Architectures for a space-based information network with shared on-orbit processing

Thesis (Ph. D.)--Massachusetts Institute of Technology, Engineering Systems Division, 2005.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Includes bibliographical references (p. 335-343).This dissertation provides a top level assessment of technology design choices for the architecture of a space-based information network with shared on-orbit processing. Networking is an efficient method of sharing communications and lowering the cost of communications, providing better interoperability and data integration for multiple satellites. The current space communications architecture sets a critical limitation on the collection of raw data sent to the ground. By introducing powerful space-borne processing, compression of raw data can alleviate the need for expensive and expansive downlinks. Moreover, distribution of processed data directly from space sensors to the end-users may be more easily realized. A space-based information network backbone can act as the transport network for mission satellites as well as enable the concept of decoupled, shared, and perhaps distributed space-borne processing for space-based assets. Optical crosslinks are the enabling technology for creating a cost-effective network capable of supporting high data rates. In this dissertation, the space-based network backbone is designed to meet a number of mission requirements by optimizing over constellation topologies under different traffic models. With high network capacity availability, space-borne processing can be accessible by any mission satellite attached to the network. Space-borne processing capabilities can be enhanced with commercial processors that are tolerant of radiation and replenished periodically (as frequently as every two years).(cont.) Additionally, innovative ways of using a space-based information network can revolutionize satellite communications and space missions. Applications include distributed computing in space, interoperable space communications, multiplatform distributed satellite communications, coherent distributed space sensing, multisensor data fusion, and restoration of disconnected global terrestrial networks after a disaster. Lastly, the consolidation of all the different communications assets into a horizontally integrated space-based network infrastructure calls for a space-based network backbone to be designed with a generic nature. A coherent infrastructure can satisfy the goals of interoperability, flexibility, scalability, and allows the system to be evolutionary. This transformational vision of a generic space-based information network allows for growth to accommodate civilian demands, lowers the price of entry for the commercial sector, and makes way for innovation to enhance and provide additional value to military systems.by Serena Chan.Ph.D

GVSU Undergraduate and Graduate Catalog, 2019-2020

Grand Valley State University 2019-2020 undergraduate and/or graduate course catalog published annually to provide students with information and guidance for enrollment.https://scholarworks.gvsu.edu/course_catalogs/1094/thumbnail.jp

GVSU Undergraduate and Graduate Catalog, 2016-2017

Grand Valley State University 2016-2017 undergraduate and/or graduate course catalog published annually to provide students with information and guidance for enrollment.https://scholarworks.gvsu.edu/course_catalogs/1091/thumbnail.jp

GVSU Undergraduate and Graduate Catalog, 2017-2018

Grand Valley State University 2017-2018 undergraduate and/or graduate course catalog published annually to provide students with information and guidance for enrollment.https://scholarworks.gvsu.edu/course_catalogs/1092/thumbnail.jp

GVSU Undergraduate and Graduate Catalog, 2016-2017

Grand Valley State University 2016-2017 undergraduate and/or graduate course catalog published annually to provide students with information and guidance for enrollment.https://scholarworks.gvsu.edu/course_catalogs/1091/thumbnail.jp

Deteção espetral de banda larga para rádio cógnitivo

Doutoramento em TelecomunicaçõesEsta tese tem como objetivo o desenvolvimento de uma unidade autónoma de deteção espetral em tempo real. Para tal são analisadas várias implementações para a estimação do nível de ruído de fundo de forma a se poder criar um limiar adaptativo para um detetor com uma taxa constante de falso alarme. Além da identificação binária da utilização do espetro, pretende-se também obter a classificação individual de cada transmissor e a sua ocupação ao longo do tempo. Para tal são exploradas duas soluções baseadas no algoritmo, de agrupamento de dados, conhecido como maximização de expectativas que permite identificar os sinais analisados pela potência recebida e relação de fase entre dois recetores. Um algoritmo de deteção de sinal baseado também na relação de fase de dois recetores e sem necessidade de estimação do ruído de fundo é também demonstrado. Este algoritmo foi otimizado para permitir uma implementação eficiente num arranjo de portas programáveis em campo a funcionar em tempo real para uma elevada largura de banda, permitindo também estimar a direção da transmissão detetada.The purpose of this thesis is to develop an autonomous unit for real time spectrum sensing. For this purpose, several implementations for the estimation of the background noise level are analysed to create an adaptive threshold and ensure a constant false alarm rate detector. In addition to the binary identification of the spectrum usage, it is also intended to obtain an individual classification of each transmitter occupation and its spectrum usage over time. To do so, two solutions based on the expectation maximization data clustering, that allow to identify the analyzed signals by the received power and phase relation between two receivers, were explored. A signal detection algorithm, also based on the phase relationship between two receivers and with no need for noise estimation is also demonstrated. This algorithm has been optimized to allow an efficient implementation in a FPGA operating in real time for a high bandwidth and it also allows the estimation of the direction of arrival of the detected transmission

Numerical and Evolutionary Optimization 2020

This book was established after the 8th International Workshop on Numerical and Evolutionary Optimization (NEO), representing a collection of papers on the intersection of the two research areas covered at this workshop: numerical optimization and evolutionary search techniques. While focusing on the design of fast and reliable methods lying across these two paradigms, the resulting techniques are strongly applicable to a broad class of real-world problems, such as pattern recognition, routing, energy, lines of production, prediction, and modeling, among others. This volume is intended to serve as a useful reference for mathematicians, engineers, and computer scientists to explore current issues and solutions emerging from these mathematical and computational methods and their applications

GVSU Undergraduate and Graduate Catalog, 2014-2015

Grand Valley State University 2014-2015 undergraduate and/or graduate course catalog published annually to provide students with information and guidance for enrollment.https://scholarworks.gvsu.edu/course_catalogs/1089/thumbnail.jp

GVSU Undergraduate and Graduate Catalog, 2018-2019

Grand Valley State University 2018-2019 undergraduate and/or graduate course catalog published annually to provide students with information and guidance for enrollment.https://scholarworks.gvsu.edu/course_catalogs/1093/thumbnail.jp

GVSU Undergraduate and Graduate Catalog, 2020-2021

Grand Valley State University 2020-2021 undergraduate and graduate course catalog. Course catalogs are published annually to provide students with information and guidance for enrollment.https://scholarworks.gvsu.edu/course_catalogs/1095/thumbnail.jp