Personal Navigation Algorithms Based on Wireless Networks and Inertial Sensors

Open access


The work aims at a development of positioning algorithm suitable for low-cost indoor or urban pedestrian navigation application. The sensor fusion was applied to increase the localization accuracy. Due to required low application cost only low grade inertial sensors and wireless network based ranging were taken into account. The wireless network was assumed to be preinstalled due to other required functionality (for example: building control) therefore only received signal strength (RSS) range measurement technique was considered. Wireless channel loss mapping method was proposed to overcome the natural uncertainties and restrictions in the RSS range measurements The available sensor and environment models are summarized first and the most appropriate ones are selected secondly. Their effective and novel application in the navigation task, and favorable fusion (Particle filtering) of all available information are the main objectives of this thesis.

If the inline PDF is not rendering correctly, you can download the PDF file here.

  • [1] FLUERASU A.—JARDAK N.—VERVISCH-PICOIS A.— SAMAMA N.: Gnss Repeater based Approach for Indoor Positioning: Current Status in European Navigation Conference Global Navigation Satellite Systems 2009.

  • [2] KEUNHO Y.—DAIJIN K.: Robust Location Tracking using a Dual Layer Particle Filter Pervasive and Mobile Computing 3 (03 2007) 209–232.

  • [3] SAVARESE C.—RABAEY J. M.—BEUTEL J.: Location in Distributed ad-hoc Wireless Sensor Networks in Proc. IEEE ICASSP ‘01 vol. 4 2001 pp. 2037–2040.

  • [4] PATWARI N.—HERO A. O.—PERKINS M.—CORREAL N. S.—O’DEA R. J.: Relative Location Estimation in Wireless Sensor Networks IEEE Transactions on Signal Processing 51 (08 2003) 2137–2148.

  • [5] PATWARI N.—ASH J. N.—KYPEROUNTAS S.—MOSES A. O. H. III R. L.—CORREAL N. S.: Locating the Nodes [Cooperative Localization in Wireless Sensor Networks IEEE Signal Processing Magazine 22 (04 2005) 54–69.

  • [6] FOX D.—HIGHTOWER J.—KAUZ H.—LIAO L.—PAT-TERSON D. J.: Bayesian Techniques for Location Estimation in Proceedings of the 2003 Workshop on Location-Aware Computing Oct 2003 pp. 16–18.

  • [7] GROVES P.D.: Principles of GNSS Inertial and Multi-Sensor Integrated Navigation Systems Artech House 2008.

  • [8] FARRELL J.: Aided Navigation: GPS with High Rate Sensors The MacGravy Hill Companies 2008.

  • [9] FOXLIN E.: Pedestrian Tracking with Shoe-Mounted Inertial Sensors IEEE Computer Graphics and Applications 25 (2005) 38–46.

  • [10] KRACH B.—ROBERTSON P.: Cascaded Estimation Architecture for Integration of Foot-Mounted Inertial Sensors in IEEE/ION Position Location and Navigation Symposium 2008 pp. 112–119.

  • [11] KUOROGI M.—KURATA T.: Personal Positioning based on Walking Locomotion Analysis with Self-Contained Sensors and a Wearable Camera in Proceedings of the 2nd IEEE/ACM International Symposium on Mixed and Augmented Reality 2003 pp. 103–112.

  • [12] ROBERTSON P.—KRACH B.—KHIDER M.: Slam Dance: Inertial-based Joint Mapping and Positioning for Pedestrian Navigation Inside GNSS 5 (2010) 48–59.

  • [13] MATTHEWS C. J.—KETEMAA Y.—GEBRE-EGZIABHER D.—SCHWARTZ M.: In-Situ Step Size Estimation using a Kinetic Model of Human Gait in ION GNSS (2010).

  • [14] THRUN S.—BURGARD W.—FOX D.: Probabilistic Robotics The MIT Press 55 Hayward street Cambridge 2005.

  • [15] COULSON A. J.—WILLIAMSON A. G.—VAUGHAN R. G.: A Statistical Basis for Lognormal Shadowing Effects in Multi-path Fading Channels IEEE Transactions on Communications 46 (04 1998) 494–502.

  • [16] HASHEMI H.: The Indoor Radio Propagation Channel Proceedings of the IEEE 81 (1993) 943–968.

  • [17] SEYBOLD J. S.: Introduction to RF Propagation John Wiley & Sons Inc. Hoboken New Jersey 2005.

  • [18] ANGERMANN M.—FRIESE A.—KHIDER M.—KRACH B.—KRACK K.—ROBERTSON P.: A Reference Measurement Data Set for Multisensor Pedestrian Navigation with Accurate Ground Truthinbook in European Navigation Conference Global Navigation Satellite Systems.

  • [19] KAINA Z.: Personal Navigation Based on Wireless Networks and Inertial Sensors Brno University of Technology Faculty of Electrical Engineering and Communication 2014 thesis. Received 17 December 2013

Journal information
Impact Factor

IMPACT FACTOR 2018: 0.636
5-year IMPACT FACTOR: 0.663

CiteScore 2018: 0.88

SCImago Journal Rank (SJR) 2018: 0.200
Source Normalized Impact per Paper (SNIP) 2018: 0.771

Cited By
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 167 65 6
PDF Downloads 89 39 4