Signal Processing Commons^™

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 …

End-To-End Deep Learning Systems For Scene Understanding, Path Planning And Navigation In Fire Fighter Teams, Manish Bhattarai

Shared Knowledge Conference

Firefighting is a dynamic activity with many operations occurring simultaneously. Maintaining situational awareness, defined as knowledge of current conditions and activities at the scene, are critical to accurate decision making. Firefighters often carry various sensors in their personal equipment, namely thermal cameras, gas sensors, and microphones. Improved data processing techniques can mine this data more effectively and be used to improve situational awareness at all times thereby improving real-time decision making and minimizing errors in judgment induced by environmental conditions and anxiety levels. This objective of this research employs state of the art Machine Learning (ML) techniques to create an …

Signal Flow Graph Approach To Efficient Dst I-Iv Algorithms, Sirani M. Perera

Sirani Mututhanthrige Perera

In this paper, fast and efficient discrete sine transformation (DST) algorithms are presented based on the factorization of sparse, scaled orthogonal, rotation, rotation-reflection, and butterfly matrices. These algorithms are completely recursive and solely based on DST I-IV. The presented algorithms have low arithmetic cost compared to the known fast DST algorithms. Furthermore, the language of signal flow graph representation of digital structures is used to describe these efficient and recursive DST algorithms having (n􀀀1) points signal flow graph for DST-I and n points signal flow graphs for DST II-IV.

The Hilbert-Huang Transform: A Theoretical Framework And Applications To Leak Identification In Pressurized Space Modules, Kenneth R. Bundy

Electronic Theses and Dissertations

Any manned space mission must provide breathable air to its crew. For this reason, air leaks in spacecraft pose a danger to the mission and any astronauts on board. The purpose of this work is twofold: the first is to address the issue of air pressure loss from leaks in spacecraft. Air leaks present a danger to spacecraft crew, and so a method of finding air leaks when they occur is needed. Most leak detection systems localize the leak in some way. Instead, we address the identification of air leaks in a pressurized space module, we aim to determine the …

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 …

Deep Neural Network Architectures For Modulation Classification Using Principal Component Analysis, Sharan Ramjee, Shengtai Ju, Diyu Yang, Aly El Gamal

The Summer Undergraduate Research Fellowship (SURF) Symposium

In this work, we investigate the application of Principal Component Analysis to the task of wireless signal modulation recognition using deep neural network architectures. Sampling signals at the Nyquist rate, which is often very high, requires a large amount of energy and space to collect and store the samples. Moreover, the time taken to train neural networks for the task of modulation classification is large due to the large number of samples. These problems can be drastically reduced using Principal Component Analysis, which is a technique that allows us to reduce the dimensionality or number of features of the samples …

High Dynamic Range Optical Devices And Applications., Elijah Robert Jensen

Electronic Theses and Dissertations

Much of what we know about fundamental physical law and the universe derives from observations and measurements using optical methods. The passive use of the electromagnetic spectrum can be the best way of studying physical phenomenon in general with minimal disturbance of the system in the process. While for many applications ambient visible light is sufficient, light outside of the visible range may convey more information. The signals of interest are also often a small fraction of the background, and their changes occur on time scales so quickly that they are visually imperceptible. This thesis reports techniques and technologies developed …

Using Principle Component Analysis Of Spectral Mixtures To Analyze Tertiary And Four End-Member Mixtures Containing Carbonates And Olivine, David Burnett

Pence-Boyce STEM Student Scholarship

CRISM images from Mars are expected to contain carbonates such as magnesite [1]. Prior research has been successfully able to determine the approximate percent composition of phyllosilicates in binary lab mixtures using Principle Component Analysis (PCA) [2]. In order to expand this model to work on CRISM images, one of preliminary steps is allowing the algorithm to work on mixtures with more than two components.

