Send article to a friendPrint

Sensor Fusion for Indoor Navigation

Latest updates

April 2012
New FootSLAM videos showing heading rate bias estimation here.

March 2012
FootSLAM is now realtime see here.
WiSLAM added.
FootSLAM Gallery started.

October 2011
Cooperative FootSLAM = FeetSLAM videos are now available here.

October 2010 - April 2012
Some notes, thoughts, and details concerning the implementation and behaviour of FootSLAM are being collected here.
Update Feb. 2011: FootSLAM exposes error in our building's reference layout.

September 2010
The new high precision datasets and videos on human odometry for our IPIN paper are now available here.

We also have a new page with videos, reference data sets and publications on human activity recognition here.

April 2010
New movies, slides and papers for FootSLAM with improved ZUPT aw well as PlaceSLAM are now available here.

September 2010
Movies, slides and papers for FootSLAM are available here.

May 2009
The reference data sets for multisensor pedestrian navigation that are introduced in our paper:

M. Angermann, A. Friese, M. Khider, B. Krach, K. Krack, P. Robertson
A Reference Measurement Data Set for Multisensor Pedestrian Navigation with Accurate Ground Truth [PDF]
European Navigation Conference (ENC-GNSS 2009), Naples, Italy, May 2009,

are now available at our download page.

General information

Positioning in buildings and other environments where GNSS reception is difficult will require a combination of sensors and other information such as building plans in order to function accurately. We are pursuing sensor fusion approaches that combine GNSS, foot mounted inertial sensors electronic compasses, baro-altimeters, maps and active RFID tags. A particularly powerful combination is INS step measurement in conjunction with maps which can converge to the correct position after less than a minute of motion. We have developed a two-layer sensor fusion architecture that operates with a Kalman filter where possible, and fuses other sensors and maps at a higher-level, lower rate, particle filter. In buildings, a few dispersed RFID tags or even moderately GNSS reception can significantly aid the overall positioning.

Combining complementary sensors through an optimal sensor fusion algorithm leads to synergetic effects and thus improves positioning.

Two-layer sensor fusion architecture that operates with a Kalman filter for the inertial stride estimation. Other sensors sensors and maps are fused at a higher-level, lower rate, particle filter.

Integration with map-matching in the particle filter: A pedestrian wearing the foot-mounted sensor walked the indicated track (black line). At each figure the posterior position estimate (green) becomes increasingly accurate, after 80s it is unimodal. Watch video [MPG].

Illustration of the pedestrian track that was estimated by a particle filter based upon our reference data set "March09Measurement09".

Videos and other media

• Youtube:

• Video: Fusion of GPS, foot-mounted INS, compass, baro-altimeter and building maps via a particle filter and a Kalman filter
• Video: Fusion of WLAN fingerprinting and a foot-mounted INS using an extended Kalman filter (work done in the EU-Project Daidalos):
• Video: Particles converging to the true position using a foot-mounted INS and map-aiding only
• Presentation on the integration of foot-mounted inertial sensors at PLANS 2008
• Indoor positioning overview poster

Papers on Pedestrian Navigation with Multisensor Fusion.

FootSLAM and PlaceSLAM papers here. Papers on mobility models here. Papers on Reference Data Sets for Multisensor Pedestrian Navigation here.

You can follow the ELIB link to our internal electronic library where you can download the paper as PDF and retrieve citation information, e.g. for BibTeX. Additional papers are available on our pages on related topics (links at the top left of this page).

Mohammed Khider, Thomas Jost, Elena Abdo Sánchez, Patrick Robertson and Michael Angermann
Bayesian Multi-sensor Navigation Incorporating Pseudo-ranges and Multipath Model, [ELIB]
Proceedings of the IEEE/ION PLANS 2010,
Indian Wells/Palm Springs, USA, May 2010

Thomas Jost, Mohammed Khider, Elena Abdo Sánchez,
Characterisation and Modelling of the Indoor Pseudorange Error using Low Cost Receivers, [ELIB]
Proceedings of the ION ITM 2010.
San Diego, USA, January 2010

Mohammed Khider, Susanna Kaiser, Patrick Robertson, Michael Angermann,
Maps And Floor Plans Enhanced 3D Movement Model For Pedestrian Navigation, [ELIB]
Proceedings of the ION GNSS 2009,
Georgia, USA, September 2009

Mohammed Khider, Susanna Kaiser, Patrick Robertson, Michael Angermann,
A Three Dimensional Movement Model For Pedestrian Navigation, [ELIB]
Proceedings of the European Navigation Conference - Global Navigation Satellite Systems (ENC-GNSS) 2009,
Napoli, Italy, May 2009

Mohammed Khider, Susanna Kaiser, Patrick Robertson, Michael Angermann,
A Novel Movement Model for Pedestrians Suitable for Personal Navigation, [ELIB]
Proceedings of the ION NTM 2008,
San Diego, USA, Jan 2008

B. Krach, P. Robertson
Cascaded Estimation Architecture for Integration of Foot-Mounted Inertial Sensors [ELIB]
Proc. 2008 IEEE/ION Position Location and Navigation Symposium (IEEE/ION PLANS 2008),
Monterey, California, USA, Mai 2008

M. Khider, S. Kaiser, P. Robertson, M. Angermann
The Effect of Maps-Enhanced Novel Movement Models on Pedestrian Navigation Performance [ELIB]
Proc. 12th European Navigation Conference (ENC GNSS 2008),
Toulouse, Frankreich, Apr. 2008

B. Krach, P. Robertson
Integration of Foot-Mounted Inertial Sensors into a Bayesian Location Estimation Framework [ELIB]
Proc. 5th Workshop on Positioning, Navigation and Communication 2008 (WPNC 2008),
Hannover, Germany, Mar. 2008

K. Wendlandt, P. Robertson, M. Khider, M. Angermann, K. Sukchaya
Demonstration of a Realtime Active-Tag RFID, Java Based Indoor Localization System using Particle Filtering [ELIB]
Adjunct Proc. 9th International Conference on Ubiquitous Computing (UBICOMP 2007),
Innsbruck, Austria, Sep. 2007

K. Wendlandt, M. Khider, M. Angermann, P. Robertson
Continuous location and direction estimation with multiple sensors using particle filtering [ELIB]
Proc. 2006 International Conference in Multisensor Fusion and Integration for Intelligent Systems (MFI 2006),
Heidelberg, Germany, Sep. 2006

K. Wendlandt, P. Robertson, M. Berbig
Indoor Localization with Probability Density Functionsd based on Bluetooth [ELIB]
Proc. 2005 Symposium on Personal Indoor and Mobile Radio Communications (PIMRC 2005),
Berlin, Germany, Sep. 2005

M. Angermann, J. Kammann, P. Robertson, A. Steingass, T. Strang
Software Representation for Heterogeneous Data Sources Within A Probabilistic Framework [ELIB]
Proc. 2001 International Symposium on Location Based Services for Cellular Users (LOCELLUS 2001),
Munich, Germany, Feb. 2001

Mohammed Khider
Implementation of a Simulator/Demonstrator for the SoftLocation Concept using Bayesian Filters, [ELIB]
Masterarbeit, S. 166, Universität Ulm (Ingenieurwissenschaften und Informatik) ,
Ulm, Germany, 2005