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Full-Text Articles in Engineering
Improving Detection Of Dim Targets: Optimization Of A Moment-Based Detection Algorithm, Shannon R. Young
Improving Detection Of Dim Targets: Optimization Of A Moment-Based Detection Algorithm, Shannon R. Young
Theses and Dissertations
Wide area motion imagery (WAMI) sensor technology is advancing rapidly. Increases in frame rates and detector array sizes have led to a dramatic increase in the volume of data that can be acquired. Without a corresponding increase in analytical manpower, much of these data remain underutilized. This creates a need for fast, automated, and robust methods for detecting dim, moving signals of interest. Current approaches fall into two categories: detect-before-track (DBT) and track-before-detect (TBD) methods. The DBT methods use thresholding to reduce the quantity of data to be processed, making real time implementation practical but at the cost of the …
Remote Sensing Using I-Band And S-Band Signals Of Opportunity, Kadir Efecik, Benjamin R. Nold, James L. Garrison
Remote Sensing Using I-Band And S-Band Signals Of Opportunity, Kadir Efecik, Benjamin R. Nold, James L. Garrison
The Summer Undergraduate Research Fellowship (SURF) Symposium
Measurement of soil moisture, especially the root zone soil moisture, is important in agriculture, meteorology, and hydrology. Root zone soil moisture is concerned with the first meter down the soil. Active and passive remote sensing methods used today utilizing L-band(1-2GHz) are physically limited to a sensing depth of about 5 cm or less. To remotely sense the soil moisture in the deeper parts of the soil, the frequency should be lowered. Lower frequencies cannot be used in active spaceborne instruments because of their need for larger antennas, radio frequency interference (RFI), and frequency spectrum allocations. Ground-based passive remote sensing using …
Statistical Analysis And Comparison Of Optical Classification Of Atmospheric Aerosol Lidar Data, Kwasi Gyening Afrifa
Statistical Analysis And Comparison Of Optical Classification Of Atmospheric Aerosol Lidar Data, Kwasi Gyening Afrifa
Electrical & Computer Engineering Projects for D. Eng. Degree
This dissertation presents a new study for the analysis and classification of atmospheric aerosols in remote sensing LIDAR data. Information on particle size and associated properties are extracted from these remote sensing atmospheric data which are collected by a ground-based LIDAR system. This study first considers optical LIDAR parameter-based classification methods for clustering and classification of different types of harmful aerosol particles in the atmosphere. Since accurate methods for aerosol prediction behaviors are based upon observed data, computational approaches must overcome design limitations, and also consider appropriate calibration and estimation accuracy. Consequently, two statistical methods based on generalized linear models …
Sar Image Time-Series Analysis Framework Using Morphological Operators And Global And Local Information-Based Linear Discriminant Analysis, Ufuk Sakarya, Caner Demi̇rpolat
Sar Image Time-Series Analysis Framework Using Morphological Operators And Global And Local Information-Based Linear Discriminant Analysis, Ufuk Sakarya, Caner Demi̇rpolat
Turkish Journal of Electrical Engineering and Computer Sciences
Fusion of spectral, spatial, and temporal information is an effective method used in many satellite remote sensing applications. On the other hand, one drawback of this fusion is an increase in complexity. In this paper, we focus on developing a fast and well-performed classification method for agricultural crops using time-series SAR data. In order to achieve this, a novel two-stage approach is proposed. In the first stage, a high-dimensional feature space is obtained using time-series dual-pol SAR data and morphological operators. Spectral, spatial, and temporal information is combined into a single high-dimensional feature space. In the second stage, a dimension …
Cross Calibration And Validation Of Landsat 8 Oli And Sentinel 2a Msi, M. M. Farhad
Cross Calibration And Validation Of Landsat 8 Oli And Sentinel 2a Msi, M. M. Farhad
Electronic Theses and Dissertations
This work describes a proposed radiometric cross calibration between the Landsat 8 Operational Land Imager (OLI) and Sentinel 2A Multispectral Instrument (MSI) sensors. The cross calibration procedure involves i) correction of the MSI data to account for spectral band differences with the OLI; and ii) correction of BRDF effects in the data from both sensors using a new model accounting for the view zenith/azimuth angles in addition to the solar zenith/view angles. Following application of the spectral and BRDF corrections, standard least-squares linear regression is used to determine the cross calibration gain and offset in each band. Uncertainties related to …