---
_id: '11861'
abstract:
- lang: eng
text: 'In this contribution we present a theoretical and experimental investigation
into the effects of reverberation and noise on features in the logarithmic mel
power spectral domain, an intermediate stage in the computation of the mel frequency
cepstral coefficients, prevalent in automatic speech recognition (ASR). Gaining
insight into the complex interaction between clean speech, noise, and noisy reverberant
speech features is essential for any ASR system to be robust against noise and
reverberation present in distant microphone input signals. The findings are gathered
in a probabilistic formulation of an observation model which may be used in model-based
feature compensation schemes. The proposed observation model extends previous
models in three major directions: First, the contribution of additive background
noise to the observation error is explicitly taken into account. Second, an energy
compensation constant is introduced which ensures an unbiased estimate of the
reverberant speech features, and, third, a recursive variant of the observation
model is developed resulting in reduced computational complexity when used in
model-based feature compensation. The experimental section is used to evaluate
the accuracy of the model and to describe how its parameters can be determined
from test data.'
author:
- first_name: Volker
full_name: Leutnant, Volker
last_name: Leutnant
- first_name: Alexander
full_name: Krueger, Alexander
last_name: Krueger
- first_name: Reinhold
full_name: Haeb-Umbach, Reinhold
id: '242'
last_name: Haeb-Umbach
citation:
ama: Leutnant V, Krueger A, Haeb-Umbach R. A New Observation Model in the Logarithmic
Mel Power Spectral Domain for the Automatic Recognition of Noisy Reverberant Speech.
IEEE/ACM Transactions on Audio, Speech, and Language Processing. 2014;22(1):95-109.
doi:10.1109/TASLP.2013.2285480
apa: Leutnant, V., Krueger, A., & Haeb-Umbach, R. (2014). A New Observation
Model in the Logarithmic Mel Power Spectral Domain for the Automatic Recognition
of Noisy Reverberant Speech. IEEE/ACM Transactions on Audio, Speech, and Language
Processing, 22(1), 95–109. https://doi.org/10.1109/TASLP.2013.2285480
bibtex: '@article{Leutnant_Krueger_Haeb-Umbach_2014, title={A New Observation Model
in the Logarithmic Mel Power Spectral Domain for the Automatic Recognition of
Noisy Reverberant Speech}, volume={22}, DOI={10.1109/TASLP.2013.2285480},
number={1}, journal={IEEE/ACM Transactions on Audio, Speech, and Language Processing},
author={Leutnant, Volker and Krueger, Alexander and Haeb-Umbach, Reinhold}, year={2014},
pages={95–109} }'
chicago: 'Leutnant, Volker, Alexander Krueger, and Reinhold Haeb-Umbach. “A New
Observation Model in the Logarithmic Mel Power Spectral Domain for the Automatic
Recognition of Noisy Reverberant Speech.” IEEE/ACM Transactions on Audio, Speech,
and Language Processing 22, no. 1 (2014): 95–109. https://doi.org/10.1109/TASLP.2013.2285480.'
ieee: V. Leutnant, A. Krueger, and R. Haeb-Umbach, “A New Observation Model in the
Logarithmic Mel Power Spectral Domain for the Automatic Recognition of Noisy Reverberant
Speech,” IEEE/ACM Transactions on Audio, Speech, and Language Processing,
vol. 22, no. 1, pp. 95–109, 2014.
mla: Leutnant, Volker, et al. “A New Observation Model in the Logarithmic Mel Power
Spectral Domain for the Automatic Recognition of Noisy Reverberant Speech.” IEEE/ACM
Transactions on Audio, Speech, and Language Processing, vol. 22, no. 1, 2014,
pp. 95–109, doi:10.1109/TASLP.2013.2285480.
short: V. Leutnant, A. Krueger, R. Haeb-Umbach, IEEE/ACM Transactions on Audio,
Speech, and Language Processing 22 (2014) 95–109.
date_created: 2019-07-12T05:29:41Z
date_updated: 2022-01-06T06:51:11Z
department:
- _id: '54'
doi: 10.1109/TASLP.2013.2285480
intvolume: ' 22'
issue: '1'
keyword:
- computational complexity
- reverberation
- speech recognition
- automatic speech recognition
- background noise
- clean speech
- computational complexity
- energy compensation
- logarithmic mel power spectral domain
- mel frequency cepstral coefficients
- microphone input signals
- model-based feature compensation schemes
- noisy reverberant speech automatic recognition
- noisy reverberant speech features
- reverberation
- Atmospheric modeling
- Computational modeling
- Noise
- Noise measurement
- Reverberation
- Speech
- Vectors
- Model-based feature compensation
- observation model for reverberant and noisy speech
- recursive observation model
- robust automatic speech recognition
language:
- iso: eng
page: 95-109
publication: IEEE/ACM Transactions on Audio, Speech, and Language Processing
publication_identifier:
issn:
- 2329-9290
status: public
title: A New Observation Model in the Logarithmic Mel Power Spectral Domain for the
Automatic Recognition of Noisy Reverberant Speech
type: journal_article
user_id: '44006'
volume: 22
year: '2014'
...
---
_id: '11740'
abstract:
- lang: eng
text: In this contribution we derive the Maximum A-Posteriori (MAP) estimates of
the parameters of a Gaussian Mixture Model (GMM) in the presence of noisy observations.
We assume the distortion to be white Gaussian noise of known mean and variance.
An approximate conjugate prior of the GMM parameters is derived allowing for a
computationally efficient implementation in a sequential estimation framework.
