This document summarizes a method for blind azimuth phase elimination in TerraSAR-X ScanSAR interferometry. The method involves determining a compensation factor based on the differences between stripmap and ScanSAR imaging geometries. It then performs a coarse initialisation of the key parameter, which is the burst duration. Finally, it refines the key parameter and eliminates the azimuth phase through compensation. The goal is to address distortions and signal loss that occur after resampling of ScanSAR SLC data.
SPPRA2010 Estimating a Rotation Matrix R by using higher-order Matrices R^n w...Toru Tamaki
Toru Tamaki, Bisser Raytchev, Kazufumi Kaneda, Toshiyuki Amano : "Wstimating a Rotation Matrix R by using higher-order Matrices R^n with Application to Supervised Pose Estimation," Proc. of SPPRA 2010: The Seventh IASTED International Conference on Signal Processing, Pattern Recognition and Applications, pp. 58-64 (2010 02). Innsbruck, Austria, 2010/February/17-19.
The document provides information about various physics concepts related to measurements and motion. It discusses:
1) Base quantities and derived quantities in physics, with base quantities being length, mass, time, temperature, and current. Derived quantities are defined in terms of base quantities.
2) Scalar and vector quantities, with scalars having magnitude but no direction, and vectors having both magnitude and direction.
3) Methods for improving measurement accuracy such as taking multiple readings and calculating an average. Sources of error like parallax error and how to avoid them are also discussed.
4) Examples of measurement tools like vernier callipers and micrometer screws, and how to account for errors like zero error in readings.
The aim of this report is to demonstrate the ability to apply and calculate the correct formulas for different Scientific and Analytical scenarios like:
- Shear Force & Bending Moment for a Beam.
- The use of software for the calculation of the above.
- Shear Stress for solid shafts.
- Friction & Acceleration.
- Simple Harmonic Motion.
Normal Modes Analysis can be used to estimate full 2D velocity vectors from radial CODAR measurements in tidal channels. It models flow as a series of eigenfunctions satisfying the boundary conditions. By fitting the radial radar data to the Normal Modes solutions, coefficients for each mode can be determined via least squares. This allows reconstruction of the full velocity field and visualization of particle trajectories over time, providing insight into tidal flow dynamics. Future work aims to validate the method against direct measurements during flow reversals and determine the optimal number of modes.
This presentation is for my class to work through as teachers are on a series of PD days. It is based on a very bad One Direction joke cracked in a class about vectors.
This document summarizes an implementation of economic gas-like models to analyze the influence of underlying network topologies. It introduces random symmetric and directed exchange rules for money transfers between agents. For random symmetric exchanges on networks like complete graphs, spatial networks, and scale-free networks, the money distribution converges to a Boltzmann-Gibbs form and is robust to network structure. A model with uniform savings is also introduced, where the money distribution takes a gamma-like form.
The document summarizes the development of interferometric radiometry for remote sensing from space. It describes the ESTAR project which demonstrated the viability of aperture synthesis for remote sensing applications. It outlines the hardware used by ESTAR and discusses various field campaigns involving soil moisture and ocean salinity measurements. Plans are described for a proposed spaceborne version called HYDROSTAR, and lessons learned from subsequent projects including 2D-STAR, SMEX-03, and issues dealing with radio frequency interference and noise injection stability.
A new study developed three algorithms to automatically determine the boundaries of scatter plots used in the triangle method for estimating evapotranspiration from satellite data. The algorithms were tested on data from northern China and showed improved consistency over manual boundary selection. Algorithm II performed best by separating scatter plots into upper and lower regions before boundary fitting. The new automatic method enables more objective and repeatable evapotranspiration estimates at regional scales from remote sensing data.
SPPRA2010 Estimating a Rotation Matrix R by using higher-order Matrices R^n w...Toru Tamaki
Toru Tamaki, Bisser Raytchev, Kazufumi Kaneda, Toshiyuki Amano : "Wstimating a Rotation Matrix R by using higher-order Matrices R^n with Application to Supervised Pose Estimation," Proc. of SPPRA 2010: The Seventh IASTED International Conference on Signal Processing, Pattern Recognition and Applications, pp. 58-64 (2010 02). Innsbruck, Austria, 2010/February/17-19.
The document provides information about various physics concepts related to measurements and motion. It discusses:
1) Base quantities and derived quantities in physics, with base quantities being length, mass, time, temperature, and current. Derived quantities are defined in terms of base quantities.
2) Scalar and vector quantities, with scalars having magnitude but no direction, and vectors having both magnitude and direction.
