Introduction to random signals and applied kalman filtering (second edition), Robert Grover Brown and Patrick Y. C. Hwang, John Wiley, New York, 1992, 512 p.p., ISBN 0–47152–573–1, $62.95
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This article is published in International Journal of Robust and Nonlinear Control.The article was published on 1992-10-01 and is currently open access. It has received 109 citations till now.read more
Citations
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Ionospheric Scintillation Monitoring Using Commercial Single Frequency C/A Code Receivers
TL;DR: The result is a design of a low-cost, portable Ionospheric Scintillation Monitor (ISM) being developed on a follow-on SBlR Phase II project and testing of a software-modified commercial C/A code receiver to perform this function.
Proceedings ArticleDOI
Inertial and magnetic posture tracking for inserting humans into networked virtual environments
TL;DR: A quaternion-based complementary filter algorithm for processing the output data from a nine-axis MARG (Magnetic field, Angular Rate, and Gravity) sensor unit containing three orthogonally mounted angular rate sensors, three Orthogonal linear accelerometers and three orthogsonal magnetometers is described.
Inertial and Magnetic Tracking of Limb Segment Orientation for Inserting Humans into Synthetic Environments
TL;DR: This research proposes to overcome current limitations using nine-axis magnetic/angular/rate/gravity (MARG) sensors combined with a quaternion-based complementary filter algorithm capable of continuously correcting for drift and following angular motion through all orientations without singularities.
Proceedings ArticleDOI
Orientation tracking for humans and robots using inertial sensors
TL;DR: This paper describes the design, implementation, and preliminary testing of an inertial tracking system using a "complementary" filter based upon quaternions that is capable of tracking a rigid body through all orientations and is more efficient than those based on Euler angles.
References
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Book
Kalman Filtering with Real-time Applications
Charles K. Chui,Guanrong Chen +1 more
TL;DR: Kalman Filtering with Real-Time Applications presents a thorough discussion of the mathematical theory and computational schemes of Kalman filtering, including a direct method consisting of a series of elementary steps, and an indirect method based on innovation projection.