RSS-based Monte Carlo localisation for mobile sensor networks

Node localisation is a fundamental problem in wireless sensor networks. Many applications require the location information of sensor nodes. Received signal strength (RSS) is a simple and inexpensive approach for localisation purpose. However, the accuracy of RSS measurement is unpredictable owing to the nature of the radio frequency (RF) channel. An RSS-based Monte Carlo localisation scheme is proposed to sequentially estimate the location of mobile nodes, using the log-normal statistical model of RSS measurement. The RSS measurement is treated as the observation model in Monte Carlo method and the mobility feature of nodes as the transition model. Our method is widely applicable because the RSS function is easy to implement on nodes, and the mathematical model for mobile nodes may have non-analytic forms. Simulation results about localisation accuracy and cost show that this scheme is better than other methods.

[1]  S. Kay.  Fundamentals of statistical signal processing: estimation theory , 1993 .

[2]  B. R. Badrinath,et al.  DV Based Positioning in Ad Hoc Networks , 2003, Telecommun. Syst..

[3]  Wenping Chen.  Cooperative Limiting Localization Schemes for Wireless Sensor Networks , 2006, First International Conference on Innovative Computing, Information and Control - Volume I (ICICIC'06).

[4]  R.L. Moses,et al.  Locating the nodes: cooperative localization in wireless sensor networks , 2005, IEEE Signal Processing Magazine.

[5]  Fredrik Gustafsson,et al.  Particle filtering for quantized sensor information , 2005, 2005 13th European Signal Processing Conference.

[6]  Simon J. Godsill,et al.  On sequential Monte Carlo sampling methods for Bayesian filtering , 2000, Stat. Comput..

[7]  Cedric Nishan Canagarajah,et al.  Algorithms for Mobile Nodes Self-Localisation in Wireless Ad Hoc Networks , 2006, 2006 9th International Conference on Information Fusion.

[8]  Xiaoli Li,et al.  A sorted RSSI quantization based algorithm for sensor network localization , 2005, 11th International Conference on Parallel and Distributed Systems (ICPADS'05).

[9]  Rodney G. Vaughan,et al.  A statistical basis for lognormal shadowing effects in multipath fading channels , 1998, IEEE Trans. Commun..

[10]  Alfred O. Hero,et al.  Using proximity and quantized RSS for sensor localization in wireless networks , 2003, WSNA '03.

[11]  Terry Moore.  Global Positioning System: Theory and Practice: B. Hofmann-Wellenhof, H. Lichteneeger and J. Collins. Springer Wien New York, 2001. 5th revised edition. ISBN 3-211-82534-2. 240×165 mm. xxiii+382 pages. 45 figures and 76 tables. Price $59·95. , 2001, Journal of Navigation.

[12]  Tian He,et al.  Range-free localization schemes in large scale sensor network , 2003, MobiCom 2003.

[13]  Yu Hen Hu,et al.  Maximum likelihood multiple-source localization using acoustic energy measurements with wireless sensor networks , 2005, IEEE Transactions on Signal Processing.

[14]  B. R. Badrinath,et al.  Ad hoc positioning system (APS) using AOA , 2003, IEEE INFOCOM 2003. Twenty-second Annual Joint Conference of the IEEE Computer and Communications Societies (IEEE Cat. No.03CH37428).

[15]  Deborah Estrin,et al.  GPS-less low-cost outdoor localization for very small devices , 2000, IEEE Wirel. Commun..

[16]  Alfred O. Hero,et al.  Relative location estimation in wireless sensor networks , 2003, IEEE Trans. Signal Process..

[17]  Wolfram Burgard,et al.  Robust Monte Carlo localization for mobile robots , 2001, Artif. Intell..

[18]  Cesare Alippi,et al.  A RSSI-based and calibrated centralized localization technique for wireless sensor networks , 2006, Fourth Annual IEEE International Conference on Pervasive Computing and Communications Workshops (PERCOMW'06).

[19]  David Evans,et al.  Localization for mobile sensor networks , 2004, MobiCom '04.

[20]  Mani B. Srivastava,et al.  The bits and flops of the n-hop multilateration primitive for node localization problems , 2002, WSNA '02.

[21]  Paramvir Bahl,et al.  RADAR: an in-building RF-based user location and tracking system , 2000, Proceedings IEEE INFOCOM 2000. Conference on Computer Communications. Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies (Cat. No.00CH37064).

[22]  Theodore S. Rappaport,et al.  Wireless communications - principles and practice , 1996 .

[23]  Mingyan Liu,et al.  Sound mobility models , 2003, MobiCom '03.

[24]  Jan M. Rabaey,et al.  PicoRadio Supports Ad Hoc Ultra-Low Power Wireless Networking , 2000, Computer.

[25]  Steven Kay,et al.  Fundamentals Of Statistical Signal Processing , 2001 .

[26]  Hari Balakrishnan,et al.  6th ACM/IEEE International Conference on on Mobile Computing and Networking (ACM MOBICOM ’00) The Cricket Location-Support System , 2022 .