Simulations on artificially generated data demonstrate the superiority of the
proposed method compared to the Maximum Likelihood technique and to the ordinary
MAP approach, whose estimates are corrected by the known statistics of the distortion
in a straightforward manner.
author:
- first_name: Aleksej
full_name: Chinaev, Aleksej
last_name: Chinaev
- first_name: Reinhold
full_name: Haeb-Umbach, Reinhold
id: '242'
last_name: Haeb-Umbach
citation:
ama: 'Chinaev A, Haeb-Umbach R. MAP-based Estimation of the Parameters of a Gaussian
Mixture Model in the Presence of Noisy Observations. In: 38th International
Conference on Acoustics, Speech and Signal Processing (ICASSP 2013). ; 2013:3352-3356.
doi:10.1109/ICASSP.2013.6638279'
apa: Chinaev, A., & Haeb-Umbach, R. (2013). MAP-based Estimation of the Parameters
of a Gaussian Mixture Model in the Presence of Noisy Observations. In 38th
International Conference on Acoustics, Speech and Signal Processing (ICASSP 2013)
(pp. 3352–3356). https://doi.org/10.1109/ICASSP.2013.6638279
bibtex: '@inproceedings{Chinaev_Haeb-Umbach_2013, title={MAP-based Estimation of
the Parameters of a Gaussian Mixture Model in the Presence of Noisy Observations},
DOI={10.1109/ICASSP.2013.6638279},
booktitle={38th International Conference on Acoustics, Speech and Signal Processing
(ICASSP 2013)}, author={Chinaev, Aleksej and Haeb-Umbach, Reinhold}, year={2013},
pages={3352–3356} }'
chicago: Chinaev, Aleksej, and Reinhold Haeb-Umbach. “MAP-Based Estimation of the
Parameters of a Gaussian Mixture Model in the Presence of Noisy Observations.”
In 38th International Conference on Acoustics, Speech and Signal Processing
(ICASSP 2013), 3352–56, 2013. https://doi.org/10.1109/ICASSP.2013.6638279.
ieee: A. Chinaev and R. Haeb-Umbach, “MAP-based Estimation of the Parameters of
a Gaussian Mixture Model in the Presence of Noisy Observations,” in 38th International
Conference on Acoustics, Speech and Signal Processing (ICASSP 2013), 2013,
pp. 3352–3356.
mla: Chinaev, Aleksej, and Reinhold Haeb-Umbach. “MAP-Based Estimation of the Parameters
of a Gaussian Mixture Model in the Presence of Noisy Observations.” 38th International
Conference on Acoustics, Speech and Signal Processing (ICASSP 2013), 2013,
pp. 3352–56, doi:10.1109/ICASSP.2013.6638279.
short: 'A. Chinaev, R. Haeb-Umbach, in: 38th International Conference on Acoustics,
Speech and Signal Processing (ICASSP 2013), 2013, pp. 3352–3356.'
date_created: 2019-07-12T05:27:20Z
date_updated: 2022-01-06T06:51:08Z
department:
- _id: '54'
doi: 10.1109/ICASSP.2013.6638279
keyword:
- Gaussian noise
- maximum likelihood estimation
- parameter estimation
- GMM parameter
- Gaussian mixture model
- MAP estimation
- Map-based estimation
- maximum a-posteriori estimation
- maximum likelihood technique
- noisy observation
- sequential estimation framework
- white Gaussian noise
- Additive noise
- Gaussian mixture model
- Maximum likelihood estimation
- Noise measurement
- Gaussian mixture model
- Maximum a posteriori estimation
- Maximum likelihood estimation
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://groups.uni-paderborn.de/nt/pubs/2013/ChHa13.pdf
oa: '1'
page: 3352-3356
publication: 38th International Conference on Acoustics, Speech and Signal Processing
(ICASSP 2013)
publication_identifier:
issn:
- 1520-6149
related_material:
link:
- description: Poster
relation: supplementary_material
url: https://groups.uni-paderborn.de/nt/pubs/2013/ChHa13_Poster.pdf
status: public
title: MAP-based Estimation of the Parameters of a Gaussian Mixture Model in the Presence
of Noisy Observations
type: conference
user_id: '44006'
year: '2013'
...
---
_id: '11816'
abstract:
- lang: eng
text: In this paper, we consider the Maximum Likelihood (ML) estimation of the parameters
of a GAUSSIAN in the presence of censored, i.e., clipped data. We show that the
resulting Expectation Maximization (EM) algorithm delivers virtually biasfree
and efficient estimates, and we discuss its convergence properties. We also discuss
optimal classification in the presence of censored data. Censored data are frequently
encountered in wireless LAN positioning systems based on the fingerprinting method
employing signal strength measurements, due to the limited sensitivity of the
portable devices. Experiments both on simulated and real-world data demonstrate
the effectiveness of the proposed algorithms.
author:
- first_name: Manh Kha
full_name: Hoang, Manh Kha
last_name: Hoang
- first_name: Reinhold
full_name: Haeb-Umbach, Reinhold
id: '242'
last_name: Haeb-Umbach
citation:
ama: 'Hoang MK, Haeb-Umbach R. Parameter estimation and classification of censored
Gaussian data with application to WiFi indoor positioning. In: 38th International
Conference on Acoustics, Speech, and Signal Processing (ICASSP 2013). ; 2013:3721-3725.
