Publications about 'optimization problem'

Articles in journal or book chapters

1. Yanyan Zhang, Hao Zhang, Shuai Hou, Yunkai Deng, Weidong Yu, and Robert Wang. An Innovative Superpolyhedron (SP) Formation for Multistatic SAR (M-SAR) Interferometry. IEEE Transactions on Geoscience and Remote Sensing, 59(12):10136-10150, December 2021. Keyword(s): Satellites, Synthetic aperture radar, Spaceborne radar, Radar, Space vehicles, Sea measurements, Radar imaging, Genetic algorithm (GA), interferometric synthetic aperture radar (InSAR), multistatic synthetic aperture radar (M-SAR), satellite formation, superpolyhedron (SP). [Abstract] [bibtex-entry]



2. Alireza Tabatabaeenejad, Mariko S. Burgin, and Mahta Moghaddam. Potential of L-Band Radar for Retrieval of Canopy and Subcanopy Parameters of Boreal Forests. IEEE Transactions on Geoscience and Remote Sensing, 50(6):2150-2160, June 2012. Keyword(s): calibration, data analysis, forestry, remote sensing by radar, simulated annealing, soil, vegetation mapping, AD 2010 06, Jet Propulsion Laboratory, L-band radar, National Aeronautics and Space Administration, SMAP mission, Uninhabited Aerial Vehicle Synthetic Aperture Radar, absolute retrieval error analysis, calibration method, canopy parameter retrieval, central Canada boreal forests, discrete scatterer radar model, forest structure, forward scattering model, global optimization scheme, inversion method, old black spruce site, old jack pine forests, optimization algorithm, optimization problem, relative retrieval error, scattering mechanisms, simulated annealing, soil moisture information, subcanopy parameter retrieval, surface soil moisture retrieval, synthetic data, vegetation parameters, young jack pine forests, Backscatter, Dielectric constant, L-band, Radar, Scattering, Soil moisture, Vegetation mapping, Allometric relationships, Canadian Experiment for Soil Moisture in 2010 (CanEx-SM10), L-band radar, Soil Moisture Active and Passive (SMAP), boreal forest, canopy, inverse problem, microwave scattering. [Abstract] [bibtex-entry]



3. A. Budillon, A. Evangelista, and G. Schirinzi. Three-Dimensional SAR Focusing From Multipass Signals Using Compressive Sampling. IEEE Trans. Geosci. Remote Sens., 49(1):488 -499, jan. 2011. Keyword(s): SAR Processing, SAR Tomography, Tomography, 3D SAR data imaging, SAR tomography, compressive sampling, image formation, multipass SAR data, multipass signals, optimization problem, spaced acquisition orbits, three-dimensional synthetic aperture radar, tomographic imaging, truncated singular value decomposition technique, image sampling, optimisation, radar imaging, synthetic aperture radar, tomography;. [Abstract] [bibtex-entry]



4. Emmanuel J. Candès, Xiaodong Li, Yi Ma, and John Wright. Robust Principal Component Analysis. J. ACM, 58(3), June 2011. Keyword(s): Principal components, sparsity, robustness vis-a-vis outliers, L1-norm minimization, nuclear-norm minimization, duality, low-rank matrices, video surveillance. [Abstract] [bibtex-entry]



5. E.J. Candes and Y. Plan. Matrix Completion With Noise. Proceedings of the IEEE, 98(6):925-936, june 2010. Keyword(s): compressed sensing, convex optimization problem, data constraints, low rank matrices, matrix completion, nuclear norm minimization, data integrity, matrix algebra, minimisation, noise, signal sampling;. [Abstract] [bibtex-entry]



6. Manoochehr Shirzaei and TR Walter. Time-dependent volcano source monitoring using interferometric synthetic aperture radar time series: A combined genetic algorithm and Kalman filter approach. Journal of Geophysical Research: Solid Earth, 115(B10), 2010. Keyword(s): SAR Processing, Deformation, Deformation Monitoring, DInSAR, SAR Interferometry, Differential Interferometry, Kalman Filter. [Abstract] [bibtex-entry]



