---
_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: <i>6th Workshop
    on Positioning Navigation and Communication (WPNC 2009)</i>. ; 2009:235-242. doi:<a
    href="https://doi.org/10.1109/WPNC.2009.4907833">10.1109/WPNC.2009.4907833</a>'
  apa: Bevermeier, M., Peschke, S., &#38; Haeb-Umbach, R. (2009). Robust vehicle localization
    based on multi-level sensor fusion and online parameter estimation. In <i>6th
    Workshop on Positioning Navigation and Communication (WPNC 2009)</i> (pp. 235–242).
    <a href="https://doi.org/10.1109/WPNC.2009.4907833">https://doi.org/10.1109/WPNC.2009.4907833</a>
  bibtex: '@inproceedings{Bevermeier_Peschke_Haeb-Umbach_2009, title={Robust vehicle
    localization based on multi-level sensor fusion and online parameter estimation},
    DOI={<a href="https://doi.org/10.1109/WPNC.2009.4907833">10.1109/WPNC.2009.4907833</a>},
    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 <i>6th Workshop on Positioning Navigation and Communication (WPNC 2009)</i>,
    235–42, 2009. <a href="https://doi.org/10.1109/WPNC.2009.4907833">https://doi.org/10.1109/WPNC.2009.4907833</a>.
  ieee: M. Bevermeier, S. Peschke, and R. Haeb-Umbach, “Robust vehicle localization
    based on multi-level sensor fusion and online parameter estimation,” in <i>6th
    Workshop on Positioning Navigation and Communication (WPNC 2009)</i>, 2009, pp.
    235–242.
  mla: Bevermeier, Maik, et al. “Robust Vehicle Localization Based on Multi-Level
    Sensor Fusion and Online Parameter Estimation.” <i>6th Workshop on Positioning
    Navigation and Communication (WPNC 2009)</i>, 2009, pp. 235–42, doi:<a href="https://doi.org/10.1109/WPNC.2009.4907833">10.1109/WPNC.2009.4907833</a>.
  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: <i>IEEE 69th Vehicular
    Technology Conference (VTC 2009 Spring)</i>. ; 2009:1-5. doi:<a href="https://doi.org/10.1109/VETECS.2009.5073634">10.1109/VETECS.2009.5073634</a>'
  apa: Bevermeier, M., Peschke, S., &#38; Haeb-Umbach, R. (2009). Joint Parameter
    Estimation and Tracking in a Multi-Stage Kalman Filter for Vehicle Positioning.
    In <i>IEEE 69th Vehicular Technology Conference (VTC 2009 Spring)</i> (pp. 1–5).
    <a href="https://doi.org/10.1109/VETECS.2009.5073634">https://doi.org/10.1109/VETECS.2009.5073634</a>
  bibtex: '@inproceedings{Bevermeier_Peschke_Haeb-Umbach_2009, title={Joint Parameter
    Estimation and Tracking in a Multi-Stage Kalman Filter for Vehicle Positioning},
    DOI={<a href="https://doi.org/10.1109/VETECS.2009.5073634">10.1109/VETECS.2009.5073634</a>},
    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 <i>IEEE 69th Vehicular Technology Conference (VTC 2009 Spring)</i>, 1–5, 2009.
    <a href="https://doi.org/10.1109/VETECS.2009.5073634">https://doi.org/10.1109/VETECS.2009.5073634</a>.
  ieee: M. Bevermeier, S. Peschke, and R. Haeb-Umbach, “Joint Parameter Estimation
    and Tracking in a Multi-Stage Kalman Filter for Vehicle Positioning,” in <i>IEEE
    69th Vehicular Technology Conference (VTC 2009 Spring)</i>, 2009, pp. 1–5.
  mla: Bevermeier, Maik, et al. “Joint Parameter Estimation and Tracking in a Multi-Stage
    Kalman Filter for Vehicle Positioning.” <i>IEEE 69th Vehicular Technology Conference
    (VTC 2009 Spring)</i>, 2009, pp. 1–5, doi:<a href="https://doi.org/10.1109/VETECS.2009.5073634">10.1109/VETECS.2009.5073634</a>.
  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'
...