3) Methods for improving measurement accuracy such as taking multiple readings and calculating an average. Sources of error like parallax error and how to avoid them are also discussed.
4) Examples of measurement tools like vernier callipers and micrometer screws, and how to account for errors like zero error in readings.
The aim of this report is to demonstrate the ability to apply and calculate the correct formulas for different Scientific and Analytical scenarios like:
- Shear Force & Bending Moment for a Beam.
- The use of software for the calculation of the above.
- Shear Stress for solid shafts.
- Friction & Acceleration.
- Simple Harmonic Motion.
Normal Modes Analysis can be used to estimate full 2D velocity vectors from radial CODAR measurements in tidal channels. It models flow as a series of eigenfunctions satisfying the boundary conditions. By fitting the radial radar data to the Normal Modes solutions, coefficients for each mode can be determined via least squares. This allows reconstruction of the full velocity field and visualization of particle trajectories over time, providing insight into tidal flow dynamics. Future work aims to validate the method against direct measurements during flow reversals and determine the optimal number of modes.
This presentation is for my class to work through as teachers are on a series of PD days. It is based on a very bad One Direction joke cracked in a class about vectors.
This document summarizes an implementation of economic gas-like models to analyze the influence of underlying network topologies. It introduces random symmetric and directed exchange rules for money transfers between agents. For random symmetric exchanges on networks like complete graphs, spatial networks, and scale-free networks, the money distribution converges to a Boltzmann-Gibbs form and is robust to network structure. A model with uniform savings is also introduced, where the money distribution takes a gamma-like form.
The document summarizes the development of interferometric radiometry for remote sensing from space. It describes the ESTAR project which demonstrated the viability of aperture synthesis for remote sensing applications. It outlines the hardware used by ESTAR and discusses various field campaigns involving soil moisture and ocean salinity measurements. Plans are described for a proposed spaceborne version called HYDROSTAR, and lessons learned from subsequent projects including 2D-STAR, SMEX-03, and issues dealing with radio frequency interference and noise injection stability.
A new study developed three algorithms to automatically determine the boundaries of scatter plots used in the triangle method for estimating evapotranspiration from satellite data. The algorithms were tested on data from northern China and showed improved consistency over manual boundary selection. Algorithm II performed best by separating scatter plots into upper and lower regions before boundary fitting. The new automatic method enables more objective and repeatable evapotranspiration estimates at regional scales from remote sensing data.
The document discusses bidirectional reflectance distribution functions (BRDF) in coastal waters and their application to validating ocean color satellites. It presents a BRDF correction algorithm optimized for coastal waters dominated by sediments or colored dissolved organic matter. Validation using in situ radiometer data from the Long Island Sound Coastal Observatory shows the proposed algorithm reduces dispersion in water leaving radiances compared to standard open ocean algorithms, improving satellite matchup comparisons.
The document discusses a Bayesian approach called localized multi-kernel relevance vector machine (LMK-RVM) that uses multiple kernel functions to perform classification. LMK-RVM allows different kernel functions or parameters to be used in different areas of feature space, providing more flexibility than single-kernel models. It combines multi-kernel learning with the sparsity of the relevance vector machine (RVM) model. The document outlines LMK-RVM and provides examples showing it can improve classification accuracy and potentially provide sparser models compared to single-kernel approaches.
The document describes a displaced ensemble variational data assimilation method to incorporate microwave imager brightness temperatures (TBs) into a cloud-resolving model. It uses an ensemble-based variational assimilation approach with a displacement error correction scheme to address errors from misplaced rainfall areas between observations and forecasts. The method is applied to assimilate TMI TBs for Typhoon CONSON on June 9, 2004, improving precipitation forecasts up to 4 hours later by reducing displacement errors and avoiding misinterpretation of TB increments.
This document presents a technique for spectral pixel reconstruction to generate natural color images from multispectral satellite sensors. It describes developing a framework to reconstruct missing spectral bands using a transformation matrix between true and false color spaces. The technique is applied to sensors like IKONOS, QuickBird, IRS-P6, LISS-3, LISS-4 and AWiFS to generate additional spectral information and high quality natural color images, even for sensors lacking a blue band. Deconvolution and noise reduction methods like Wiener filtering and Bayesian approaches are also discussed. The technique provides a way to make images from different sensors comparable by reconstructing spectral pixels.