7. Robert. L. Morrison, Minh N. Do, and David C. Munson. SAR Image Autofocus By Sharpness Optimization: A Theoretical Study. IEEE Transactions on Image Processing, 16(9):2309-2321, September 2007. Keyword(s): SAR Processing, Autofocus, SAR image autofocus, intensity-squared metric, point-targets image, sharpness optimization, synthetic aperture radar, image processing, optimisation, synthetic aperture radar, Algorithms, Artificial Intelligence, Computer Simulation, Image Enhancement, Image Interpretation, Computer-Assisted, Models, Theoretical, Pattern Recognition, Automated, Reproducibility of Results, Sensitivity and Specificity;. [Abstract] [bibtex-entry]



8. E.J. Candes, J. Romberg, and T. Tao. Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information. IEEE Transactions on Information Theory, 52(2):489-509, feb. 2006. Keyword(s): Fourier coefficient, convex optimization, discrete-time signal, image reconstruction, incomplete frequency information, linear programming, minimization problem, nonlinear sampling theorem, piecewise constant object, probability value, robust uncertainty principle, signal reconstruction, sparse random matrix, trigonometric expansion, Fourier analysis, convex programming, image reconstruction, image sampling, indeterminancy, linear programming, minimisation, piecewise constant techniques, probability, signal reconstruction, signal sampling, sparse matrices;. [Abstract] [bibtex-entry]



9. E.J. Candes and T. Tao. Decoding by linear programming. IEEE Transactions on Information Theory, 51(12):4203-4215, December 2005. Keyword(s): Gaussian random matrix, basis pursuit, linear code decoding, linear programming, minimization problem, natural error correcting problem, simple convex optimization problem, sparse solution, uncertainty principle, Gaussian processes, convex programming, decoding, error correction codes, indeterminancy, linear codes, linear programming, minimisation, random codes, sparse matrices;. [Abstract] [bibtex-entry]



10. Curtis W. Chen and Howard A. Zebker. Phase unwrapping for large SAR interferograms: statistical segmentation and generalized network models. IEEE Trans. Geosci. Remote Sens., 40(8):1709-1719, August 2002. Keyword(s): SAR Processing, phase unwrapping, SNAPHU, geophysical signal processing, image segmentation, optimisation, radar imaging, radiowave interferometry, remote sensing by radar, statistical analysis, synthetic aperture radar, InSAR data, SNAPHU, a posteriori probability, central Alaska, full-size interferograrn, generalized network models, interferometric input data, interferometric synthetic aperture radar data, large SAR interferograms, network-flow, nonlinear solver, phase unwrapping, secondary optimization problem, statistical models, statistical segmentation, statistical-cost network-flow phase-unwrapping algorithm, tile-unwrapping stage, tiles, topographic interferogram, Algorithm design and analysis, Data analysis, Geophysics computing, Partitioning algorithms, Phase estimation, Probability, Synthetic aperture radar interferometry, Two dimensional displays. [Abstract] [bibtex-entry]



11. S.R. Cloude and Konstantinos P. Papathanassiou. Polarimetric SAR interferometry. IEEE Transactions on Geoscience and Remote Sensing, 36(5):1551-1565, September 1998. Keyword(s): SAR Processing, PolInSAR, geophysical techniques, radar imaging, radar polarimetry, radar theory, remote sensing by radar, synthetic aperture radarInSAR, coherence optimization problem, elevated forest canopy, general formulation, geophysical measurement technique, interferogram, interferometric SAR, interferometric coherence, land surface, linear combinations, maximization, polarimetric SAR interferometry, polarimetric basis transformation, radar remote sensing, scalar interferometry, stochastic scattering model, strong polarization dependency, synthetic aperture radar, terrain mapping, vector wave interferometry, SAR Tomography. [Abstract] [bibtex-entry]

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This collection of SAR literature is far from being complete.
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