Award Date
4-2018
Degree Type
Honors Thesis
Degree Name
Bachelor of Science
Department
Electrical and Computer Engineering
Advisor 1
Dr. Emma Regentova
Advisor 2
Dr. Andrew Hanson
Advisor 3
Dr. Venkatesan Muthukumar
Number of Pages
59
Abstract
The usefulness of modern digital communication comes from ensuring the data from a source arrives to its destination quickly and correctly. To meet these demands, communication protocols employ data compression and error detection/correction to ensure compactness and accuracy of the data, especially for critical scientific data which requires the use of lossless compression. For example, in deep space communication, information received from satellites to ground stations on Earth come in huge volumes captured with high precision and resolution by space mission instruments, such as Hubble Space Telescope (HST). On-board implementation of communication protocols poses numerous constraints and demands on the high performance given the criticality of data and a high cost of a space mission, including data values. The objectives of this study are to determine which data compression techniques yields the a) minimum data volumes, b) most error resilience, and c) utilize the least amount and power of hardware resources. For this study, a Field Programmable Gate Array (FPGA) will serve as the main component for building the circuitry for each source coding technique. Furthermore, errors are induced based on studies of reported errors rates in deep space communication channels to test for error resilience. Finally, the calculation of resource utilization of the source encoder determines the power and computational usage. Based on the analysis of the error resilience and the characteristics of errors, the requirements to the channel coding are formulated.
Keywords
Source coding; Error resilience; Channel coding; Deep space communication
Disciplines
Electrical and Computer Engineering
File Format
File Size
1.228 KB
Language
English
Repository Citation
Dizon, Reiner, "Efficient Image Coding and Transmission in Deep Space Communication" (2018). Honors College Theses. 31.
https://digitalscholarship.unlv.edu/honors_theses/31