doi:10.1109/ICASSP.2013.6638353'
apa: Hoang, M. K., & Haeb-Umbach, R. (2013). Parameter estimation and classification
of censored Gaussian data with application to WiFi indoor positioning. In 38th
International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2013)
(pp. 3721–3725). https://doi.org/10.1109/ICASSP.2013.6638353
bibtex: '@inproceedings{Hoang_Haeb-Umbach_2013, title={Parameter estimation and
classification of censored Gaussian data with application to WiFi indoor positioning},
DOI={10.1109/ICASSP.2013.6638353},
booktitle={38th International Conference on Acoustics, Speech, and Signal Processing
(ICASSP 2013)}, author={Hoang, Manh Kha and Haeb-Umbach, Reinhold}, year={2013},
pages={3721–3725} }'
chicago: Hoang, Manh Kha, and Reinhold Haeb-Umbach. “Parameter Estimation and Classification
of Censored Gaussian Data with Application to WiFi Indoor Positioning.” In 38th
International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2013),
3721–25, 2013. https://doi.org/10.1109/ICASSP.2013.6638353.
ieee: M. K. Hoang and R. Haeb-Umbach, “Parameter estimation and classification of
censored Gaussian data with application to WiFi indoor positioning,” in 38th
International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2013),
2013, pp. 3721–3725.
mla: Hoang, Manh Kha, and Reinhold Haeb-Umbach. “Parameter Estimation and Classification
of Censored Gaussian Data with Application to WiFi Indoor Positioning.” 38th
International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2013),
2013, pp. 3721–25, doi:10.1109/ICASSP.2013.6638353.
short: 'M.K. Hoang, R. Haeb-Umbach, in: 38th International Conference on Acoustics,
Speech, and Signal Processing (ICASSP 2013), 2013, pp. 3721–3725.'
date_created: 2019-07-12T05:28:48Z
date_updated: 2022-01-06T06:51:09Z
department:
- _id: '54'
doi: 10.1109/ICASSP.2013.6638353
keyword:
- Gaussian processes
- Global Positioning System
- convergence
- expectation-maximisation algorithm
- fingerprint identification
- indoor radio
- signal classification
- wireless LAN
- EM algorithm
- ML estimation
- WiFi indoor positioning
- censored Gaussian data classification
- clipped data
- convergence properties
- expectation maximization algorithm
- fingerprinting method
- maximum likelihood estimation
- optimal classification
- parameters estimation
- portable devices sensitivity
- signal strength measurements
- wireless LAN positioning systems
- Convergence
- IEEE 802.11 Standards
- Maximum likelihood estimation
- Parameter estimation
- Position measurement
- Training
- Indoor positioning
- censored data
- expectation maximization
- signal strength
- wireless LAN
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://groups.uni-paderborn.de/nt/pubs/2013/HoHa2013.pdf
oa: '1'
page: 3721-3725
publication: 38th International Conference on Acoustics, Speech, and Signal Processing
(ICASSP 2013)
publication_identifier:
issn:
- 1520-6149
related_material:
link:
- description: Poster
relation: supplementary_material
url: https://groups.uni-paderborn.de/nt/pubs/2013/HoHa2013_Poster.pdf
status: public
title: Parameter estimation and classification of censored Gaussian data with application
to WiFi indoor positioning
type: conference
user_id: '44006'
year: '2013'
...
---
_id: '11726'
abstract:
- lang: eng
text: In this paper we present a robust location estimation algorithm especially
focused on the accuracy in vertical position. A loosely-coupled error state space
Kalman filter, which fuses sensor data of an Inertial Measurement Unit and the
output of a Global Positioning System device, is augmented by height information
from an altitude measurement unit. This unit consists of a barometric altimeter
whose output is fused with topographic map information by a Kalman filter to provide
robust information about the current vertical user position. These data replace
the less reliable vertical position information provided the GPS device. It is
shown that typical barometric errors like thermal divergences and fluctuations
in the pressure due to changing weather conditions can be compensated by the topographic
map information and the barometric error Kalman filter. The resulting height information
is shown not only to be more reliable than height information provided by GPS.
It also turns out that it leads to better attitude and thus better overall localization
estimation accuracy due to the coupling of spatial orientations via the Direct
Cosine Matrix. Results are presented both for artificially generated and field
test data, where the user is moving by car.
author:
- first_name: Maik
full_name: Bevermeier, Maik
last_name: Bevermeier
- first_name: Oliver
full_name: Walter, Oliver
last_name: Walter
- first_name: Sven
full_name: Peschke, Sven
last_name: Peschke
- first_name: Reinhold
full_name: Haeb-Umbach, Reinhold
id: '242'
last_name: Haeb-Umbach
citation:
ama: 'Bevermeier M, Walter O, Peschke S, Haeb-Umbach R. Barometric height estimation
combined with map-matching in a loosely-coupled Kalman-filter. In: 7th Workshop
on Positioning Navigation and Communication (WPNC 2010). ; 2010:128-134. doi:10.1109/WPNC.2010.5650745'
apa: Bevermeier, M., Walter, O., Peschke, S., & Haeb-Umbach, R. (2010). Barometric
height estimation combined with map-matching in a loosely-coupled Kalman-filter.
In 7th Workshop on Positioning Navigation and Communication (WPNC 2010)
(pp. 128–134). https://doi.org/10.1109/WPNC.2010.5650745
bibtex: '@inproceedings{Bevermeier_Walter_Peschke_Haeb-Umbach_2010, title={Barometric
height estimation combined with map-matching in a loosely-coupled Kalman-filter},
DOI={10.1109/WPNC.2010.5650745},
booktitle={7th Workshop on Positioning Navigation and Communication (WPNC 2010)},
author={Bevermeier, Maik and Walter, Oliver and Peschke, Sven and Haeb-Umbach,
Reinhold}, year={2010}, pages={128–134} }'
chicago: Bevermeier, Maik, Oliver Walter, Sven Peschke, and Reinhold Haeb-Umbach.
