Open Access

Particle Filtering Algorithms for Tracking a Maneuvering Target Using a Network of Wireless Dynamic Sensors

EURASIP Journal on Advances in Signal Processing20062006:083042

https://doi.org/10.1155/ASP/2006/83042

Received: 16 June 2005

Accepted: 30 April 2006

Published: 27 June 2006

Abstract

We investigate the problem of tracking a maneuvering target using a wireless sensor network. We assume that the sensors are binary (they transmit '1' for target detection and '0' for target absence) and capable of motion, in order to enable the tracking of targets that move over large regions. The sensor velocity is governed by the tracker, but subject to random perturbations that make the actual sensor locations uncertain. The binary local decisions are transmitted over the network to a fusion center that recursively integrates them in order to sequentially produce estimates of the target position, its velocity, and the sensor locations. We investigate the application of particle filtering techniques (namely, sequential importance sampling, auxiliary particle filtering and cost-reference particle filtering) in order to efficiently perform data fusion, and propose new sampling schemes tailored to the problem under study. The validity of the resulting algorithms is illustrated by means of computer simulations.

[1234567891011121314151617181920212223]

Authors’ Affiliations

(1)
Departamento de Teoría de la Señal y Comunicaciones, Universidad Carlos III de Madrid

References

  1. Luo RC, Yih C-C, Su KL: Multisensor fusion and integration: approaches, applications and future research directions. IEEE Sensors Journal 2002, 2(2):107-119. 10.1109/JSEN.2002.1000251View ArticleGoogle Scholar
  2. Chong C-Y, Kumar SP: Sensor networks: evolution, opportunities, and challenges. Proceedings of the IEEE 2003, 91(8):1247-1256. 10.1109/JPROC.2003.814918View ArticleGoogle Scholar
  3. Zhao F, Guibas L: Wireless Sensor Networks. Morgan Kaufman, New York, NY, USA; 2004.Google Scholar
  4. Brooks RR, Ramanathan P, Sayeed AM: Distributed target classification and tracking in sensor networks. Proceedings of the IEEE 2003, 91(8):1163-1171. 10.1109/JPROC.2003.814923View ArticleGoogle Scholar
  5. Doherty L, Warneke BA, Boser BE, Pister KSJ: Energy and performance considerations for smart dust. International Journal of Parallel and Distributed Systems and Networks 2001, 4(3):121-133.Google Scholar
  6. Patwari N, Hero AO III, Perkins M, Correal NS, O'Dea RJ: Relative location estimation in wireless sensor networks. IEEE Transactions on Signal Processing 2003, 51(8):2137-2148. 10.1109/TSP.2003.814469View ArticleGoogle Scholar
  7. Savvides A, Girod L, Srivastava MB, Estrin D: Localization in sensor networks. In Wireless Sensor Networks. Edited by: Raghavendra CS, Sivalingham KM, Znati T. Kluwer Academic, Boston, Mass, USA; 2004.Google Scholar
  8. Savvides A, Han C-C, Srivastava MB: Dynamic fine-grained localization in ad-hoc networks of sensors. Proceedings of the 7th Annual International Conference on Mobile Computing and Networking (MOBICOM '01), July 2001, Rome, Italy 166-179.View ArticleGoogle Scholar
  9. Ihler AT, Fisher JW III, Moses RL, Willsky AS: Nonparametric belief propagation for self-calibration in sensor networks. Proceedings of the 3rd International Symposium on Information Processing in Sensor Networks (IPSN '04), April 2004, Berkeley, Calif, USA 225-233.Google Scholar
  10. Artés-Rodríguez A: Decentralized detection in sensor networks using range information. Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP '04), May 2004, Montreal, Quebec, Canada 2: 265-268.Google Scholar
  11. Míguez J, Bugallo MF, Djurić PM: Decision fusion for distributed target tracking using cost reference particle filtering. Proceedings of 13th European Signal Processing Conference (EUSIPCO '05), September 2005, Antalya, TurkeyGoogle Scholar
  12. Djurić PM, Vemula M, Bugallo MF, Míguez J: Non-cooperative localization of binary sensors. Proceedings of 13th IEEE Workshop on Statistical Signal Processing (SSP '05), July 2005, Bordeaux, FranceGoogle Scholar
  13. Liu JS, Chen R: Sequential Monte Carlo methods for dynamic systems. Journal of the American Statistical Association 1998, 93(443):1032-1044. 10.2307/2669847MathSciNetView ArticleMATHGoogle Scholar
  14. Doucet A, Godsill S, Andrieu C: On sequential Monte Carlo sampling methods for Bayesian filtering. Statistics and Computing 2000, 10(3):197-208. 10.1023/A:1008935410038View ArticleGoogle Scholar
  15. Arulumpalam MS, Maskell S, Gordon N, Klapp T: A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking. IEEE Transactions on Signal Processing 2002, 50(2):174-188. 10.1109/78.978374View ArticleGoogle Scholar
  16. Djurić PM, Kotecha JH, Zhang J, et al.: Particle filtering. IEEE Signal Processing Magazine 2003, 20(5):19-38. 10.1109/MSP.2003.1236770View ArticleGoogle Scholar
  17. Crisan D, Doucet A: A survey of convergence results on particle filtering methods for practitioners. IEEE Transactions on Signal Processing 2002, 50(3):736-746. 10.1109/78.984773MathSciNetView ArticleGoogle Scholar
  18. Doucet A, de Freitas N, Gordon N: An introduction to sequential Monte Carlo methods. In Sequential Monte Carlo Methods in Practice. Edited by: Doucet A, de Freitas N, Gordon N. Springer, New York, NY, USA; 2001:4-14. chapter 1View ArticleGoogle Scholar
  19. Douc R, Cappé O, Moulines E: Comparison of resampling schemes for particle filtering. Proceedings of the 4th International Symposium on Image and Signal Processing and Analysis (ISPA '05), September 2005, Zagreb, Croatia 64-69.Google Scholar
  20. Pitt MK, Shephard N: Auxiliary variable based particle filters. In Sequential Monte Carlo Methods in Practice. Edited by: Doucet A, de Freitas N, Gordon N. Springer, New York, NY, USA; 2001:273-293. chapter 13View ArticleGoogle Scholar
  21. Míguez J, Bugallo MF, Djurić PM: A new class of particle filters for random dynamic systems with unknown statistics. EURASIP Journal on Applied Signal Processing 2004, 2004(15):2278-2294. 10.1155/S1110865704406039View ArticleMathSciNetMATHGoogle Scholar
  22. Gustafsson F, Gunnarsson F, Bergman N, et al.: Particle filters for positioning, navigation, and tracking. IEEE Transactions on Signal Processing 2002, 50(2):425-437. 10.1109/78.978396View ArticleGoogle Scholar
  23. Rappaport TS: Wireless Communications: Principles and Practice. 2nd edition. Prentice-Hall, Upper Saddle River, NJ, USA; 2001.MATHGoogle Scholar

Copyright

© J. Míguez and A. Artés-Rodríguez 2006

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.