Engineering Commons^™

A Comparative Study Of Vinti-Based Orbit Propagation And Estimation For Cubesats In Very Low Earth Orbits, Ethan Michael Senecal

Mechanical & Aerospace Engineering Theses & Dissertations

In recent years, there has been a growing interest in CubeSats and very low Earth orbit (VLEO) space missions. Mission SeaLion, a collaborative CubeSat mission between Old Dominion University, the U.S. Coast Guard Academy, and U.S. Air Force Institute of Technology, planned to launch a 3U CubeSat into VLEO. The VLEO mission is a particularly challenging environment for navigation and orbit propagation because drag introduces a significant perturbation for orbit models such as SGP4. Additionally, mission requirements left no capacity for attitude determination or control, further reducing knowledge of drag behavior of the satellite in flight. This deficiency is a …

Lidar Buoy Detection For Autonomous Marine Vessel Using Pointnet Classification, Christopher Adolphi, Dorothy Dorie Parry, Yaohang Li, Masha Sosonkina, Ahmet Saglam, Yiannis E. Papelis

Modeling, Simulation and Visualization Student Capstone Conference

Maritime autonomy, specifically the use of autonomous and semi-autonomous maritime vessels, is a key enabling technology supporting a set of diverse and critical research areas, including coastal and environmental resilience, assessment of waterway health, ecosystem/asset monitoring and maritime port security. Critical to the safe, efficient and reliable operation of an autonomous maritime vessel is its ability to perceive on-the-fly the external environment through onboard sensors. In this paper, buoy detection for LiDAR images is explored by using several tools and techniques: machine learning methods, Unity Game Engine (herein referred to as Unity) simulation, and traditional image processing. The Unity Game …

Impact Of Atmospheric Correction On Classification And Quantification Of Seagrass Density From Worldview-2 Imagery, Victoria J. Hill, Richard C. Zimmerman, Paul Bissett, David Kohler, Blake Schaeffer, Megan Coffer, Jiang Li, Kazi Aminul Islam

OES Faculty Publications

Mapping the seagrass distribution and density in the underwater landscape can improve global Blue Carbon estimates. However, atmospheric absorption and scattering introduce errors in space-based sensors’ retrieval of sea surface reflectance, affecting seagrass presence, density, and above-ground carbon (AGC_seagrass) estimates. This study assessed atmospheric correction’s impact on mapping seagrass using WorldView-2 satellite imagery from Saint Joseph Bay, Saint George Sound, and Keaton Beach in Florida, USA. Coincident in situ measurements of water-leaving radiance (L_w), optical properties, and seagrass leaf area index (LAI) were collected. Seagrass classification and the retrieval of LAI were compared after empirical line …

Arithfusion: An Arithmetic Deep Model For Temporal Remote Sensing Image Fusion, Md Reshad Ul Hoque, Jian Wu, Chiman Kwan, Krzysztof Koperski, Jiang Li

Electrical & Computer Engineering Faculty Publications

Different satellite images may consist of variable numbers of channels which have different resolutions, and each satellite has a unique revisit period. For example, the Landsat-8 satellite images have 30 m resolution in their multispectral channels, the Sentinel-2 satellite images have 10 m resolution in the pan-sharp channel, and the National Agriculture Imagery Program (NAIP) aerial images have 1 m resolution. In this study, we propose a simple yet effective arithmetic deep model for multimodal temporal remote sensing image fusion. The proposed model takes both low- and high-resolution remote sensing images at t₁ together with low-resolution images at a …

Statistical Analysis And Comparison Of Optical Classification Of Atmospheric Aerosol Lidar Data, Mohammed Alqawba, Norou Diawara, Kwasi G. Afrifa, Mohamed I. Elbakary, Mecit Cetin, Khan Iftekharuddin

Mathematics & Statistics Faculty Publications

In this article, we present 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 consider appropriate calibration and estimation accuracy. Consequently, two statistical methods based on generalized linear …

Deep Learning For Remote Sensing Image Processing, Yan Lu

Computational Modeling & Simulation Engineering Theses & Dissertations

Remote sensing images have many applications such as ground object detection, environmental change monitoring, urban growth monitoring and natural disaster damage assessment. As of 2019, there were roughly 700 satellites listing “earth observation” as their primary application. Both spatial and temporal resolutions of satellite images have improved consistently in recent years and provided opportunities in resolving fine details on the Earth's surface. In the past decade, deep learning techniques have revolutionized many applications in the field of computer vision but have not fully been explored in remote sensing image processing. In this dissertation, several state-of-the-art deep learning models have been …

Fpga-Based On-Board Geometric Calibration For Linear Ccd Array Sensors, Guoqing Zhou, Linjun Jiang, Jingjin Huang, Rongting Zhang, Dequan Liu, Xiang Zhou, Oktay Baysal