EcoSAR will be the first airborne P-band digital beamforming polarimetric interferometric SAR to quantify ecosystem structure, biomass, and surface water. It will fly on NASA's P3 airplane and measure biomass up to 200 Mg/ha and canopy heights to 1m accuracy. These measurements will help validate future satellite missions and improve carbon estimates. EcoSAR's design includes dual 25m baseline antennas, 435MHz center frequency, and high resolution science mode of 1.3m. Its main objectives are to measure biomass, height, ecosystem structure over disturbances, and support international carbon initiatives. P-band is well-suited for this as its long wavelength penetrates canopies. The instrument
1) Satellite images detected the disappearance of a large supraglacial lake on Tshojo Glacier in Bhutan between March and July 2009, coinciding with a glacier outburst flood event.
2) The lake volume was estimated at 1.47 million cubic meters based on a post-flood DEM, suggesting it was an adequate source for the flood waters.
3) Subsequent images showed the lake beginning to refill in late 2010, indicating its behavior should continue to be monitored to predict future flood risks.
Two-year assessment of Nowcasting performance in the CASA systemgrssieee
This document summarizes a two-year assessment of nowcasting performance in the CASA radar network system. The CASA system uses a nowcasting algorithm called DARTS to provide 0-20 minute forecasts for emergency management and 1-5 minute forecasts for radar scanning adaptation. Evaluation of the system using over 95 hours of data from 2009-2010 found that the DARTS nowcasting algorithm provided favorable skill scores and improved steering of radar scans over persistence forecasts alone. Forecaster feedback also indicated the nowcasting-guided steering eliminated issues with narrow sector scans missing important storm features.
This document describes a series of field experiments called MicroWEXs that were conducted to collect detailed seasonal microwave observation datasets under dynamic vegetation conditions. The experiments measured soil moisture, temperature, and vegetation properties. Forward microwave emission and scattering models were developed and coupled with soil-vegetation-atmosphere transfer models. Assimilation algorithms using the Ensemble Kalman Filter were tested to estimate soil moisture from the microwave observations. The MicroWEX-10 experiment planned for 2011 aimed to provide unprecedented diurnal active and passive microwave data to further improve the models and assimilation methods.
The document discusses snow analysis techniques used at the European Centre for Medium-Range Weather Forecasts (ECMWF). It describes the evolution from using Cressman interpolation and NOAA/NESDIS 24km snow cover data in the past to the current operational Optimum Interpolation snow analysis using higher resolution 4km NESDIS data. Issues with the previous Cressman method like "PacMan" patterns are addressed. The revised snow analysis was implemented in November 2010 and provides improvements over the older techniques.
1. The SBAS-DInSAR algorithm was used to analyze ERS and ENVISAT SAR data from 1992-2010 over the Yellowstone Caldera, revealing a complex deformation field.
2. An optimal distribution of interferometric pairs was identified to limit the impact of temporal decorrelation, exploiting pairs with small baselines.
3. The analysis revealed accelerated uplift in the Yellowstone caldera between 2004-2007, with rates consistent with inflation of a subsurface sill at a rate of 0.1 km3 per year.
The document summarizes the findings of NASA's VIIRS Land Team regarding the utility of VIIRS Land and Cryosphere EDRs to meet NASA's science requirements. It discusses several EDRs including land surface temperature, surface type, albedo, vegetation indices, and snow cover. For most products, continuity with MODIS is important but some changes or additions to the algorithms or additional products may be needed. Processing via NASA's Land PEATE could produce climate-quality VIIRS science products compatible with MODIS.
The document proposes a method to infer daily soil moisture levels from multiple satellite sensors, including MODIS, SEVIRI MSG, ASAR, and AMSR-E. It uses an apparent thermal inertia (ATI) approach derived from MODIS thermal data, calibrated with SAR and AMSR-E soil moisture estimates. The ATI values are filtered over time using AMSR-E data to reduce noise and provide daily soil moisture index classes for different test sites in Italy and France. Results show the method achieves reasonably accurate soil moisture estimates compared to ground measurements.
The document summarizes the pre-launch assessment of the VIIRS cloud mask (VCM) as follows:
1) It reviewed the VCM logic and contents, and presented global results using the pre-launch VCM without tuning, which showed room for improvement.
2) It described methods used for pre-launch tuning using synthetic data, which helped reduce false alarms and improve performance over land and desert.
3) Quantitative results showed the tuning effort significantly improved the VCM's probability of correct typing, especially over land.
Learning Moving Cast Shadows for Foreground Detection (VS 2008)Jia-Bin Huang
The document summarizes a research paper about learning moving cast shadows for foreground detection. It presents a proposed algorithm that uses a confidence-rated Gaussian mixture learning approach and Bayesian framework with Markov random fields to model local and global shadow features. This exploits the complementary nature of local and global features to improve shadow detection. The algorithm is evaluated on outdoor and indoor video sequences, showing improved accuracy over previous methods especially in adaptability to different lighting conditions. Future work could incorporate additional features and more powerful models.
