Electrical and Computer Engineering Commons^™

Target Detection, Tracking, And Localization Using Multi-Spectral Image Fusion And Rf Doppler Differentials, Casey D. Demars

Dissertations, Master's Theses and Master's Reports

It is critical for defense and security applications to have a high probability of detection and low false alarm rate while operating over a wide variety of conditions. Sensor fusion, which is the the process of combining data from two or more sensors, has been utilized to improve the performance of a system by exploiting the strengths of each sensor. This dissertation presents algorithms to fuse multi-sensor data that improves system performance by increasing detection rates, lowering false alarms, and improving track performance. Furthermore, this dissertation presents a framework for comparing algorithm error for image registration which is a critical …

Study Of Obstacle Effect On The Gpsr Protocol And A Novel Intelligent Greedy Routing Protocol For Vanets, Ravikumar Chilmula

Dissertations, Master's Theses and Master's Reports

In recent years, connected vehicle technologies have been developed by automotive companies, academia, and researchers as part of Intelligent Transportation Systems (ITS). This group of stakeholders continue to work on these technologies to make them as reliable and cost-effective as possible. This attention is because of the increasing connected vehicles safety-related, entertainment, and traffic management applications, which have the potential to decrease the number of road accidents, save fuel and time for millions of daily commuters worldwide.

Vehicular Ad-Hoc Network (VANET), which is a subgroup of Mobile Ad-Hoc Network (MANET), is being developed and implemented in vehicles as the critical …

Testing Of Recursive And Non-Recursive Algorithms For Real-Time Phasor And Frequency Estimations In Power Systems, Dhruv Sharma

Dissertations, Master's Theses and Master's Reports

Steady-state performance of various recursive and non-recursive algorithms are tested in this report according to the test signals given in the IEEE Standard C37.118.1-2011. Phase magnitude and phase angle of the power grid signals have been estimated using Discrete Fourier Transform (non-recursive), Discrete Fourier Transform (recursive), Least Square, and Wavelet Transform Algorithms. Frequency estimation is performed using Discrete Fourier Transform, Weighted Least Square, and Zero Crossing methods. These algorithms are evaluated in LabView software and tested by generating test signals in a Simulink model. Furthermore, Total Vector Error (TVE) is calculated using dynamic test signals as per the IEEE Standard …

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 …

Video Frame Reduction In Autonomous Vehicles, Gaurav R. Bagwe

Dissertations, Master's Theses and Master's Reports

Camera sensors are emerging in many applications such as Smart Buildings and autonomous driving. The Data generated by multiple cameras in a smart building and autonomous driving applications is usually transmitted through an edge box to a cloud terminal. This transmitted information requires a considerable channel bandwidth, which is not available through current communication standards. The report proposes a Camera Sensor Frame Reduction method to decrease the required channel bandwidth for applications such as autonomous driving.

Here, we propose a method that incorporates cross frame similarity measurement method to reduce the redundant frames and decrease the data rate of each …