“Barometric Height Estimation Combined with Map-Matching in a Loosely-Coupled
Kalman-Filter.” In 7th Workshop on Positioning Navigation and Communication
(WPNC 2010), 128–34, 2010. https://doi.org/10.1109/WPNC.2010.5650745.
ieee: M. Bevermeier, O. Walter, S. Peschke, and R. Haeb-Umbach, “Barometric height
estimation combined with map-matching in a loosely-coupled Kalman-filter,” in
7th Workshop on Positioning Navigation and Communication (WPNC 2010), 2010,
pp. 128–134.
mla: Bevermeier, Maik, et al. “Barometric Height Estimation Combined with Map-Matching
in a Loosely-Coupled Kalman-Filter.” 7th Workshop on Positioning Navigation
and Communication (WPNC 2010), 2010, pp. 128–34, doi:10.1109/WPNC.2010.5650745.
short: 'M. Bevermeier, O. Walter, S. Peschke, R. Haeb-Umbach, in: 7th Workshop on
Positioning Navigation and Communication (WPNC 2010), 2010, pp. 128–134.'
date_created: 2019-07-12T05:27:04Z
date_updated: 2022-01-06T06:51:07Z
department:
- _id: '54'
doi: 10.1109/WPNC.2010.5650745
keyword:
- altitude measurement unit
- barometers
- barometric altimeter
- barometric error Kalman filter
- barometric height estimation
- direct cosine matrix
- global positioning system
- Global Positioning System
- GPS device
- height information
- height measurement
- inertial measurement unit
- Kalman filters
- loosely-coupled error state space Kalman filter
- loosely-coupled Kalman-filter
- map matching
- robust information
- robust location estimation
- sensor fusion
- topographic map information
- vertical user position
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://groups.uni-paderborn.de/nt/pubs/2010/BeWaPeHa10.pdf
oa: '1'
page: 128-134
publication: 7th Workshop on Positioning Navigation and Communication (WPNC 2010)
status: public
title: Barometric height estimation combined with map-matching in a loosely-coupled
Kalman-filter
type: conference
user_id: '44006'
year: '2010'
...
---
_id: '21774'
author:
- first_name: Harald
full_name: Fricke, Harald
last_name: Fricke
- first_name: Andreas
full_name: Elsner, Andreas
last_name: Elsner
- first_name: Reiner
full_name: Weise, Reiner
last_name: Weise
- first_name: Matthias
full_name: Bolte, Matthias
last_name: Bolte
- first_name: Jörg
full_name: van den Hoff, Jörg
last_name: van den Hoff
- first_name: Wolfgang
full_name: Burchert, Wolfgang
last_name: Burchert
- first_name: Gitta
full_name: Domik, Gitta
id: '90'
last_name: Domik
- first_name: Eva
full_name: Fricke, Eva
last_name: Fricke
citation:
ama: 'Fricke H, Elsner A, Weise R, et al. Quantitative myocardial perfusion PET
combined with coronary anatomy derived from CT angiography: Validation of a new
fusion and visualisation software. Zeitschrift für Medizinische Physik.
2009;19(3):182-188. doi:10.1016/j.zemedi.2009.05.005'
apa: 'Fricke, H., Elsner, A., Weise, R., Bolte, M., van den Hoff, J., Burchert,
W., … Fricke, E. (2009). Quantitative myocardial perfusion PET combined with coronary
anatomy derived from CT angiography: Validation of a new fusion and visualisation
software. Zeitschrift Für Medizinische Physik, 19(3), 182–188. https://doi.org/10.1016/j.zemedi.2009.05.005'
bibtex: '@article{Fricke_Elsner_Weise_Bolte_van den Hoff_Burchert_Domik_Fricke_2009,
title={Quantitative myocardial perfusion PET combined with coronary anatomy derived
from CT angiography: Validation of a new fusion and visualisation software}, volume={19},
DOI={10.1016/j.zemedi.2009.05.005},
number={3}, journal={Zeitschrift für Medizinische Physik}, author={Fricke, Harald
and Elsner, Andreas and Weise, Reiner and Bolte, Matthias and van den Hoff, Jörg
and Burchert, Wolfgang and Domik, Gitta and Fricke, Eva}, year={2009}, pages={182–188}
}'
chicago: 'Fricke, Harald, Andreas Elsner, Reiner Weise, Matthias Bolte, Jörg van
den Hoff, Wolfgang Burchert, Gitta Domik, and Eva Fricke. “Quantitative Myocardial
Perfusion PET Combined with Coronary Anatomy Derived from CT Angiography: Validation
of a New Fusion and Visualisation Software.” Zeitschrift Für Medizinische Physik
19, no. 3 (2009): 182–88. https://doi.org/10.1016/j.zemedi.2009.05.005.'
ieee: 'H. Fricke et al., “Quantitative myocardial perfusion PET combined
with coronary anatomy derived from CT angiography: Validation of a new fusion
and visualisation software,” Zeitschrift für Medizinische Physik, vol.
19, no. 3, pp. 182–188, 2009.'
mla: 'Fricke, Harald, et al. “Quantitative Myocardial Perfusion PET Combined with
Coronary Anatomy Derived from CT Angiography: Validation of a New Fusion and Visualisation
Software.” Zeitschrift Für Medizinische Physik, vol. 19, no. 3, 2009, pp.
182–88, doi:10.1016/j.zemedi.2009.05.005.'
short: H. Fricke, A. Elsner, R. Weise, M. Bolte, J. van den Hoff, W. Burchert, G.
