Compressive Sensing Based Probabilistic Sensor Management for Target Tracking in Wireless Sensor Networks

IEEE Transactions on Signal Processing

Volumn 63, Issue 22, 2015, Pages 6049-6060

  Zheng, Yujiao ^a   Cao, Nianxia ^a   Wimalajeewa, Thakshila ^a   Varshney, Pramod K ^a  

^a Syracuse University   (United States)

Author keywords

Compressive sensing; sensor management; target tracking; wireless sensor networks

Indexed keywords

CLUTTER (INFORMATION THEORY); COMPRESSED SENSING; FISHER INFORMATION MATRIX; OPTIMAL SYSTEMS; PROBABILITY; SIGNAL RECONSTRUCTION; TARGET TRACKING; TRACKING (POSITION);

COMPLETE INFORMATION; COMPRESSIVE SENSING; MULTIPLE ACCESS CHANNELS; NUMERICAL RESULTS; OBSERVATION VECTORS; PARTIAL INFORMATION; PERFORMANCE METRICES; SENSOR MANAGEMENT;

WIRELESS SENSOR NETWORKS;

EID: 84959335847     PISSN: 1053587X     EISSN: None     Source Type: Journal    
DOI: 10.1109/TSP.2015.2464197     Document Type: Article

References (31)

