Inverse Airborne Optical Sectioning [PDF]
arXiv, 2022 We present Inverse Airborne Optical Sectioning (IAOS) an optical analogy to Inverse Synthetic Aperture Radar (ISAR). Moving targets, such as walking people, that are heavily occluded by vegetation can be made visible and tracked with a stationary optical sensor (e.g., a hovering camera drone above forest).
arxiv
SAR-ISAR Blending Using Compressed Sensing Methods [PDF]
, 2015 Inverse Synthetic Aperture Radar (ISAR) target images are extracted using compressed sensing methods. The extracted images are edited and merged into measured Synthetic Aperture Radar (SAR) images.
Jersblad, Johan, Larsson, Christer
core
Some thoughts on the use of InSAR data to constrain models of surface deformation: Noise structure and data downsampling [PDF]
, 2005 Repeat-pass Interferometric Synthetic Aperture Radar (InSAR) provides spatially dense maps of surface deformation with potentially tens of millions of data points. Here we estimate the actual covariance structure of noise in InSAR data.
Lohman, Rowena B., Simons, Mark
core +2 more sources
Inferring Eruption Dynamics From Seismometer Tilt: A Case Study of Erebus and Augustine Volcanoes
Journal of Geophysical Research: Solid Earth, Volume 130, Issue 4, April 2025.Abstract Broadband seismometers are sensitive to tilt as a consequence of their design. We used broadband data from Erebus volcano on Ross Island, Antarctica, and Augustine volcano in Lower Cook Inlet, Alaska, to make tilt measurements associated with individual volcanic explosions and investigate the near‐terminal magmatic system configuration of each
M. S. Christoffersen +5 more
wiley +1 more source
A Multiple Radar Approach for Automatic Target Recognition of Aircraft using Inverse Synthetic Aperture Radar [PDF]
arXiv, 2017 Along with the improvement of radar technologies, Automatic Target Recognition (ATR) using Synthetic Aperture Radar (SAR) and Inverse SAR (ISAR) has come to be an active research area. SAR/ISAR are radar techniques to generate a two-dimensional high-resolution image of a target. Unlike other similar experiments using Convolutional Neural Networks (CNN)
arxiv
3D Near-Field Virtual MIMO-SAR Imaging Using FMCW Radar Systems at 77 GHz [PDF]
arXiv, 2022 In this paper, we present 3D high resolution radar imaging at millimeter-Wave (mmWave) frequencies by means of a combination of virtual Multiple Input Multiple Output (MIMO) Frequency Modulated Continuous Wave (FMCW) Radars and Synthetic Aperture Radar (SAR) which results in a compact, low-cost, and high-speed 3D mmWave imagery system with low ...
arxiv
Joint sparsity-driven inversion and model error correction for radar imaging [PDF]
, 2009 Solution of inverse problems in imaging requires the use of a mathematical model of the observation process. However such models often involve errors and uncertainties themselves. The application of interest in this paper is synthetic aperture radar (SAR)
Cetin, Mujdat +3 more
core +2 more sources
Ocean Response Along the East Antarctic Coastal Margin to the Southern Annular Mode
Geophysical Research Letters, Volume 52, Issue 6, 28 March 2025.Abstract Ocean circulation around the Antarctic coastal margins plays a critical role in heat delivery to Antarctica, melting ice shelves. However, until recently, satellite‐based sea‐level observations have been limited by the presence of sea ice. With improved algorithms, it is now possible to monitor sea‐level fluctuations over most of the Southern ...
K. Mizobata +6 more
wiley +1 more source
Multibeam single frequency synthetic aperture radar processor for imaging separate range swaths [PDF]
, 1982 A single-frequency multibeam synthetic aperture radar for large swath imaging is disclosed. Each beam illuminates a separate ""footprint'' (i.e., range and azimuth interval).
Jain, A.
core +1 more source
A nonquadratic regularization-based technique for joint SAR imaging and model error correction [PDF]
, 2008 Regularization based image reconstruction algorithms have successfully been applied to the synthetic aperture radar (SAR) imaging problem. Such algorithms assume that the mathematical model of the imaging system is perfectly known.
Cetin, Mujdat +3 more
core +1 more source