Domik, E. Fricke, Zeitschrift Für Medizinische Physik 19 (2009) 182–188.
date_created: 2021-04-25T17:06:55Z
date_updated: 2022-01-06T06:55:13Z
department:
- _id: '65'
doi: 10.1016/j.zemedi.2009.05.005
intvolume: ' 19'
issue: '3'
keyword:
- Coronary artery disease
- CT angiography
- cardiac PET
- quantitative perfusion measurement
- Koronare Herzerkrankung
- CT-Angiographie
- PET
- quantitative Perfusionsmessung
language:
- iso: eng
page: 182-188
publication: Zeitschrift für Medizinische Physik
publication_identifier:
issn:
- 0939-3889
status: public
title: 'Quantitative myocardial perfusion PET combined with coronary anatomy derived
from CT angiography: Validation of a new fusion and visualisation software'
type: journal_article
user_id: '14955'
volume: 19
year: '2009'
...
---
_id: '11723'
abstract:
- lang: eng
text: In this paper we present a novel vehicle tracking algorithm, which is based
on multi-level sensor fusion of GPS (global positioning system) with Inertial
Measurement Unit sensor data. It is shown that the robustness of the system to
temporary dropouts of the GPS signal, which may occur due to limited visibility
of satellites in narrow street canyons or tunnels, is greatly improved by sensor
fusion. We further demonstrate how the observation and state noise covariances
of the employed Kalman filters can be estimated alongside the filtering by an
application of the Expectation-Maximization algorithm. The proposed time-variant
multi-level Kalman filter is shown to outperform an Interacting Multiple Model
approach while at the same time being computationally less demanding.
author:
- first_name: Maik
full_name: Bevermeier, Maik
last_name: Bevermeier
- first_name: Sven
full_name: Peschke, Sven
last_name: Peschke
- first_name: Reinhold
full_name: Haeb-Umbach, Reinhold
id: '242'
last_name: Haeb-Umbach
citation:
ama: 'Bevermeier M, Peschke S, Haeb-Umbach R. Robust vehicle localization based
on multi-level sensor fusion and online parameter estimation. In: 6th Workshop
on Positioning Navigation and Communication (WPNC 2009). ; 2009:235-242. doi:10.1109/WPNC.2009.4907833'
apa: Bevermeier, M., Peschke, S., & Haeb-Umbach, R. (2009). Robust vehicle localization
based on multi-level sensor fusion and online parameter estimation. In 6th
Workshop on Positioning Navigation and Communication (WPNC 2009) (pp. 235–242).
https://doi.org/10.1109/WPNC.2009.4907833
bibtex: '@inproceedings{Bevermeier_Peschke_Haeb-Umbach_2009, title={Robust vehicle
localization based on multi-level sensor fusion and online parameter estimation},
DOI={10.1109/WPNC.2009.4907833},
booktitle={6th Workshop on Positioning Navigation and Communication (WPNC 2009)},
author={Bevermeier, Maik and Peschke, Sven and Haeb-Umbach, Reinhold}, year={2009},
pages={235–242} }'
chicago: Bevermeier, Maik, Sven Peschke, and Reinhold Haeb-Umbach. “Robust Vehicle
Localization Based on Multi-Level Sensor Fusion and Online Parameter Estimation.”
In 6th Workshop on Positioning Navigation and Communication (WPNC 2009),
235–42, 2009. https://doi.org/10.1109/WPNC.2009.4907833.
ieee: M. Bevermeier, S. Peschke, and R. Haeb-Umbach, “Robust vehicle localization
based on multi-level sensor fusion and online parameter estimation,” in 6th
Workshop on Positioning Navigation and Communication (WPNC 2009), 2009, pp.
235–242.
mla: Bevermeier, Maik, et al. “Robust Vehicle Localization Based on Multi-Level
Sensor Fusion and Online Parameter Estimation.” 6th Workshop on Positioning
Navigation and Communication (WPNC 2009), 2009, pp. 235–42, doi:10.1109/WPNC.2009.4907833.
short: 'M. Bevermeier, S. Peschke, R. Haeb-Umbach, in: 6th Workshop on Positioning
Navigation and Communication (WPNC 2009), 2009, pp. 235–242.'
date_created: 2019-07-12T05:27:01Z
date_updated: 2022-01-06T06:51:07Z
department:
- _id: '54'
doi: 10.1109/WPNC.2009.4907833
keyword:
- covariance matrices
- expectation-maximisation algorithm
- expectation-maximization algorithm
- global positioning system
- Global Positioning System
- GPS
- inertial measurement unit
- interacting multiple model approach
- Kalman filters
- multilevel sensor fusion
- narrow street canyons
- narrow tunnels
- online parameter estimation
- parameter estimation
- road vehicles
- robust vehicle localization
- sensor fusion
- state noise covariances
- time-variant multilevel Kalman filter
- vehicle tracking algorithm
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://groups.uni-paderborn.de/nt/pubs/2009/BePeHa09.pdf
oa: '1'
page: 235-242
publication: 6th Workshop on Positioning Navigation and Communication (WPNC 2009)
status: public
title: Robust vehicle localization based on multi-level sensor fusion and online parameter
estimation
type: conference
user_id: '44006'
year: '2009'
...
