Aircraft state estimation from visual motion: application of the subspace constraints approach

2002 IEEE Position Location and Navigation Symposium (IEEE Cat. No.02CH37284) ◽

10.1109/plans.2002.998917 ◽

2003 ◽

Cited By ~ 1

Author(s):

H. Rotstein ◽

P. Gurfil

Keyword(s):

State Estimation ◽

Visual Motion ◽

Subspace Constraints

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Partial Aircraft State Estimation from Visual Motion Using the Subspace Constraints Approach

Journal of Guidance Control and Dynamics ◽

10.2514/2.4811 ◽

2001 ◽

Vol 24 (5) ◽

pp. 1016-1028 ◽

Cited By ~ 52

Author(s):

Pini GurŽfil ◽

Hector Rotstein

Keyword(s):

State Estimation ◽

Visual Motion ◽

Subspace Constraints

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Slow Dynamics of Postural Sway Are in the Feedback Loop

Journal of Neurophysiology ◽

10.1152/jn.01144.2004 ◽

2006 ◽

Vol 95 (3) ◽

pp. 1410-1418 ◽

Cited By ~ 72

Author(s):

Tim Kiemel ◽

Kelvin S. Oie ◽

John J. Jeka

Keyword(s):

State Estimation ◽

Feedback Loop ◽

Inverted Pendulum ◽

Visual Motion ◽

Postural Sway ◽

Slow Component ◽

Quiet Stance ◽

Slow Process ◽

Underlying Basis ◽

Fifth Order

Postural sway is considered to have two fundamental stochastic components, a slow nonoscillatory component and a faster damped-oscillatory component. The slow component has been shown to account for the majority of sway variance during quiet stance. Postural control is generally viewed as a feedback loop in which sway is detected by sensory systems and appropriate motor commands are generated to stabilize the body's orientation. Whereas the mechanistic source for the damped-oscillatory sway component is most likely feedback control of an inverted pendulum, the underlying basis for the slow component is less clear. We investigated whether the slow process was inside or outside the feedback loop by providing standing subjects with sum-of-sines visual motion. Linear stochastic models were fit to the experimental sway trajectories to determine the stochastic structure of sway as well as the transfer function from visual motion to sway. The results supported a fifth-order stochastic model, consisting of a slow process and two damped-oscillatory components. Importantly, the slow process was determined to be inside the feedback loop. This supports the hypothesis that the slow component is due to errors in state estimation because state estimation is inside the feedback loop rather than a moving reference point or an exploratory process outside the feedback loop.

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