Smoothing for ZUPT-aided INSs

Due to the recursive and integrative nature of zero-velocity-update-aided (ZUPT-aided) inertial navigation systems (INSs), the error covariance increases throughout each ZUPT-less period followed by a drastic decrease and large state estimate corrections as soon as ZUPTs are applied. For dead-reckon...

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Published in:2012 International Conference on Indoor Positioning and Indoor Navigation pp. 1 - 5
Main Authors: Colomar, David Simon, Nilsson, J., Handel, P.
Format: Conference Proceeding
Language:English
Published: IEEE 01.11.2012
Series:International Conference on Indoor Positioning and Indoor Navigation
Subjects:
Acceleration
Dead reckoning
Error covariances
Inertial sensor
Kalman filters
Navigation
Off-line processing
Real-time application
Real-time systems
Sensors
Smoothing algorithms
Smoothing methods
State estimates
Trajectory
ISBN:1467319554, 9781467319553, 9781467319546, 1467319546
Online Access:Get full text
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Abstract Due to the recursive and integrative nature of zero-velocity-update-aided (ZUPT-aided) inertial navigation systems (INSs), the error covariance increases throughout each ZUPT-less period followed by a drastic decrease and large state estimate corrections as soon as ZUPTs are applied. For dead-reckoning with foot-mounted inertial sensors, this gives undesirable discontinuities in the estimated trajectory at the end of each step. However, for many applications, some degree of lag can be tolerated and the information provided by the ZUPTs at the end of a step can be made available throughout the step, eliminating the discontinuities. For this purpose, we propose a smoothing algorithm for ZUPT-aided INSs. For near real-time applications, smoothing is applied to the data in a step-wise manner requiring a suggested varying-lag segmentation rule. For complete off-line processing, full data set smoothing is examined. Finally, the consequences and impact of smoothing are analyzed and quantified based on real-data.
AbstractList Due to the recursive and integrative nature of zero-velocity-update-aided (ZUPT-aided) inertial navigation systems (INSs), the error covariance increases throughout each ZUPT-less period followed by a drastic decrease and large state estimate corrections as soon as ZUPTs are applied. For dead-reckoning with foot-mounted inertial sensors, this gives undesirable discontinuities in the estimated trajectory at the end of each step. However, for many applications, some degree of lag can be tolerated and the information provided by the ZUPTs at the end of a step can be made available throughout the step, eliminating the discontinuities. For this purpose, we propose a smoothing algorithm for ZUPT-aided INSs. For near real-time applications, smoothing is applied to the data in a step-wise manner requiring a suggested varying-lag segmentation rule. For complete off-line processing, full data set smoothing is examined. Finally, the consequences and impact of smoothing are analyzed and quantified based on real-data.
Author Nilsson, J.
Colomar, David Simon
Handel, P.
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  surname: Nilsson
  fullname: Nilsson, J.
  organization: Signal Process. Lab., KTH R. Inst. of Technol., Stockholm, Sweden
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  surname: Handel
  fullname: Handel, P.
  organization: Signal Process. Lab., KTH R. Inst. of Technol., Stockholm, Sweden
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Snippet Due to the recursive and integrative nature of zero-velocity-update-aided (ZUPT-aided) inertial navigation systems (INSs), the error covariance increases...
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SubjectTerms Acceleration
Dead reckoning
Error covariances
Inertial sensor
Kalman filters
Navigation
Off-line processing
Real-time application
Real-time systems
Sensors
Smoothing algorithms
Smoothing methods
State estimates
Trajectory
Title Smoothing for ZUPT-aided INSs
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