Mechanical & Aerospace Engineering Faculty Publications

With increasing demands in real-time or near real-time remotely sensed imagery applications in such as military deployments, quick response to terrorist attacks and disaster rescue, the on-board geometric calibration problem has attracted the attention of many scientists in recent years. This paper presents an on-board geometric calibration method for linear CCD sensor arrays using FPGA chips. The proposed method mainly consists of four modules—Input Data, Coefficient Calculation, Adjustment Computation and Comparison—in which the parallel computations for building the observation equations and least squares adjustment, are implemented using FPGA chips, for which a decomposed matrix inversion method is presented. A Xilinx …

Assessment Of Spatiotemporal Fusion Algorithms For Planet And Worldview Images, Chiman Kwan, Xiaolin Zhu, Feng Gao, Bryan Chou, Daniel Perez, Jinag Li, Yuzhong Shen, Krzysztof Koperski, Giovanni Marchisio

Electrical & Computer Engineering Faculty Publications

Although Worldview-2 (WV) images (non-pansharpened) have 2-m resolution, the re-visit times for the same areas may be seven days or more. In contrast, Planet images are collected using small satellites that can cover the whole Earth almost daily. However, the resolution of Planet images is 3.125 m. It would be ideal to fuse these two satellites images to generate high spatial resolution (2 m) and high temporal resolution (1 or 2 days) images for applications such as damage assessment, border monitoring, etc. that require quick decisions. In this paper, we evaluate three approaches to fusing Worldview (WV) and Planet images. …

Sparse Coding Based Feature Representation Method For Remote Sensing Images, Ender Oguslu

Electrical & Computer Engineering Theses & Dissertations

In this dissertation, we study sparse coding based feature representation method for the classification of multispectral and hyperspectral images (HSI). The existing feature representation systems based on the sparse signal model are computationally expensive, requiring to solve a convex optimization problem to learn a dictionary. A sparse coding feature representation framework for the classification of HSI is presented that alleviates the complexity of sparse coding through sub-band construction, dictionary learning, and encoding steps. In the framework, we construct the dictionary based upon the extracted sub-bands from the spectral representation of a pixel. In the encoding step, we utilize a soft …

Sparse Coding Based Dense Feature Representation Model For Hyperspectral Image Classification, Ender Oguslu, Guoqing Zhou, Zezhong Zheng, Khan Iftekharuddin, Jiang Li

Electrical & Computer Engineering Faculty Publications

We present a sparse coding based dense feature representation model (a preliminary version of the paper was presented at the SPIE Remote Sensing Conference, Dresden, Germany, 2013) for hyperspectral image (HSI) classification. The proposed method learns a new representation for each pixel in HSI through the following four steps: sub-band construction, dictionary learning, encoding, and feature selection. The new representation usually has a very high dimensionality requiring a large amount of computational resources. We applied the l₁/l_q regularized multiclass logistic regression technique to reduce the size of the new representation. We integrated the method with a linear …

Hyperspectral Image Classification Using A Spectral-Spatial Sparse Coding Model, Ender Oguslu, Guoqing Zhou, Jiang Li, Lorenzo Bruzzone (Ed.)

Electrical & Computer Engineering Faculty Publications

We present a sparse coding based spectral-spatial classification model for hyperspectral image (HSI) datasets. The proposed method consists of an efficient sparse coding method in which the l₁/l_q regularized multi-class logistic regression technique was utilized to achieve a compact representation of hyperspectral image pixels for land cover classification. We applied the proposed algorithm to a HSI dataset collected at the Kennedy Space Center and compared our algorithm to a recently proposed method, Gaussian process maximum likelihood (GP-ML) classifier. Experimental results show that the proposed method can achieve significantly better performances than the GP-ML classifier when training data …

Sensitive Detection Of Novel Effects And Characteristic Signal Structure Of Higher Harmonic Detection In Wavelength Modulation Spectroscopy, Mohammad Amir Khan

Electrical & Computer Engineering Theses & Dissertations

We discuss experimental and theoretical results of absorption features of the oxygen A-band transitions when synchronous detection at higher harmonics using Wavelength Modulation Spectroscopy (WMS) is performed. A key aspect of structure higher harmonic detection is discussed. It is shown that the signal magnitude and spectral locations of turning points and zero crossings of WMS signal demonstrate key signatures of collision dynamics of gaseous specie parameters and lineshape parameters. In addition, it is also shown that these salient features provide sensitive probes for any changes in the gas environment or lineshape parameters. We discuss several advantages and subtle physical effects …

Vegetation Identification Based On Satellite Imagery, Vamsi K.R. Mantena, Ramu Pedada, Srinivas Jakkula, Yuzhong Shen, Jiang Li, Hamid R. Arabnia (Ed.)

