Bandwidth-efficient target tracking in distributed sensor networks using particle filters

2006 9th International Conference on Information Fusion, FUSION

Volumn , Issue , 2006, Pages

  Zuo, L ^a   Mehrotra, K ^a   Varshney, P K ^a   Mohan, C K ^a  

^a SYRACUSE UNIVERSITY   (United States)

Author keywords

Data association; EM algorithm; Gaussian mixture model; Particle filtering; Target tracking

Indexed keywords

AIR FILTERS; CELLULAR RADIO SYSTEMS; CONTROL THEORY; DATA FUSION; ESTIMATION; EXTENDED KALMAN FILTERS; FUSION REACTIONS; INFORMATION FUSION; KALMAN FILTERS; NONLINEAR FILTERING; NUCLEAR PHYSICS; PARAMETER ESTIMATION; SENSOR DATA FUSION; SENSOR NETWORKS; SENSORS; SIGNAL FILTERING AND PREDICTION; TELECOMMUNICATION EQUIPMENT; TRELLIS CODES; WAVE FILTERS;

A POSTERIORI; BEST LINEAR UNBIASED ESTIMATOR; DATA ASSOCIATION; DISTRIBUTED PARTICLE FILTERS; DISTRIBUTED SENSOR NETWORKS; E-M ALGORITHMS; EM ALGORITHM; ESTIMATION PROBLEMS; EXTENDED KALMAN FILTER (EKF); FUSION CENTER; GAUSSIAN MIXTURE MODEL; HIGHLY NONLINEAR; INTERNATIONAL CONFERENCES; LOCAL SENSORS; MOVING TARGETS; MULTISENSOR ENVIRONMENT; NON-GAUSSIAN; PARTICLE FILTERING; REAL-TIME PROCESSING; SIMULATION RESULTS;

TARGET TRACKING;

EID: 50149089178     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICIF.2006.301692     Document Type: Conference Paper

References (13)

1. Y. Bar-Shalom and T.E. Fortmann, Tracking and Data Association, Academic Press, San Diego, CA, 1988.
2. N. Gordon, D. Salmond, and A. F. M. Smith, "Novel approach to nonlinear and non-Gaussian Bayesian state estimation," in Proceedings IEEF, vol. 140, pp. 107-113, 1993.
3. A. Doucet, N.de Freitas and N.J. Gordon, Sequential Monte Carlo Methods in Practice, Springer-Verlag, New York, 2001.
4. X. Rong Li, and V.P. Jilkov, "Survey of maneuvering target tracking part I: Dynamic models," in IEEE Transactions on Aerospace and Electronic Systems, Vol. 39, 2003.
5. X. Rong Li and Vesselin P.Jilkov, "A Survey of Maneuvering Target Tracking-Part III: Measurement Models," in SPIE Conf. on Signal and Data Processing of Small Targets, 2001.
6. X.Rong Li, YM Zhu and CZ Han, "Unified Optimal Linear Estimation Fusion-Part I: Unified Models and Fusion Rules," in Proc. Int'l. Conf. on Information Fusion, France, July 2000.
7. Mark Coates, "Distributed particle filters for sensor networks," in Proc. of 3rd Int'l symposium on Information processing in sensor networks, Berkeley, CA, USA
8. Dong Guo and Xiaodong Wang, "Dynamic sensor collaboration via sequential Monte Carlo," in IEEE Journal on Selected Areas in Communications, vol. 22, pp. 1037-1047, Aug. 2004.
9. C. Hue, J.-P. L. Cadre and P. Perez, "Sequential Monte Carlo methods for multiple target tracking and data fusion," in IEEE Trans. Signal Processing, vol. 50, no. 2, pp. 309-325, Feb. 2002.
10. Xiaohong Sheng and Yu-Hen Hu, "Distributed Particle Filters For Wireless Sensor Network Target Tracking," in ICASSP 2005, Philadelphia, PA, USA.
11. Tom Vercauteren, Dong Guo Xiaodong Wang, "Joint Multiple Target Tracking and Classification in Collaborative Sensor Networks," in IEEE Journal on Selected Areas in Communications, April. 2005.
12. Tien Pham and Haralabos C. Papadopoulos, "Distributed Tracking in Ad-Hoc Sensor Network," in IEEE Workshop on Statistical Signal Processing, July 2005.
13. J. Bilmes, "A gentle tutorial of the EM algorithm and its application to parameter estimation for Gaussian Mixture and Hidden Markov Models," in UC Berkeley TR-97-021, April, 1998.