Magnetic tracking is one of miscellaneous motion capture methods, and maybe the oldest. However, its working principle is rarely introduced in detail perhaps due to its early adaptation resides in military and medical industry. Due to my interest in VR & animation MoCap, I’ve spent some time digging into the very depth of it and would like to share some non-confidential knowledge of it with you.
In this slide, a short history of magnetic tracking will be visited, followed by its working principle and algorithm simulation. Hope you enjoy it.
If you wanna discuss something in depth with me, please don’t hesitate to contact me via: dibao.wang@gmail.com
The document summarizes a meeting of the 3rd Thematic Network on photometric stereo estimation from spectral systems. It discusses using photometric stereo techniques to simultaneously recover spectral reflectance and surface relief from images. Specifically, it presents using an RGB digital camera to do this and recover 3D shape and albedo from surfaces under different lighting conditions. Results show good color recovery with around 2% total error between original and simulated images under the same illuminant but different geometries.
Bayesian Defect Signal Analysis for Nondestructive Evaluation of MaterialsAleksandar Dogandžić
In this document, the author describes a Bayesian approach for analyzing non-destructive evaluation (NDE) data to identify elliptically-shaped defect regions. An elliptical parametric model is used to represent potential defect locations and shapes. Measurements are modeled as signals from defects plus noise. A hierarchical Bayesian model incorporates priors on the elliptical parameters and defect signal distributions. Markov chain Monte Carlo simulations are used to sample from the posterior distribution over the parameters given the data in order to identify likely defect regions and signals. Numerical examples are presented to demonstrate the approach.
Founded in 2001, this company is headquartered in Schelle, Belgium and has additional offices in Evergem, Belgium and Vancouver, Canada. It develops gyroscopic pipeline mapping systems for utility infrastructure like gas, water and telecommunications pipelines. The systems contain inertial sensors like gyroscopes and accelerometers that are calibrated to align with the pipe. As the system is moved through the pipe, it records location data along with bend radius, weld locations and offsets. The output data can be used for GIS mapping, pre-commissioning compliance, and defect detection. The systems are applicable to pipes ranging in size from 32mm to 800mm in diameter and made from materials like HDPE, steel and concrete. Recent projects
Synthetic Aperture Radar (SAR) uses signal processing techniques to synthesize a large antenna from data collected by a physically small antenna as it moves along a flight path. This allows SAR to achieve high-resolution images independent of altitude. SAR transmits microwave pulses and analyzes the returned echoes to build up images of the terrain. SAR has various applications including topographic mapping and measuring ocean waves, currents, and wind. Ocean backscatter measured by SAR is influenced by surface roughness driven by factors like wind as well as hydrodynamic effects of waves and currents.
У рамках програми «Підвищення кваліфікації фахівців нафтогазової галузі України для міжнародного співробітництва та роботи у західних компаніях», за підтримки компанії «Shell» 6 березня в аудиторії ВНЗ «Інститут Тутковського» відбулися курси підвищення кваліфікації на тему «Від побудови сейсмічних зображень до інверсії».
1) Techniques are presented for accurately geolocating radar data from the TerraSAR-X and TanDEM-X satellites. Effects from the ionosphere, water vapor, tides, and continental drift must be accounted for.
2) Measurements of corner reflectors were used to evaluate absolute and relative localization accuracy. Accounting for all effects improved absolute accuracy to just a few centimeters for TerraSAR-X.
3) The relative accuracy between TanDEM-X images was sub-centimeter in range, demonstrating the capability for highly precise digital elevation models.
The document discusses bidirectional reflectance distribution functions (BRDF) in coastal waters and their application to validating ocean color satellites. It presents a BRDF correction algorithm optimized for coastal waters dominated by sediments or colored dissolved organic matter. Validation using in situ radiometer data from the Long Island Sound Coastal Observatory shows the proposed algorithm reduces dispersion in water leaving radiances compared to standard open ocean algorithms, improving satellite matchup comparisons.
The document discusses a Bayesian approach called localized multi-kernel relevance vector machine (LMK-RVM) that uses multiple kernel functions to perform classification. LMK-RVM allows different kernel functions or parameters to be used in different areas of feature space, providing more flexibility than single-kernel models. It combines multi-kernel learning with the sparsity of the relevance vector machine (RVM) model. The document outlines LMK-RVM and provides examples showing it can improve classification accuracy and potentially provide sparser models compared to single-kernel approaches.
