Flight-test evaluation of sensor fusion algorithms for attitude estimation

Jason N. Gross; Yu Gu; Matthew B. Rhudy; Srikanth Gururajan; Marcello R. Napolitano

doi:10.1109/TAES.2012.6237583

Flight-test evaluation of sensor fusion algorithms for attitude estimation

Jason N. Gross
, Yu Gu
, Matthew B. Rhudy
, Srikanth Gururajan
, Marcello R. Napolitano

Division of Engineering, Business & Computing (Berks)

Research output: Contribution to journal › Article › peer-review

90 Scopus citations

Abstract

In this paper, several Global Positioning System/inertial navigation system (GPS/INS) algorithms are presented using both extended Kalman filter (EKF) and unscented Kalman filter (UKF), and evaluated with respect to performance and complexity. The contributions of this study are that attitude estimates are compared with independent measurements provided by a mechanical vertical gyroscope using 23 diverse sets of flight data, and that a fundamental difference between EKF and UKF with respect to linearization is evaluated.

Original language	English (US)
Article number	6237583
Pages (from-to)	2128-2139
Number of pages	12
Journal	IEEE Transactions on Aerospace and Electronic Systems
Volume	48
Issue number	3
DOIs	https://doi.org/10.1109/TAES.2012.6237583
State	Published - 2012

All Science Journal Classification (ASJC) codes

Aerospace Engineering
Electrical and Electronic Engineering

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10.1109/TAES.2012.6237583

Cite this

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title = "Flight-test evaluation of sensor fusion algorithms for attitude estimation",

abstract = "In this paper, several Global Positioning System/inertial navigation system (GPS/INS) algorithms are presented using both extended Kalman filter (EKF) and unscented Kalman filter (UKF), and evaluated with respect to performance and complexity. The contributions of this study are that attitude estimates are compared with independent measurements provided by a mechanical vertical gyroscope using 23 diverse sets of flight data, and that a fundamental difference between EKF and UKF with respect to linearization is evaluated.",

author = "Gross, \{Jason N.\} and Yu Gu and Rhudy, \{Matthew B.\} and Srikanth Gururajan and Napolitano, \{Marcello R.\}",

note = "Funding Information: This work was supported in part by the West Virginia Department of Highway under Project RP253-B.",

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AU - Gross, Jason N.

AU - Gu, Yu

AU - Rhudy, Matthew B.

AU - Gururajan, Srikanth

AU - Napolitano, Marcello R.

N1 - Funding Information: This work was supported in part by the West Virginia Department of Highway under Project RP253-B.

PY - 2012

Y1 - 2012

N2 - In this paper, several Global Positioning System/inertial navigation system (GPS/INS) algorithms are presented using both extended Kalman filter (EKF) and unscented Kalman filter (UKF), and evaluated with respect to performance and complexity. The contributions of this study are that attitude estimates are compared with independent measurements provided by a mechanical vertical gyroscope using 23 diverse sets of flight data, and that a fundamental difference between EKF and UKF with respect to linearization is evaluated.

AB - In this paper, several Global Positioning System/inertial navigation system (GPS/INS) algorithms are presented using both extended Kalman filter (EKF) and unscented Kalman filter (UKF), and evaluated with respect to performance and complexity. The contributions of this study are that attitude estimates are compared with independent measurements provided by a mechanical vertical gyroscope using 23 diverse sets of flight data, and that a fundamental difference between EKF and UKF with respect to linearization is evaluated.

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JO - IEEE Transactions on Aerospace and Electronic Systems

JF - IEEE Transactions on Aerospace and Electronic Systems

IS - 3

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ER -

Flight-test evaluation of sensor fusion algorithms for attitude estimation

Abstract

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