---
_id: '11724'
abstract:
- lang: eng
text: In this paper we present a novel vehicle tracking method which is based on
multi-stage Kalman filtering of GPS and IMU sensor data. After individual Kalman
filtering of GPS and IMU measurements the estimates of the orientation of the
vehicle are combined in an optimal manner to improve the robustness towards drift
errors. The tracking algorithm incorporates the estimation of time-variant covariance
parameters by using an iterative block Expectation-Maximization algorithm to account
for time-variant driving conditions and measurement quality. The proposed system
is compared to an interacting multiple model approach (IMM) and achieves improved
localization accuracy at lower computational complexity. Furthermore we show how
the joint parameter estimation and localizaiton can be conducted with streaming
input data to be able to track vehicles in a real driving environment.
author:
- first_name: Maik
full_name: Bevermeier, Maik
last_name: Bevermeier
- first_name: Sven
full_name: Peschke, Sven
last_name: Peschke
- first_name: Reinhold
full_name: Haeb-Umbach, Reinhold
id: '242'
last_name: Haeb-Umbach
citation:
ama: 'Bevermeier M, Peschke S, Haeb-Umbach R. Joint Parameter Estimation and Tracking
in a Multi-Stage Kalman Filter for Vehicle Positioning. In: IEEE 69th Vehicular
Technology Conference (VTC 2009 Spring). ; 2009:1-5. doi:10.1109/VETECS.2009.5073634'
apa: Bevermeier, M., Peschke, S., & Haeb-Umbach, R. (2009). Joint Parameter
Estimation and Tracking in a Multi-Stage Kalman Filter for Vehicle Positioning.
In IEEE 69th Vehicular Technology Conference (VTC 2009 Spring) (pp. 1–5).
https://doi.org/10.1109/VETECS.2009.5073634
bibtex: '@inproceedings{Bevermeier_Peschke_Haeb-Umbach_2009, title={Joint Parameter
Estimation and Tracking in a Multi-Stage Kalman Filter for Vehicle Positioning},
DOI={10.1109/VETECS.2009.5073634},
booktitle={IEEE 69th Vehicular Technology Conference (VTC 2009 Spring)}, author={Bevermeier,
Maik and Peschke, Sven and Haeb-Umbach, Reinhold}, year={2009}, pages={1–5} }'
chicago: Bevermeier, Maik, Sven Peschke, and Reinhold Haeb-Umbach. “Joint Parameter
Estimation and Tracking in a Multi-Stage Kalman Filter for Vehicle Positioning.”
In IEEE 69th Vehicular Technology Conference (VTC 2009 Spring), 1–5, 2009.
https://doi.org/10.1109/VETECS.2009.5073634.
ieee: M. Bevermeier, S. Peschke, and R. Haeb-Umbach, “Joint Parameter Estimation
and Tracking in a Multi-Stage Kalman Filter for Vehicle Positioning,” in IEEE
69th Vehicular Technology Conference (VTC 2009 Spring), 2009, pp. 1–5.
mla: Bevermeier, Maik, et al. “Joint Parameter Estimation and Tracking in a Multi-Stage
Kalman Filter for Vehicle Positioning.” IEEE 69th Vehicular Technology Conference
(VTC 2009 Spring), 2009, pp. 1–5, doi:10.1109/VETECS.2009.5073634.
short: 'M. Bevermeier, S. Peschke, R. Haeb-Umbach, in: IEEE 69th Vehicular Technology
Conference (VTC 2009 Spring), 2009, pp. 1–5.'
date_created: 2019-07-12T05:27:02Z
date_updated: 2022-01-06T06:51:07Z
department:
- _id: '54'
doi: 10.1109/VETECS.2009.5073634
keyword:
- computational complexity
- expectation-maximisation algorithm
- Global Positioning System
- inertial measurement unit
- inertial navigation
- interacting multiple model
- iterative block expectation-maximization algorithm
- Kalman filters
- multi-stage Kalman filter
- parameter estimation
- road vehicles
- vehicle positioning
- vehicle tracking
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://groups.uni-paderborn.de/nt/pubs/2009/BePeHa09-1.pdf
oa: '1'
page: 1-5
publication: IEEE 69th Vehicular Technology Conference (VTC 2009 Spring)
status: public
title: Joint Parameter Estimation and Tracking in a Multi-Stage Kalman Filter for
Vehicle Positioning
type: conference
user_id: '44006'
year: '2009'
...
---
_id: '11881'
abstract:
- lang: eng
text: A combination of GPS (global positioning system) and INS (inertial navigation
system) is known to provide high precision and highly robust vehicle localization.
Notably during times when the GPS signal has a poor quality, e.g. due to the lack
of a sufficiently large number of visible satellites, the INS, which may consist
of a gyroscope and an odometer, will lead to improved positioning accuracy. In
this paper we show how velocity information obtained from GSM (global system for
mobile communications) signalling, rather than from a tachometer, can be used
together with a gyroscope sensor to support localization in the presence of temporarily
unavailable GPS data. We propose a sensor fusion system architecture and present
simulation results that show the effectiveness of this approach.