The document describes a displaced ensemble variational data assimilation method to incorporate microwave imager brightness temperatures (TBs) into a cloud-resolving model. It uses an ensemble-based variational assimilation approach with a displacement error correction scheme to address errors from misplaced rainfall areas between observations and forecasts. The method is applied to assimilate TMI TBs for Typhoon CONSON on June 9, 2004, improving precipitation forecasts up to 4 hours later by reducing displacement errors and avoiding misinterpretation of TB increments.
This document presents a technique for spectral pixel reconstruction to generate natural color images from multispectral satellite sensors. It describes developing a framework to reconstruct missing spectral bands using a transformation matrix between true and false color spaces. The technique is applied to sensors like IKONOS, QuickBird, IRS-P6, LISS-3, LISS-4 and AWiFS to generate additional spectral information and high quality natural color images, even for sensors lacking a blue band. Deconvolution and noise reduction methods like Wiener filtering and Bayesian approaches are also discussed. The technique provides a way to make images from different sensors comparable by reconstructing spectral pixels.
EcoSAR will be the first airborne P-band digital beamforming polarimetric interferometric SAR to quantify ecosystem structure, biomass, and surface water. It will fly on NASA's P3 airplane and measure biomass up to 200 Mg/ha and canopy heights to 1m accuracy. These measurements will help validate future satellite missions and improve carbon estimates. EcoSAR's design includes dual 25m baseline antennas, 435MHz center frequency, and high resolution science mode of 1.3m. Its main objectives are to measure biomass, height, ecosystem structure over disturbances, and support international carbon initiatives. P-band is well-suited for this as its long wavelength penetrates canopies. The instrument
1) Satellite images detected the disappearance of a large supraglacial lake on Tshojo Glacier in Bhutan between March and July 2009, coinciding with a glacier outburst flood event.
2) The lake volume was estimated at 1.47 million cubic meters based on a post-flood DEM, suggesting it was an adequate source for the flood waters.
3) Subsequent images showed the lake beginning to refill in late 2010, indicating its behavior should continue to be monitored to predict future flood risks.
Two-year assessment of Nowcasting performance in the CASA systemgrssieee
This document summarizes a two-year assessment of nowcasting performance in the CASA radar network system. The CASA system uses a nowcasting algorithm called DARTS to provide 0-20 minute forecasts for emergency management and 1-5 minute forecasts for radar scanning adaptation. Evaluation of the system using over 95 hours of data from 2009-2010 found that the DARTS nowcasting algorithm provided favorable skill scores and improved steering of radar scans over persistence forecasts alone. Forecaster feedback also indicated the nowcasting-guided steering eliminated issues with narrow sector scans missing important storm features.
This document describes a series of field experiments called MicroWEXs that were conducted to collect detailed seasonal microwave observation datasets under dynamic vegetation conditions. The experiments measured soil moisture, temperature, and vegetation properties. Forward microwave emission and scattering models were developed and coupled with soil-vegetation-atmosphere transfer models. Assimilation algorithms using the Ensemble Kalman Filter were tested to estimate soil moisture from the microwave observations. The MicroWEX-10 experiment planned for 2011 aimed to provide unprecedented diurnal active and passive microwave data to further improve the models and assimilation methods.
The document discusses snow analysis techniques used at the European Centre for Medium-Range Weather Forecasts (ECMWF). It describes the evolution from using Cressman interpolation and NOAA/NESDIS 24km snow cover data in the past to the current operational Optimum Interpolation snow analysis using higher resolution 4km NESDIS data. Issues with the previous Cressman method like "PacMan" patterns are addressed. The revised snow analysis was implemented in November 2010 and provides improvements over the older techniques.
1. The SBAS-DInSAR algorithm was used to analyze ERS and ENVISAT SAR data from 1992-2010 over the Yellowstone Caldera, revealing a complex deformation field.
2. An optimal distribution of interferometric pairs was identified to limit the impact of temporal decorrelation, exploiting pairs with small baselines.
3. The analysis revealed accelerated uplift in the Yellowstone caldera between 2004-2007, with rates consistent with inflation of a subsurface sill at a rate of 0.1 km3 per year.
The document summarizes the findings of NASA's VIIRS Land Team regarding the utility of VIIRS Land and Cryosphere EDRs to meet NASA's science requirements. It discusses several EDRs including land surface temperature, surface type, albedo, vegetation indices, and snow cover. For most products, continuity with MODIS is important but some changes or additions to the algorithms or additional products may be needed. Processing via NASA's Land PEATE could produce climate-quality VIIRS science products compatible with MODIS.
