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- Remote sensing (7)
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- Polarimetric remote sensing--Statistical methods (1)
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Articles 1 - 14 of 14
Full-Text Articles in Engineering
Composite Style Pixel And Point Convolution-Based Deep Fusion Neural Network Architecture For The Semantic Segmentation Of Hyperspectral And Lidar Data, Kevin T. Decker, Brett J. Borghetti
Composite Style Pixel And Point Convolution-Based Deep Fusion Neural Network Architecture For The Semantic Segmentation Of Hyperspectral And Lidar Data, Kevin T. Decker, Brett J. Borghetti
Faculty Publications
Multimodal hyperspectral and lidar data sets provide complementary spectral and structural data. Joint processing and exploitation to produce semantically labeled pixel maps through semantic segmentation has proven useful for a variety of decision tasks. In this work, we identify two areas of improvement over previous approaches and present a proof of concept network implementing these improvements. First, rather than using a late fusion style architecture as in prior work, our approach implements a composite style fusion architecture to allow for the simultaneous generation of multimodal features and the learning of fused features during encoding. Second, our approach processes the higher …
A Comparison Of Sporadic-E Occurrence Rates Using Gps Radio Occultation And Ionosonde Measurements, Rodney Carmona, Omar A. Nava, Eugene V. Dao, Daniel J. Emmons
A Comparison Of Sporadic-E Occurrence Rates Using Gps Radio Occultation And Ionosonde Measurements, Rodney Carmona, Omar A. Nava, Eugene V. Dao, Daniel J. Emmons
Faculty Publications
Sporadic-E (Es) occurrence rates from Global Position Satellite radio occultation (GPS-RO) measurements have shown to vary by a factor of five between studies, motivating the need for a comparison with ground-based measurements. In an attempt to find accurate GPS-RO techniques for detecting Es formation, occurrence rates derived using five previously developed GPS-RO techniques are compared to ionosonde measurements over an eight-year period from 2010–2017. GPS-RO measurements within 170 km of a ionosonde site are used to calculate Es occurrence rates and compared to the ground-truth ionosonde measurements. The techniques are compared individually for each ionosonde site …
Machine Learning Land Cover And Land Use Classification Of 4-Band Satellite Imagery, Lorelei Turner [*], Torrey J. Wagner, Paul Auclair, Brent T. Langhals
Machine Learning Land Cover And Land Use Classification Of 4-Band Satellite Imagery, Lorelei Turner [*], Torrey J. Wagner, Paul Auclair, Brent T. Langhals
Faculty Publications
Land-cover and land-use classification generates categories of terrestrial features, such as water or trees, which can be used to track how land is used. This work applies classical, ensemble and neural network machine learning algorithms to a multispectral remote sensing dataset containing 405,000 28x28 pixel image patches in 4 electromagnetic frequency bands. For each algorithm, model metrics and prediction execution time were evaluated, resulting in two families of models; fast and precise. The prediction time for an 81,000-patch group of predictions wasmodels, and >5s for the precise models, and there was not a significant change in prediction time when a …
Learning Set Representations For Lwir In-Scene Atmospheric Compensation, Nicholas M. Westing [*], Kevin C. Gross, Brett J. Borghetti, Jacob A. Martin, Joseph Meola
Learning Set Representations For Lwir In-Scene Atmospheric Compensation, Nicholas M. Westing [*], Kevin C. Gross, Brett J. Borghetti, Jacob A. Martin, Joseph Meola
Faculty Publications
Atmospheric compensation of long-wave infrared (LWIR) hyperspectral imagery is investigated in this article using set representations learned by a neural network. This approach relies on synthetic at-sensor radiance data derived from collected radiosondes and a diverse database of measured emissivity spectra sampled at a range of surface temperatures. The network loss function relies on LWIR radiative transfer equations to update model parameters. Atmospheric predictions are made on a set of diverse pixels extracted from the scene, without knowledge of blackbody pixels or pixel temperatures. The network architecture utilizes permutation-invariant layers to predict a set representation, similar to the work performed …
Multi-Sensor Data Fusion Between Radio Tomographic Imaging And Noise Radar, Christopher Vergara
Multi-Sensor Data Fusion Between Radio Tomographic Imaging And Noise Radar, Christopher Vergara
Theses and Dissertations
The lack of situational awareness within an operational environment is a problem that carries high risk and expensive consequences. Radio Tomographic Imaging (RTI) and noise radar are two proven technologies capable of through-wall imaging and foliage penetration. The intent of this thesis is to provide a proof of concept for the fusion of data from RTI and noise radar. The output of this thesis will consist of a performance comparison between the two technologies followed by the derivation of a fusion technique to produce a single image. Proposals have been made for the integration of multiple-input multiple-output (MIMO) radar with …
Remote Sensing Of Hidden Objects, Mark G. Hoelscher, Michael A. Marciniak
Remote Sensing Of Hidden Objects, Mark G. Hoelscher, Michael A. Marciniak
AFIT Patents
An apparatus and method are provided for creating an indirect image of an object. The apparatus includes a light source and an imaging system. Light emitted from the light source is reflected by a first non-specular surface toward the object. Light reflected by the object is further reflected by a second non-specular surface toward the imaging system. The imaging system is configured to create the indirect image from the reflected light.
