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Resilience Analysis of Inertial Navi...

Stavish, Kenneth V.

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Resilience Analysis of Inertial Navigation Systems (INS) through an Enhanced INS Tool Kit.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Resilience Analysis of Inertial Navigation Systems (INS) through an Enhanced INS Tool Kit./
Author:	Stavish, Kenneth V.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2018,
Description:	70 p.
Notes:	Source: Dissertation Abstracts International, Volume: 79-07(E), Section: B.
Contained By:	Dissertation Abstracts International79-07B(E).
Subject:	Engineering. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10743838
ISBN:	9780355615814

Resilience Analysis of Inertial Navigation Systems (INS) through an Enhanced INS Tool Kit.
Stavish, Kenneth V.

Resilience Analysis of Inertial Navigation Systems (INS) through an Enhanced INS Tool Kit. - Ann Arbor : ProQuest Dissertations & Theses, 2018 - 70 p.

Source: Dissertation Abstracts International, Volume: 79-07(E), Section: B.

Thesis (D.Engr.)--The George Washington University, 2018.

Resilience is explained as an entity's capacity to survive and recover from disruptions. Approaches to design resilient systems are in growing demand; however, there have been few demonstrations for measuring and quantifying systems resilience. This research presents a Resilience Analysis regarding Inertial Navigation System (INS) architectures. Specifically for the case study at hand, it is not clear which INS architecture to choose (tightly coupled or loosely coupled) for resilience. This research tests whether Robustness and Recovery measures of effectiveness (MOEs) can be used to determine which INS architecture is most resilient.

ISBN: 9780355615814Subjects--Topical Terms:

586835
Engineering.

Resilience Analysis of Inertial Navigation Systems (INS) through an Enhanced INS Tool Kit.
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100 1 $a Stavish, Kenneth V. $3 3351337
245 1 0 $a Resilience Analysis of Inertial Navigation Systems (INS) through an Enhanced INS Tool Kit.
260 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2018
300 $a 70 p.
500 $a Source: Dissertation Abstracts International, Volume: 79-07(E), Section: B.
500 $a Advisers: Timothy Blackburn; Andreas Garstenauer.
502 $a Thesis (D.Engr.)--The George Washington University, 2018.
520 $a Resilience is explained as an entity's capacity to survive and recover from disruptions. Approaches to design resilient systems are in growing demand; however, there have been few demonstrations for measuring and quantifying systems resilience. This research presents a Resilience Analysis regarding Inertial Navigation System (INS) architectures. Specifically for the case study at hand, it is not clear which INS architecture to choose (tightly coupled or loosely coupled) for resilience. This research tests whether Robustness and Recovery measures of effectiveness (MOEs) can be used to determine which INS architecture is most resilient.
520 $a The methodology of this research included enhancing an INS Tool Kit with Resilience Analysis functions. The INS Tool Kit was used to collect resilience data for different INS configurations dealing with Global Positioning System (GPS) outages. Robustness and Recovery data were collected for 500 observations of five different INS configurations. Three configurations were loosely coupled and two were tightly coupled; therefore, 1500 observations of resilience data for loosely coupled INS were compared to 1000 observations for tightly coupled INS. Using data from this Resilience Analysis, a series of nonparametric Mann-Whitney tests showed there is a statistically significant difference between tightly coupled and loosely coupled INS architectures in terms of resilience. Based on these results, greater resilience to GPS outages can be added to the list of advantages for tightly coupled INS architectures. The conclusion of this research is that Robustness and Recovery measures can be used to determine and compare the resilience of different INS architectures.
590 $a School code: 0075.
650 4 $a Engineering. $3 586835
650 4 $a Systems science. $3 3168411
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710 2 $a The George Washington University. $b Engineering Management. $3 1262973
773 0 $t Dissertation Abstracts International $g 79-07B(E).
790 $a 0075
791 $a D.Engr.
792 $a 2018
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10743838