The document proposes a method to infer daily soil moisture levels from multiple satellite sensors, including MODIS, SEVIRI MSG, ASAR, and AMSR-E. It uses an apparent thermal inertia (ATI) approach derived from MODIS thermal data, calibrated with SAR and AMSR-E soil moisture estimates. The ATI values are filtered over time using AMSR-E data to reduce noise and provide daily soil moisture index classes for different test sites in Italy and France. Results show the method achieves reasonably accurate soil moisture estimates compared to ground measurements.
The document summarizes the pre-launch assessment of the VIIRS cloud mask (VCM) as follows:
1) It reviewed the VCM logic and contents, and presented global results using the pre-launch VCM without tuning, which showed room for improvement.
2) It described methods used for pre-launch tuning using synthetic data, which helped reduce false alarms and improve performance over land and desert.
3) Quantitative results showed the tuning effort significantly improved the VCM's probability of correct typing, especially over land.
Learning Moving Cast Shadows for Foreground Detection (VS 2008)Jia-Bin Huang
The document summarizes a research paper about learning moving cast shadows for foreground detection. It presents a proposed algorithm that uses a confidence-rated Gaussian mixture learning approach and Bayesian framework with Markov random fields to model local and global shadow features. This exploits the complementary nature of local and global features to improve shadow detection. The algorithm is evaluated on outdoor and indoor video sequences, showing improved accuracy over previous methods especially in adaptability to different lighting conditions. Future work could incorporate additional features and more powerful models.
Magnetic tracking is one of miscellaneous motion capture methods, and maybe the oldest. However, its working principle is rarely introduced in detail perhaps due to its early adaptation resides in military and medical industry. Due to my interest in VR & animation MoCap, I’ve spent some time digging into the very depth of it and would like to share some non-confidential knowledge of it with you.
In this slide, a short history of magnetic tracking will be visited, followed by its working principle and algorithm simulation. Hope you enjoy it.
If you wanna discuss something in depth with me, please don’t hesitate to contact me via: dibao.wang@gmail.com
The document summarizes a meeting of the 3rd Thematic Network on photometric stereo estimation from spectral systems. It discusses using photometric stereo techniques to simultaneously recover spectral reflectance and surface relief from images. Specifically, it presents using an RGB digital camera to do this and recover 3D shape and albedo from surfaces under different lighting conditions. Results show good color recovery with around 2% total error between original and simulated images under the same illuminant but different geometries.
Bayesian Defect Signal Analysis for Nondestructive Evaluation of MaterialsAleksandar Dogandžić
In this document, the author describes a Bayesian approach for analyzing non-destructive evaluation (NDE) data to identify elliptically-shaped defect regions. An elliptical parametric model is used to represent potential defect locations and shapes. Measurements are modeled as signals from defects plus noise. A hierarchical Bayesian model incorporates priors on the elliptical parameters and defect signal distributions. Markov chain Monte Carlo simulations are used to sample from the posterior distribution over the parameters given the data in order to identify likely defect regions and signals. Numerical examples are presented to demonstrate the approach.
Founded in 2001, this company is headquartered in Schelle, Belgium and has additional offices in Evergem, Belgium and Vancouver, Canada. It develops gyroscopic pipeline mapping systems for utility infrastructure like gas, water and telecommunications pipelines. The systems contain inertial sensors like gyroscopes and accelerometers that are calibrated to align with the pipe. As the system is moved through the pipe, it records location data along with bend radius, weld locations and offsets. The output data can be used for GIS mapping, pre-commissioning compliance, and defect detection. The systems are applicable to pipes ranging in size from 32mm to 800mm in diameter and made from materials like HDPE, steel and concrete. Recent projects
Synthetic Aperture Radar (SAR) uses signal processing techniques to synthesize a large antenna from data collected by a physically small antenna as it moves along a flight path. This allows SAR to achieve high-resolution images independent of altitude. SAR transmits microwave pulses and analyzes the returned echoes to build up images of the terrain. SAR has various applications including topographic mapping and measuring ocean waves, currents, and wind. Ocean backscatter measured by SAR is influenced by surface roughness driven by factors like wind as well as hydrodynamic effects of waves and currents.
У рамках програми «Підвищення кваліфікації фахівців нафтогазової галузі України для міжнародного співробітництва та роботи у західних компаніях», за підтримки компанії «Shell» 6 березня в аудиторії ВНЗ «Інститут Тутковського» відбулися курси підвищення кваліфікації на тему «Від побудови сейсмічних зображень до інверсії».
