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Analysis of Field Programmable Gate Array-Based Kalman Filter Architectures

A Field Programmable Gate Array (FPGA)-based Polymorphic Faddeev Systolic Array (PolyFSA) architecture is proposed to accelerate an Extended Kalman Filter (EKF) algorithm. A system architecture comprising a software processor as the host processor, a hardware controller, a cache-based memory sub-system, and the proposed PolyFSA as co-processor, is presented. PolyFSA-based system architecture is implemented on a Xilinx Virtex 4 family of FPGAs. Results indicate significant speed-ups for the proposed architecture when compared against a space-based software processor. This dissertation proposes a comprehensive architecture analysis that is comprised of (i) error analysis, (ii) performance analysis, and (iii) area analysis. Results are presented in the form of 2-D pareto plots (area versus error, area versus time) and a 3-D plot (area versus time versus error). These plots indicate area savings obtained by varying any design constraints for the PolyFSA architecture. The proposed performance model can be reused to estimate the execution time of EKF on other conventional hardware architectures. In this dissertation, the performance of the proposed PolyFSA is compared against the performance of two conventional hardware architectures. The proposed architecture outperforms the other two in most test cases.

Identiferoai:union.ndltd.org:UTAHS/oai:digitalcommons.usu.edu:etd-1784
Date01 December 2010
CreatorsSudarsanam, Arvind
PublisherDigitalCommons@USU
Source SetsUtah State University
Detected LanguageEnglish
Typetext
Formatapplication/pdf
SourceAll Graduate Theses and Dissertations
RightsCopyright for this work is held by the author. Transmission or reproduction of materials protected by copyright beyond that allowed by fair use requires the written permission of the copyright owners. Works not in the public domain cannot be commercially exploited without permission of the copyright owner. Responsibility for any use rests exclusively with the user. For more information contact Andrew Wesolek (andrew.wesolek@usu.edu).

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