author:
- first_name: Sven
full_name: Peschke, Sven
last_name: Peschke
- first_name: Maik
full_name: Bevermeier, Maik
last_name: Bevermeier
- first_name: Reinhold
full_name: Haeb-Umbach, Reinhold
id: '242'
last_name: Haeb-Umbach
citation:
ama: 'Peschke S, Bevermeier M, Haeb-Umbach R. A GPS positioning approach exploiting
GSM velocity estimates. In: 6th Workshop on Positioning Navigation and Communication
(WPNC 2009). ; 2009:195-202. doi:10.1109/WPNC.2009.4907827'
apa: Peschke, S., Bevermeier, M., & Haeb-Umbach, R. (2009). A GPS positioning
approach exploiting GSM velocity estimates. In 6th Workshop on Positioning
Navigation and Communication (WPNC 2009) (pp. 195–202). https://doi.org/10.1109/WPNC.2009.4907827
bibtex: '@inproceedings{Peschke_Bevermeier_Haeb-Umbach_2009, title={A GPS positioning
approach exploiting GSM velocity estimates}, DOI={10.1109/WPNC.2009.4907827},
booktitle={6th Workshop on Positioning Navigation and Communication (WPNC 2009)},
author={Peschke, Sven and Bevermeier, Maik and Haeb-Umbach, Reinhold}, year={2009},
pages={195–202} }'
chicago: Peschke, Sven, Maik Bevermeier, and Reinhold Haeb-Umbach. “A GPS Positioning
Approach Exploiting GSM Velocity Estimates.” In 6th Workshop on Positioning
Navigation and Communication (WPNC 2009), 195–202, 2009. https://doi.org/10.1109/WPNC.2009.4907827.
ieee: S. Peschke, M. Bevermeier, and R. Haeb-Umbach, “A GPS positioning approach
exploiting GSM velocity estimates,” in 6th Workshop on Positioning Navigation
and Communication (WPNC 2009), 2009, pp. 195–202.
mla: Peschke, Sven, et al. “A GPS Positioning Approach Exploiting GSM Velocity Estimates.”
6th Workshop on Positioning Navigation and Communication (WPNC 2009), 2009,
pp. 195–202, doi:10.1109/WPNC.2009.4907827.
short: 'S. Peschke, M. Bevermeier, R. Haeb-Umbach, in: 6th Workshop on Positioning
Navigation and Communication (WPNC 2009), 2009, pp. 195–202.'
date_created: 2019-07-12T05:30:04Z
date_updated: 2022-01-06T06:51:11Z
department:
- _id: '54'
doi: 10.1109/WPNC.2009.4907827
keyword:
- cellular radio
- distance measurement
- global positioning system
- Global Positioning System
- global system for mobile communications
- GPS positioning approach
- GSM velocity
- gyroscopes
- gyroscope sensor
- inertial navigation
- inertial navigation system
- odometer
- sensor fusion system architecture
- sensors
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://groups.uni-paderborn.de/nt/pubs/2009/PeBeHa09-1.pdf
oa: '1'
page: 195-202
publication: 6th Workshop on Positioning Navigation and Communication (WPNC 2009)
status: public
title: A GPS positioning approach exploiting GSM velocity estimates
type: conference
user_id: '44006'
year: '2009'
...
---
_id: '9568'
abstract:
- lang: eng
text: A simple pre-stress estimate method of Langevin transducers is studied. The
measurement setup consists of a capacitor, an impedance converter and a voltmeter.
Based on the piezoelectric equation and the basic circuit theory, the mathematical
expression between the pre-stress and the voltage across the capacitor is derived.
The pre-stress level can then be calculated out of the measurement of the capacitor
voltage. In order to evaluate the precision of this method, a force washer is
used to measure the pre-stress of the Langevin transducer. The result shows the
pre-stress level obtained from this method is 30-40\% higher than the pre-stress
level measured by the force washer. This method is simple and can be used to estimate
the pre-stress of various Langevin transducers. The precision of this method can
be raised if d33 is identified under different pre-stress levels.
author:
- first_name: Fu
full_name: Bo, Fu
last_name: Bo
- first_name: Li
full_name: Ting, Li
last_name: Ting
- first_name: Tobias
full_name: Hemsel, Tobias
id: '210'
last_name: Hemsel
citation:
ama: 'Bo F, Ting L, Hemsel T. A simple pre-stress estimating method of langevin
transducers. In: Piezoelectricity, Acoustic Waves, and Device Applications,
2008. SPAWDA 2008. Symposium On. ; 2008:324-327. doi:10.1109/SPAWDA.2008.4775801'
apa: Bo, F., Ting, L., & Hemsel, T. (2008). A simple pre-stress estimating method
of langevin transducers. In Piezoelectricity, Acoustic Waves, and Device Applications,
2008. SPAWDA 2008. Symposium on (pp. 324–327). https://doi.org/10.1109/SPAWDA.2008.4775801
bibtex: '@inproceedings{Bo_Ting_Hemsel_2008, title={A simple pre-stress estimating
method of langevin transducers}, DOI={10.1109/SPAWDA.2008.4775801},
booktitle={Piezoelectricity, Acoustic Waves, and Device Applications, 2008. SPAWDA
2008. Symposium on}, author={Bo, Fu and Ting, Li and Hemsel, Tobias}, year={2008},
pages={324–327} }'
chicago: Bo, Fu, Li Ting, and Tobias Hemsel. “A Simple Pre-Stress Estimating Method
of Langevin Transducers.” In Piezoelectricity, Acoustic Waves, and Device Applications,
2008. SPAWDA 2008. Symposium On, 324–27, 2008. https://doi.org/10.1109/SPAWDA.2008.4775801.
ieee: F. Bo, L. Ting, and T. Hemsel, “A simple pre-stress estimating method of langevin
transducers,” in Piezoelectricity, Acoustic Waves, and Device Applications,
2008. SPAWDA 2008. Symposium on, 2008, pp. 324–327.
mla: Bo, Fu, et al. “A Simple Pre-Stress Estimating Method of Langevin Transducers.”
Piezoelectricity, Acoustic Waves, and Device Applications, 2008. SPAWDA 2008.