1. T. Bokareva, W. Hu, S. Kanhere, B. Ristic, N. Gordon, T. Bessell et al., "Wireless sensor networks for battlefield surveillance," in Proc. Conf. Land Warfare, 2006, pp. 1-8.
2. J. Yick, B. Mukherjee, D. Ghosal, "Wireless sensor network survey," Comput. Netw., vol. 52, no. 12, pp. 2292-2330, 2008.
3. V. C. Gungor and G. P. Hancke, "Industrial wireless sensor networks: Challenges, design principles, technical approaches," IEEE Trans. Ind. Electron., vol. 56, no. 10, pp. 4258-4265, 2009.
4. A. Milenkovi?, C. Otto, E. Jovanov, "Wireless sensor networks for personal health monitoring: Issues and an implementation," Comput. Commun., vol. 29, no. 13, pp. 2521-2533, 2006.
5. S. Joshi and S. Boyd, "Sensor selection via convex optimization," IEEE Trans. Signal Process., vol. 57, pp. 451-462, Feb. 2009.
6. Y. Mo, R. Ambrosino, B. Sinopoli, "Sensor selection strategies for state estimation in energy constrained wireless sensor networks," Automatica, vol. 47, pp. 1330-1338, Jul. 2011.
7. F. Zhao, J. Shin, J. Reich, "Information-driven dynamic sensor collaboration," IEEE Trans. Signal Process., vol. 19, no. 1, pp. 61-72, May 2002.
8. L. Zuo, R. Niu, P. Varshney, "Posterior crlb based sensor selection for target tracking in sensor networks," in Proc. IEEE Int. Conf. Acoust., Speech, Signal Process., Apr. 2007, pp. 1041-1044.
9. L. Zuo, R. Niu, P. Varshney, "A sensor selection approach for target tracking in sensor networks with quantized measurements," in Proc. IEEE Int. Conf. Acoust., Speech, Signal Process., Mar. 2008, pp. 2521-2524.
10. G. Wang, J. Chen, J. Sun, Y. Cai, "Power scheduling of Kalman filtering in wireless sensor networks with data packet drops," 2013, arXiv preprint arXiv:1312.3269.
11. N. Cao, E. Masazade, P. K. Varshney, "A multiobjective optimization based sensor selection method for target tracking in wireless sensor networks," in Proc. IEEE Int. Conf. Inf. Fusion (FUSION), 2013, pp. 974-980.
12. S. Liu, M. Fardad, S. Kar, P. Varshney, "On optimal sensor collaboration topologies for linear coherent estimation," in Proc. IEEE Int. Symp. Inf. Theory (ISIT), 2014, pp. 2624-2628.
13. S. Liu, M. Fardad, E. Masazade, P. Varshney, "Optimal periodic sensor scheduling in networks of dynamical systems," IEEE Trans. Signal Process., vol. 62, no. 12, pp. 3055-3068, Jun. 2014.
14. I. D. Schizas, "Distributed informative-sensor identification via sparsity-aware matrix decomposition," IEEE Trans. Signal Process., vol. 61, no. 18, pp. 4610-4624, 2013.
15. S. Chepuri and G. Leus, "Sparsity-promoting sensor selection for nonlinear measurement models," IEEE Trans. Signal Process., vol. 63, no. 3, pp. 684-698, Feb. 2015.
16. S. Chepuri and G. Leus, "Sparsity-promoting adaptive sensor selection for non-linear filtering," in Proc. IEEE Int. Conf. Acoust., Speech, Signal Process. (ICASSP), May 2014, pp. 5080-5084.
17. D. Donoho, "Compressed sensing," IEEE Signal Process. Mag., pp. 118-124, Jul. 2007.
18. E. Candès and M. B. Wakin, "An introduction to compressive sampling," IEEE Signal Process. Mag., vol. 25, no. 2, pp. 21-30, Mar. 2008.
19. L. Xu, Q. Liang, X. Cheng, D. Chen, "Compressive sensing in distributed radar sensor networks using pulse compression waveforms," EURASIP J.Wireless Commun. Netw., vol. 2013, no. 1, pp. 1-10, 2013.
20. C. Feng, S. Valaee, Z. Tan, "Multiple target localization using compressive sensing," in Proc. IEEE Global Telecommun. Conf. (GLOBECOM), 2009, pp. 1-6, IEEE.
21. A. Carmi and P. Gurfil, "Sensor selection via compressed sensing," Automatica, pp. 3304-3314, Nov. 2013.
22. J. Haupt, W. U. Bajwa, M. Rabbat, R. Nowak, "Compressed sensing for networked data," IEEE Signal Process. Mag., vol. 25, no. 2, pp. 92-101, 2008.
23. G. Yang, V. Y. Tan, C. K. Ho, S. H. Ting, Y. L. Guan, "Wireless compressive sensing for energy harvesting sensor nodes," IEEE Trans. Signal Process., vol. 61, no. 18, pp. 4491-4505, 2013.
24. Y. Zheng, T. Wimalajeewa, P. K. Varshney, "Probabilistic sensor management for target tracking via compressive sensing," in Proc. IEEE Int. Conf. Acoust., Speech, Signal Process. (ICASSP), May 2014, pp. 5095-5099.
25. E. Candès, J. Romberg, T. Tao, "Robust uncertainty principles: Exact signal reconstruction from highly incomplete frequency information," IEEE Trans. Inf. Theory, vol. 52, no. 2, pp. 489-509, Feb. 2006.
26. E. C. T. Tao, "Near-optimal signal recovery from random projections: Universal encoding strategies?," IEEE Trans. Inf. Theory, vol. 52, no. 12, pp. 5406-5425, Dec. 2006.
27. J. Tropp and A. Gilbert, "Signal recovery from random measurements via orthogonal matching pursuit," IEEE Trans. Inf. Theory, vol. 53, no. 12, pp. 4655-4666, Dec. 2007.
28. P. Tichavsky, C. Muravchik, A. Nehorai, "Posterior Cramé-Rao bounds for discrete-time nonlinear filtering," IEEE Trans. Signal Process., vol. 46, no. 5, pp. 1386-1396, May 1998.
29. M. S. Arulampalam, S. Maskell, N. Gordon, C. Tim, "A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking," IEEE Trans. Signal Process., vol. 50, no. 2, pp. 174-188, Feb. 2002.
30. S. Boyd, Convex Optimization. Cambridge, U.K.: Cambridge Univ. Press, 2004.
31. D. Achlioptas, "Database-friendly random projections: Johnson-Lindenstrauss with binary coins," J. Comput. Syst. Sci., vol. 66, no. 4, pp. 671-687, 2003.