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Publications about 'least mean squares methods'

Articles in journal or book chapters

  1. Yu Morishita and Ramon F. Hanssen. Deformation Parameter Estimation in Low Coherence Areas Using a Multisatellite InSAR Approach. IEEE Trans. Geosci. Remote Sens., 53(8):4275-4283, August 2015. Keyword(s): SAR Processing, persistent scatterer interferometry, PSI, InSAR, DInSAR, Interferometry, Differential Interferometry, decorrelation, deformation, geophysical techniques, least mean squares methods, radar interferometry, remote sensing by radar, soil, synthetic aperture radar, time series, The Netherlands, drained peat soils, least squares method, local subsidence rates, low coherence areas, multisatellite InSAR, pasture periodic signal, peat periodic signal, persistent scatterer interferometry, satellite data, small baseline subset algorithms, statistically homogeneous pixels, surface deformation parameter estimation, Coherence, Decorrelation, Deformable models, Estimation, Satellites, Soil, Synthetic aperture radar, Decorrelation, radar interferometry, synthetic aperture radar (SAR). [Abstract] [bibtex-entry]


  2. Viet Thuy Vu, Thomas K. Sjogren, Mats I. Pettersson, L. Hakansson, A. Gustavsson, and Lars M. H. Ulander. RFI Suppression in Ultrawideband SAR Using an Adaptive Line Enhancer. IEEE Geosci. Remote Sens. Lett., 7(4):694-698, October 2010. Keyword(s): SAR Processing, RFI, radio frequency interference, RFI mitigation, interference suppression, least mean squares methods, radiofrequency interference, synthetic aperture radar, ultra wideband radar, RFI suppression, UWB low-frequency SAR data, adaptive line enhancer, least mean square algorithm, radiofrequency interference, ultrawideband low-frequency synthetic aperture radar, Adaptive control, Interference suppression, Least mean square algorithms, Line enhancers, Programmable control, Proposals, Radio frequency, Radiofrequency interference, Synthetic aperture radar, Ultra wideband technology, Adaptive line enhancer (ALE), CARABAS-II, normalized least mean square (LMS) (NLMS), radio-frequency interference (RFI), synthetic aperture radar (SAR), ultrawideband (UWB). [Abstract] [bibtex-entry]


  3. Richard T. Lord and Michael R. Inggs. Efficient RFI suppression in SAR using LMS adaptive filter integrated with range/Doppler algorithm. Electronics Letters, 35(8):629-630, 1999. Keyword(s): SAR Processing, Doppler radar, adaptive filters, interference suppression, least mean squares methods, radar imaging, radar interference, synthetic aperture radar, Doppler algorithm, LMS adaptive filter, RFI Suppression, SAR image processing, radiofrequency interference, range compression. [Abstract] [bibtex-entry]


Conference articles

  1. Richard T. Lord and Michael R. Inggs. Approaches to RF interference suppression for VHF/UHF synthetic aperture radar. In Communications and Signal Processing, 1998. COMSIG '98. Proceedings of the 1998 South African Symposium on, pages 95-100, 1998. Keyword(s): SAR Processing, adaptive filters, adaptive signal processing, interference suppression, least mean squares methods, radar imaging, radar interference, synthetic aperture radar, LMS adaptive filter, P-Band, RF interference suppression, RFI Suppression, SAR imagery, VHF/UHF SAR applications, VHF/UHF synthetic aperture radar, coherent subtraction algorithms, filter approaches, image quality, interference power, least-mean-squared filter, radio frequency interference, receiver noise, spectral estimation. [Abstract] [bibtex-entry]


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Please note that access to full text PDF versions of papers is restricted to the Chair of Earth Observation and Remote Sensing, Institute of Environmental Engineering, ETH Zurich.
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This collection of SAR literature is far from being complete.
It is rather a collection of papers which I store in my literature data base. Hence, the list of publications under PUBLICATIONS OF AUTHOR'S NAME should NOT be mistaken for a complete bibliography of that author.




Last modified: Mon Feb 1 16:40:18 2021
Author: Othmar Frey, Earth Observation and Remote Sensing, Institute of Environmental Engineering, Swiss Federal Institute of Technology - ETH Zurich .


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