Symposium On, 2008, pp. 324–27, doi:10.1109/SPAWDA.2008.4775801.
short: 'F. Bo, L. Ting, T. Hemsel, in: Piezoelectricity, Acoustic Waves, and Device
Applications, 2008. SPAWDA 2008. Symposium On, 2008, pp. 324–327.'
date_created: 2019-04-29T11:16:13Z
date_updated: 2022-01-06T07:04:16Z
department:
- _id: '151'
doi: 10.1109/SPAWDA.2008.4775801
keyword:
- capacitors
- impedance convertors
- piezoelectric transducers
- stress analysis
- Langevin transducers
- basic circuit theory
- capacitor
- impedance converter
- piezoelectric equation
- pre-stress estimating method
- voltmeter
- Capacitors
- Educational institutions
- Equations
- Force measurement
- Impedance measurement
- Manufacturing
- Mechatronics
- Piezoelectric transducers
- Voltage
- Voltmeters
- Langevin transducer
- capacitor
- piezoelectric element
- pre-stress
language:
- iso: eng
page: 324-327
publication: Piezoelectricity, Acoustic Waves, and Device Applications, 2008. SPAWDA
2008. Symposium on
status: public
title: A simple pre-stress estimating method of langevin transducers
type: conference
user_id: '55222'
year: '2008'
...
---
_id: '9576'
abstract:
- lang: eng
text: 'In neurosurgery, delineation of tumor boundaries during resection of brain
tumors is of substantial relevance. During operation distinction between tumor
and healthy tissue rely on the abilities of the surgeon based on visual and tactile
differentiation. In this paper a high sensitivity actuator-sensor system using
a piezoelectric bimorph is presented. Frequency shift and transfer function of
the bimorphpsilas voltages are detected and evaluated. Sensorpsilas sensitivity
is evaluated using two frequency controls strategies: A phase-locked loop (PLL)
and a self-oscillating circuit. Results of measurements conducted on gel-phantoms
are presented and discussed.'
author:
- first_name: David Oliva
full_name: Uribe, David Oliva
last_name: Uribe
- first_name: Ralf
full_name: Stroop, Ralf
last_name: Stroop
- first_name: Tobias
full_name: Hemsel, Tobias
id: '210'
last_name: Hemsel
- first_name: Jörg
full_name: Wallaschek, Jörg
last_name: Wallaschek
citation:
ama: 'Uribe DO, Stroop R, Hemsel T, Wallaschek J. Development of a biomedical tissue
differentiation system using piezoelectric actuators. In: Frequency Control
Symposium, 2008 IEEE International. ; 2008:91-94. doi:10.1109/FREQ.2008.4622963'
apa: Uribe, D. O., Stroop, R., Hemsel, T., & Wallaschek, J. (2008). Development
of a biomedical tissue differentiation system using piezoelectric actuators. In
Frequency Control Symposium, 2008 IEEE International (pp. 91–94). https://doi.org/10.1109/FREQ.2008.4622963
bibtex: '@inproceedings{Uribe_Stroop_Hemsel_Wallaschek_2008, title={Development
of a biomedical tissue differentiation system using piezoelectric actuators},
DOI={10.1109/FREQ.2008.4622963},
booktitle={Frequency Control Symposium, 2008 IEEE International}, author={Uribe,
David Oliva and Stroop, Ralf and Hemsel, Tobias and Wallaschek, Jörg}, year={2008},
pages={91–94} }'
chicago: Uribe, David Oliva, Ralf Stroop, Tobias Hemsel, and Jörg Wallaschek. “Development
of a Biomedical Tissue Differentiation System Using Piezoelectric Actuators.”
In Frequency Control Symposium, 2008 IEEE International, 91–94, 2008. https://doi.org/10.1109/FREQ.2008.4622963.
ieee: D. O. Uribe, R. Stroop, T. Hemsel, and J. Wallaschek, “Development of a biomedical
tissue differentiation system using piezoelectric actuators,” in Frequency
Control Symposium, 2008 IEEE International, 2008, pp. 91–94.
mla: Uribe, David Oliva, et al. “Development of a Biomedical Tissue Differentiation
System Using Piezoelectric Actuators.” Frequency Control Symposium, 2008 IEEE
International, 2008, pp. 91–94, doi:10.1109/FREQ.2008.4622963.
short: 'D.O. Uribe, R. Stroop, T. Hemsel, J. Wallaschek, in: Frequency Control Symposium,
2008 IEEE International, 2008, pp. 91–94.'
date_created: 2019-04-29T13:07:39Z
date_updated: 2022-01-06T07:04:16Z
department:
- _id: '151'
doi: 10.1109/FREQ.2008.4622963
keyword:
- biomedical measurement
- brain
- cancer
- neurophysiology
- phantoms
- phase locked loops
- piezoelectric actuators
- surgery
- tactile sensors
- transfer functions
- tumours
- PLL
- biomedical tissue differentiation system
- brain tumor resection
- frequency control
- frequency shift
- gel-phantom
- high sensitivity actuator-sensor system
- neurosurgery
- phase-locked loop
- piezoelectric actuators
- piezoelectric bimorph
- self-oscillating circuit
- sensor sensitivity
- tactile differentiation
- tactile sensor system
- transfer function
- tumor boundary
- visual differentiation
- Biomedical measurements
- Circuits
- Frequency control
- Neoplasms
- Neurosurgery
- Phase locked loops
- Piezoelectric actuators
- Surges
- Transfer functions
- Voltage
language:
- iso: eng
page: 91-94
publication: Frequency Control Symposium, 2008 IEEE International
publication_identifier:
issn:
- 1075-6787
quality_controlled: '1'
status: public
title: Development of a biomedical tissue differentiation system using piezoelectric
actuators
type: conference
user_id: '55222'
year: '2008'
...