1) Techniques are presented for accurately geolocating radar data from the TerraSAR-X and TanDEM-X satellites. Effects from the ionosphere, water vapor, tides, and continental drift must be accounted for.
2) Measurements of corner reflectors were used to evaluate absolute and relative localization accuracy. Accounting for all effects improved absolute accuracy to just a few centimeters for TerraSAR-X.
3) The relative accuracy between TanDEM-X images was sub-centimeter in range, demonstrating the capability for highly precise digital elevation models.
The document proposes an improved method for audio signal separation using supervised nonnegative matrix factorization (NMF) with time-variant basis deformation. The key contributions are:
1. Classifying supervised bases into time-variant attack and sustain parts and applying different all-pole model-based deformations to each.
2. Introducing discriminative training to avoid overfitting the interference signal and better separate the target.
3. An iterative approximated algorithm is presented that searches for deformation matrices representing the target signal while being constrained to also fit the mixture signal.
4. Experimental results on instrument mixtures show the proposed method achieves better signal-to-distortion ratio performance than previous supervised NMF techniques.
IAA-LA2-10-01 Spectral and Radiometric Calibration Procedure for a SWIR Hyper...Christian Gabriel Gomez
Presentación para 2nd IAA Latin American Symposium on Small Satellites.
Procedimiento de calibración espectral y radiométrica de una cámara hiperespectral SWIR.
Wise Sliding Window Segmentation: A classification-aided approach for traject...Mohammad Etemad
Large amounts of mobility data are being generated from many different sources, and several data mining methods have been proposed for this data. One of the most critical steps for trajectory data mining is segmentation.
This task can be seen as a pre-processing step in which a trajectory is divided into several meaningful consecutive sub-sequences. This process is necessary because trajectory patterns may not hold in the entire trajectory but on trajectory parts.
In this work we propose a supervised trajectory segmentation algorithm, called Wise Sliding Window Segmentation (WS-II).
It processes the trajectory coordinates to find behavioral changes in space and time, generating an error signal that is further used to train a binary classifier for segmenting trajectory data.
This algorithm is flexible and can be used in different domains. We evaluate our method over three real datasets from different domains (meteorology, fishing, and individuals movements), and compare it with four other trajectory segmentation algorithms: OWS, GRASP-UTS, CB-SMoT, and SPD.
We observed that the proposed algorithm achieves the highest performance for all datasets with statistically significant differences in terms of the harmonic mean of purity and coverage.
Synthetic aperture radar (SAR) uses the motion of the radar platform to synthesize a large antenna aperture, providing very high cross-range resolution. It collects returns sequentially and processes them as if collected simultaneously. Inverse SAR uses target motion instead of platform motion, allowing imaging of moving objects like ships. Both techniques overcome limitations of conventional radar to generate high-resolution radar images of terrain and targets.
The document presents SURF (Speeded Up Robust Features), a novel scale- and rotation-invariant detector and descriptor. SURF uses a fast-Hessian detector based on the Hessian matrix and DoG approximations. It assigns orientations based on Haar wavelet responses and extracts 64-dimensional descriptors from summed Haar wavelet responses. SURF matches features based on sign of the Laplacian for fast indexing. Experiments show SURF outperforms other methods in repeatability, distinctiveness and robustness while computing faster.
Bandpass modulation schemes transmit data by varying the amplitude, phase, or frequency of a carrier signal. Common schemes include M-PAM, M-PSK, M-FSK, and M-QAM. At the receiver, data is detected through either coherent or non-coherent detection. Coherent detection uses carrier phase estimation while non-coherent does not. The average probability of symbol error is calculated for each modulation scheme and used to compare their performance.
MO4.L09 - POTENTIAL AND LIMITATIONS OF FORWARD-LOOKING BISTATIC SARgrssieee
This document discusses the potential and limitations of forward-looking bistatic synthetic aperture radar (SAR). It describes the bistatic geometry and iso-range and iso-Doppler contours in the bistatic case. It also details an experiment using TerraSAR-X and PAMIR SAR to image in the forward and backward directions and demonstrates the feasibility of bistatic forward-looking SAR. Resolution analysis and experimental results showing raw data, range compressed data, and comparison to optical images are also presented.
TH2.L09.4 - CHARACTERISTIC ANALYSIS OF VEHICLE TARGET IN QUAD-POL RADARSAT-2...grssieee
1) The document analyzes the characteristic backscattering properties of vehicle targets in quad-polarimetric Radarsat-2 SAR images.
2) Experiments at different incidence angles and azimuth angles found significant differences in the radar cross section and polarization components of vehicle targets.