Dark Current Rts-Noise In Silicon Image Sensors, Benjamin William Hendrickson

Dissertations and Theses

Random Telegraph Signal (RTS) noise is a random noise source defined by discrete and metastable changes in the magnitude of a signal. Though observed in a variety of physical processes, RTS is of particular interest to image sensor fabrication where progress in the suppression of other noise sources has elevated its noise contribution to the point of approaching the limiting noise source in scientific applications.

There have been two basic physical sources of RTS noise reported in image sensors. The first involves a charge trap in the oxide layer of the source follower in a CMOS image sensor. The capture …

2018 Ieee Signal Processing Cup: Forensic Camera Model Identification Challenge, Michael Geiger

Honors Theses

The goal of this Senior Capstone Project was to lead Union College’s first ever Signal Processing Cup Team to compete in IEEE’s 2018 Signal Processing Cup Competition. This year’s competition was a forensic camera model identification challenge and was divided into two separate stages of competition: Open Competition and Final Competition. Participation in the Open Competition was open to any teams of undergraduate students, but the Final Competition was only open to the three finalists from Open Competition and is scheduled to be held at ICASSP 2018 in Calgary, Alberta, Canada. Teams that make it to the Final Competition will …

Longitudinal Tracking Of Physiological State With Electromyographic Signals., Robert Warren Stallard

Electronic Theses and Dissertations

Electrophysiological measurements have been used in recent history to classify instantaneous physiological configurations, e.g., hand gestures. This work investigates the feasibility of working with changes in physiological configurations over time (i.e., longitudinally) using a variety of algorithms from the machine learning domain. We demonstrate a high degree of classification accuracy for a binary classification problem derived from electromyography measurements before and after a 35-day bedrest. The problem difficulty is increased with a more dynamic experiment testing for changes in astronaut sensorimotor performance by taking electromyography and force plate measurements before, during, and after a jump from a small platform. A …

Spectral Mixture Modeling Using Principle Component Analysis, Joseph S. Makarewicz, Heather D. Makarewicz

Scholar Week 2016 - present

A method for modeling mixtures between two end-member spectra using principle component analysis and linear regression was presented. The presentation included results from three binary mixture data sets including orthopyroxene-clinopyroxene, kaolinite-montmorillonite, and nontronite-ferrihydrite.

Near Earth Space Object Detection Utilizing Parallax As Multi-Hypothesis Test Criterion, Joseph C. Tompkins

Theses and Dissertations

The US Strategic Command (USSTRATCOM) operated Space Surveillance Network (SSN) is tasked with Space Situational Awareness (SSA) for the US military. This system is made up of Electro-Optic sensors such as the Space Surveillance Telescope (SST) and Ground-based Electro-Optical Deep Space Surveillance (GEODSS) as well as RADAR based sensors such as the Space Fence. While Lockheed Martin’s Space Fence is very adept at detecting & tracking objects in Low Earth Orbit (LEO) below 3000 Km in height [1], gaps remain in the tracking of Resident Space Objects (RSO’s) in Geosynchronous Orbits (GEO) due to limitations associated with the implementation of …

Mitigating The Effects Of Boom Occlusion On Automated Aerial Refueling Through Shadow Volumes, Zachary C. Paulson

Theses and Dissertations

In flight refueling of Unmanned Aerial Vehicles (UAVs) is critical to the United States Air Force (USAF). However, the large communication latency between a ground-based operator and his/her remote UAV makes docking with a refueling tanker unsafe. This latency may be mitigated by leveraging a tanker-centric stereo vision system. The vision system observes and computes an approaching receiver's relative position and orientation offering a low-latency, high frequency docking solution. Unfortunately, the boom -- an articulated refueling arm responsible for physically pumping fuel into the receiver -- occludes large portions of the receiver especially as the receiver approaches and docks with …

Rss-Based Device-Free Passive Detection And Localization Using Home Automation Network Radio Frequencies, Tiffany M. Phan