Design Of A Monocular Multi-Spectral Skin Detection, Melanin Estimation, And False-Alarm Suppression System, Keith R. Peskosky
Design Of A Monocular Multi-Spectral Skin Detection, Melanin Estimation, And False-Alarm Suppression System, Keith R. Peskosky
Theses and Dissertations
A real-time skin detection, false-alarm reduction, and melanin estimation system is designed targeting search and rescue (SAR) with application to special operations for manhunting and human measurement and signatures intelligence. A mathematical model of the system is developed and used to determine how the physical system performs under illumination, target-to-sensor distance, and target-type scenarios. This aspect is important to the SAR community to gain an understanding of the deployability in different operating environments. A multi-spectral approach is developed and consists of two short-wave infrared cameras and two visible cameras. Through an optical chain of lenses, custom designed and fabricated dichroic …
Using Multiple Robust Parameter Design Techniques To Improve Hyperspectral Anomaly Detection Algorithm Performance, Matthew T. Davis
Using Multiple Robust Parameter Design Techniques To Improve Hyperspectral Anomaly Detection Algorithm Performance, Matthew T. Davis
Theses and Dissertations
Detecting and identifying objects of interest is the goal of all remote sensing. New advances, specifically in hyperspectral imaging technology have provided the analyst with immense amounts of data requiring evaluation. Several filtering techniques or anomaly detection algorithms have been proposed. However, most new algorithms are insufficiently verified to be robust to the broad range of hyperspectral data being made available. One such algorithm, AutoGAD, is tested here via two separate robust parameter design techniques to determine optimal parameters for consistent performance on a range of data with large attribute variances. Additionally, the results of the two techniques are compared …
Statistical Methods For Polarimetric Imagery, Daniel A. Lemaster
Statistical Methods For Polarimetric Imagery, Daniel A. Lemaster
Theses and Dissertations
Estimation theory is applied to a physical model of incoherent polarized light to address problems in polarimetric image registration, restoration, and analysis for electro-optical imaging systems. In the image registration case, the Cramer-Rao lower bound on unbiased joint estimates of the registration parameters and the underlying scene is derived, simplified using matrix methods, and used to explain the behavior of multi-channel linear polarimetric imagers. In the image restoration case, a polarimetric maximum likelihood blind deconvolution algorithm is derived and tested using laboratory and simulated imagery. Finally, a principal components analysis is derived for polarization imaging systems. This analysis expands upon …
Dynamics And Control Of Tethered Satellite Formations For The Purpose Of Space-Based Remote Sensing, Kurt A. Vogel
Dynamics And Control Of Tethered Satellite Formations For The Purpose Of Space-Based Remote Sensing, Kurt A. Vogel
Theses and Dissertations
This dissertation assesses the utility of tethered satellite formations for the space-based remote sensing mission. Energy dissipation is found to have an adverse effect on foundational rigid body (Likins-Pringle) equilibria. It is shown that a continuously earth-facing equilibrium condition for a fixed-length tethered system does not exist since the spin rate required for the proper precession would not be high enough to maintain tether tension. The range of required spin rates for steady-spin motion is numerically defined here, but none of these conditions can meet the continuously earth-facing criteria. Of particular note is the discovery that applying certain rigid body …
Terrain And Spatial Effects On Hazard Prediction And Assessment Capability (Hpac) Software Dose-Rate Contour Plot Predictions As Compared To A Sample Of Local Fallout Data From Test Detonations In The Continental United States, 1945-1962, Kevin D. Pace
Theses and Dissertations
Hazard Prediction and Capability (HPAC) Software is validated by comparing modeled predictions to historical test data. Reanalysis weather data is acquired and reformatted for use in HPAC. Simulations are made using various amounts of weather data by use of a spatial domain. Simulations are also varied by levels of terrain resolution. The predicted output of the software is numerically compared to historical test data. The result of this research culminated in the knowledge that HPAC prediction accuracy is improved by using terrain resolutions beyond the flat earth assumption. Furthermore, this research establishes that domain size variation produces no significant advantage …
Modeling And Simulation Of Commercial Satellite Imagery Processes, David A. Shultz
Modeling And Simulation Of Commercial Satellite Imagery Processes, David A. Shultz
Theses and Dissertations
The purpose of this research was to develop a general, statistical model of order-to-delivery times for commercial satellite imagery. The research looked at the current four satellite providers with 3-meter or better imagers in the context of a generalized model of commercial imaging satellite operations. Existing methods use orbit analysis tools to determine the imaging time of a specified target based on defined satellite position and times, but can only develop shortest and longest times to an imaging opportunity. To address the general question of the time it takes to deliver an image for non-specific targets, this research develops a …
Simulating A Chromotomographic Sensor For Hyperspectral Imaging In The Infrared, Anthony J. Dearinger
Simulating A Chromotomographic Sensor For Hyperspectral Imaging In The Infrared, Anthony J. Dearinger
Theses and Dissertations
Hyperspectral imaging systems passively sense radiant electromagnetic energy from a remote scene to form a three dimension profile of the remote scene. The data contained in this profile describes real images of the remote scene for a certain number of spectral wavelength bands across a finite spectral range of electromagnetic radiation. Typical grating type hyperspectral imaging systems collect spectral electromagnetic radiation in the visible and near infrared spectral range, by incrementally scanning across the spatial extent of the remote scene. The legacy of low optical throughput because of the optical scanning techniques employed in these systems means adapting these systems …
Commercial Regional Space/Airborne Imaging, Ugur Akyazi, Ali Durmus, Birce Boga Bakirli, Arif Arin
Commercial Regional Space/Airborne Imaging, Ugur Akyazi, Ali Durmus, Birce Boga Bakirli, Arif Arin
Theses and Dissertations
In this work goal programming is used to solve a minimum cost multicommodity network flow problem with multiple goals. A single telecommunication network with multiple commodities (e.g., voice, video, data, etc.) flowing over it is analyzed. This network consists of: linear objective function, linear cost arcs, fixed capacities, specific origin-destination pairs for each commodity. A multicommodity network flow problem with goals can be successfully modeled using linear goal programming techniques. When properly modeled, network flow techniques may be employed to exploit the pure network structure of a multicommodity network flow problem with goals. Lagrangian relaxation captures the essence of the …