3) Polarization decomposition analysis showed double bounce scattering is an important characteristic for detecting trucks on roads, and vehicles are best detected when oriented parallel to the SAR flight direction.
TH2.L09.4 - CHARACTERISTIC ANALYSIS OF VEHICLE TARGET IN QUAD-POL RADARSAT-2...grssieee
This document analyzes the characteristic analysis of vehicle targets in quad-polarized Radarsat-2 SAR images. It discusses experiments analyzing differences in backscatter based on incidence angle, azimuth angle, and truck configuration. The results show incidence angle has the largest impact on backscatter characteristics. Polarization decomposition helps verify target characteristics, with double bounce being important for trucks. Vehicles are best detected when parallel to the SAR flight direction. Prior geographic constraints can aid vehicle detection on roads in SAR imagery.
This document outlines an approach for detecting body-worn explosives using radar. It describes modeling the detection system using FDFD and simulating different configurations. An experiment is described that uses a scanning beam radar module to obtain range profiles of targets at various positions and orientations. The signal processing methods are discussed, including using limited views of the target and an ellipse fitting algorithm to classify targets as threats or non-threats based on their time response characteristics. The results show multiple ISAR image features can distinguish threats, and the ellipse algorithm was successful in most cases. Improving the aperture size and reducing phase noise could enhance the resolution and performance of the system.
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1. Blind Azimuth Phase
Elimination for TerraSAR-X
ScanSAR Interferometry
Alex Zhe Hu, Linlin Ge and Xiaojing Li
Geodesy and Earth Observing Systems Group (GEOS),
School of Surveying and Spatial Information Systems,
The University of New South Wales, Sydney, Australia
Email: z.hu@student.unsw.edu.au
7. Introduction
• ScanSAR Interferometry
ALOS EnviSAT
RADARSAT TerraSAR-X
PALSAR ASAR
L-band C-band C-band X-band
250–350km 400km 300–500km 150km
100m 75–150m 50–100m up to 16m
Ortiz and Holzner and
Shimada 2007 ?
Zebker 2007 Bamler 2002
8. Introduction
• TerraSAR-X ScanSAR Interferometry
– Distortion and signal loss in azimuth direction
after resampling
– Only SLC data available for the public
9. Introduction
• TerraSAR-X ScanSAR Interferometry
– Distortion and signal loss in azimuth direction
after resampling
– Only SLC data available for the public
– Blind Azimuth Phase Elimination
12. Methodology
• Brief workflow
Determination of the
Compensation Factor
Coarse Initialisation of
the Key Parameter
Refining of
the Key Parameter
Elimination of
the Azimuth Phase
13. Methodology
• Determination of the Compensation Factor
Sensor Sensor Sensor Sensor
Moving Moving
Direction Direction
Synthetic Burst
(Azimuth) (Azimuth)
Aperture Time
Target Target
Stripmap ScanSAR
⎛ τ −τ 0 ⎞ ⎛ τ − Tc ⎞
s strip (τ ) = exp ⎡ jπ f dm (τ − τ 0 ) ⎤ ⋅ w ⎜ sscan (τ ) = exp ⎡ jπ f dm (τ − τ 0 ) ⎤ ⋅ rect ⎜
2 2
⎣ ⎦ ⎝ T ⎟ ⎣ ⎦ ⎟
⎠ ⎝ Tb ⎠
24. Results and Discussions
Information Master Image Slave Image
Acquisition Date 16 February 2010 27 February 2010
Acquisition Start
02:56:12 (UTC) 02:56:13 (UTC)
Time
Acquisition Stop
02:56:30 (UTC) 02:56:31 (UTC)
Time
Number of
4 (strip_04 – strip_07)
Swathes
Number of Bursts 59 (strip_04 – strip_07) 61 (strip_04 – strip_07)
Central Latitude 28.785 ° 28.785 °
Central Longitude 47.514 ° 47.513°
Range Resolution 2.504 (metre) 2.503 (metre)
Azimuth
18.5 (metre) 18.5 (metre)
Resolution
33. Concluding Remarks
• Simplifying the TerraSAR-X ScanSAR
interferometry by making it Stripmap-like
• Precise enough to remove the non-linear
azimuth phases
• Providing a solution for TerraSAR-X
ScanSAR interferometry starts from SLC
data
• Can also be applied to other advanced
SAR system with non-linear azimuth
phases, such as Spotlight
34. Acknowledgement:
The authors are grateful to Infoterra for providing the
TerraSAR-X ScanSAR dataset on this research.
The first author also sincerely thanks GEOS and the Faculty of
Engineering of UNSW for supporting his scholarship on his PhD
study.