Electrical & Computer Engineering Faculty Publications

Automatic vegetation identification plays an important role in many applications including remote sensing and high performance flight simulations. This paper presents a method to automatically identify vegetation based upon satellite imagery. First, we utilize the ISODATA algorithm to cluster pixels in the images where the number of clusters is determined by the algorithm. We then apply morphological operations to the clustered images to smooth the boundaries between clusters and to fill holes inside clusters. After that, we compute six features for each cluster. These six features then go through a feature selection algorithm and three of them are determined to …

Seasonal Adaptation Of Vegetation Color In Satellite Images, Srinivas Jakkula, Vamsi K.R. Mantena, Ramu Pedada, Yuzhong Shen, Jiang Li, Hamid R. Arabnia (Ed.)

Electrical & Computer Engineering Faculty Publications

Remote sensing techniques like NDVI (Normal Difference vegetative Index) when applied to phenological variations in aerial images, ascertained the seasonal rise and decline of photosynthetic activity in different seasons, resulting in different color tones of vegetation. The rise and fall of NDVI values decide the biological response, either the green up or brown down [1]. Vegetation in green up period appears with more vegetative vigor and during brown down period it has a dry appearance. This paper proposes a novel method that identifies vegetative patterns in satellite images and then alters vegetation color to simulate seasonal changes based on training …

Inversion And Analysis Of Remotely Sensed Atmospheric Water Vapor Measurements At 940nm, Jack Cutler Larsen

Mechanical & Aerospace Engineering Theses & Dissertations

The understanding and acceptance of remotely sensed atmospheric data depends strongly on the steps taken to characterize experiment error and validate observations through comparisons to other independent measurements. A formal error analysis of the Stratospheric Aerosol and Gas Experiment II (SAGE II) water vapor operational inversion algorithm is performed and compared to previous results. Random measurement errors were characterized by segmented least-squares profile fitting of the slant path absorption which found the error to be uncorrelated in the stratosphere with estimated variances significantly smaller than expected from 18-30 km. Estimates of null space error were developed from radiosonde hygrometers in …

A Total Systems Analysis Method For The Conceptual Design Of Spacecraft: An Application To Remote Sensing Imager Systems, Knut I. Oxnevad

Engineering Management & Systems Engineering Theses & Dissertations

Increased emphasis is being placed on improving the performance of space projects, within tighter budgets and shorter development times. This has led to a need for more efficient space system design methods. The research described here represents an effort to develop and evaluate such a method.

Systems engineering and concurrent engineering together provide the theoretical foundation for the method. The method, derived from both this theoretical foundation and ideas from experts in the space industry, emphasizes a total systems analysis approach, taking into account given mission requirements, and the mathematical modeling of interactions between system variables and between subsystems. The …

Integrated Control Of Thermally Distorted Large Space Antennas, Robert H. Tolson

Mechanical & Aerospace Engineering Theses & Dissertations

Studies on controlling the thermal distortion of large space antennae have generally investigated a single orbital position and have optimized actuator locations based on minimizing the RMS surface deviation from the original parabolic shape. One study showed the benefits of directly using far zone electric field characteristics as the performance measure; but, this approach resulted in a nonlinear programming problem. The objective of the current study is to develop an approach to designing a control system that (1) recognizes the time dependence of the distortion and (2) controls variables that are directly related to far field performance in a quadratic …

Usage And Limitations Of Characteristic Vector Analysis Of Remote Sensing Multispectral Data For The Identification And Quantification Of Water Quality Parameters, Theodore A. Talay

Civil & Environmental Engineering Theses & Dissertations

Recent applications of the technique of characteristic vector analysis to remote-sensing water color data has met with varying degrees of success. It is apparent from these experiments that a more thorough understanding of the informational capability of characteristic vector analysis is needed.

The Development Of A Stepped Frequency Microwave Radiometer And Its Application To Remote Sensing Of The Earth, Richard Forrest Harrington

Electrical & Computer Engineering Theses & Dissertations

The design, development, application, and capabilities of a variable frequency microwave radiometer are described. This radiometer has demonstrated the versatility, accuracy, and stability required to provide contributions to the geophysical understanding of ocean and ice processes. The design technique utilized a closed-loop feedback method, whereby noise pulses were added to the received electromagnetic radiation to achieve a null balance in a Dicke switched radiometer. Stability was achieved through the use of a constant temperature enclosure around the low loss microwave front end. The Dicke reference temperature was maintained to an absolute accuracy of 0.1 K using a closed-loop proportional temperature …