Theses and Dissertations

This research provided a proof of concept for a device-free passive (DfP) system capable of detecting and localizing a target through exploitation of a home automation network’s radio frequency (RF) signals. The system was developed using Insteon devices with a 915 MHz center frequency. Without developer privileges, limitations of the Insteon technology like no intrinsic received signal strength (RSS) field and silent periods between messages were overcome by using software-defined radios to simulate Insteon devices capable of collecting and reporting RSS, and by creating a message generation script and implementing a calibrated filter threshold to reduce silent periods. Evaluation of …

Plasmonic Grating Geometrics And Wavelength-Dependent Focus Depth In Infrared Detectors, Patrick R. Kennedy

Theses and Dissertations

The objective for this research is to determine a relationship between plasmonic grating geometries and the wavelength-dependent focus depth. This research is focused on enhancing the signal collected by infrared detectors by using a metal grating as a planar lens to focus light in the detecting region of the substrate. This can be used to maintain a thinner absorbing region and possibly to create multi-color imaging in a single pixel. Simulations demonstrate that the plasmonic lens is capable of creating a wavelength dependent focus spot.

Retrospective Data Filter, Richard J. Prengaman, Robert E. Thurber, Joe Phipps, Ronald I. Greenberg, Wai L. Hom, James F. Jaworski, Guy W. Riffle

Ronald Greenberg

In a target detection communication system, apparatus and method for determining the presence of probable targets based on contacts (which can indicate the presence of a target, noise, chatter, or objects not of interest) detected within a predefined position sector or sectors over a specified number of scans. The position of each detected contact, as a contact of interest, is compared with the positions of contacts detected at previous times or scans. Velocity profiles indicate which previous contacts support the likelihood that the contact of interest represents a target having a velocity within a defined band. The likelihood, which can …

Self-Image Multimedia Technologies For Feedforward Observational Learning, Nkiruka M. A. Uzuegbunam

Theses and Dissertations--Electrical and Computer Engineering

This dissertation investigates the development and use of self-images in augmented reality systems for learning and learning-based activities. This work focuses on self- modeling, a particular form of learning, actively employed in various settings for therapy or teaching. In particular, this work aims to develop novel multimedia systems to support the display and rendering of augmented self-images. It aims to use interactivity (via games) as a means of obtaining imagery for use in creating augmented self-images. Two multimedia systems are developed, discussed and analyzed. The proposed systems are validated in terms of their technical innovation and their clinical efficacy in …

Offline And Online Density Estimation For Large High-Dimensional Data, Aref Majdara

Dissertations, Master's Theses and Master's Reports

Density estimation has wide applications in machine learning and data analysis techniques including clustering, classification, multimodality analysis, bump hunting and anomaly detection. In high-dimensional space, sparsity of data in local neighborhood makes many of parametric and nonparametric density estimation methods mostly inefficient.

This work presents development of computationally efficient algorithms for high-dimensional density estimation, based on Bayesian sequential partitioning (BSP). Copula transform is used to separate the estimation of marginal and joint densities, with the purpose of reducing the computational complexity and estimation error. Using this separation, a parallel implementation of the density estimation algorithm on a 4-core CPU is …

Intelligent And Secure Underwater Acoustic Communication Networks, Chaofeng Wang

Dissertations, Master's Theses and Master's Reports

Underwater acoustic (UWA) communication networks are promising techniques for medium- to long-range wireless information transfer in aquatic applications. The harsh and dynamic water environment poses grand challenges to the design of UWA networks. This dissertation leverages the advances in machine learning and signal processing to develop intelligent and secure UWA communication networks. Three research topics are studied: 1) reinforcement learning (RL)-based adaptive transmission in UWA channels; 2) reinforcement learning-based adaptive trajectory planning for autonomous underwater vehicles (AUVs) in under-ice environments; 3) signal alignment to secure underwater coordinated multipoint (CoMP) transmissions.

First, a RL-based algorithm is developed for adaptive transmission in …