp. 1-6., 2018
  O. Loffeld, D.A. Hage, M. Heredia Conde, L. Wang
  
• New Results on Sparse Signal Recovery via Kalman-Filter-based ℓ1 Minimization, IEEE Elsevier Signal Processing, Jan. 2020
  D.A. Hage, M. Heredia Conde, O. Loffeld
  (See online at https://doi.org/10.1016/j.sigpro.2020.107487)