Compressive cooperative obstacle mapping in mobile networks

Proceedings - IEEE Military Communications Conference MILCOM

Volumn , Issue , 2010, Pages 524-530

  Mostofi, Yasamin ^a   Gonzalez Ruiz, Alejandro ^a  

^a University of New Mexico   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COOPERATIVE NETWORKS; MOBILE NETWORKS; OBSTACLE MAP; OBSTACLE MAPPING; SPARSE REPRESENTATION; WIRELESS CHANNEL; WIRELESS MEASUREMENTS;

WIRELESS NETWORKS;

MILITARY COMMUNICATIONS;

EID: 79951618112     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/MILCOM.2010.5680402     Document Type: Conference Paper

References (31)

1. F. Dellaert, F. Alegre, and E. B. Martinson. Intrinsic localization and mapping with 2 applications: Diffusion mapping and macro polo localization. In IEEE Intl. Conf. on Robotics and Automation, volume 2, pages 2344-2349, 2003.
2. R. Sim, G. Dudek, and N. Roy. A closed form solution to the single degree of freedom simultaneous localisation and map building (SLAM) problem. In IEEE CDC, volume 1, pages 191-196, 2000.
3. R. Gartshore, A. Aguado, and C. Galambos. Incremental map building using an occupancy grid for an autonomous monocular robot. In 7th International Conference on Control, Automation, Robotics and Vision, volume 2, pages 613-618, December 2002.
4. Y. Mostofi and P. Sen. Compressive Cooperative Mapping in Mobile Networks. In Proceedings of the 28th American Control Conference (ACC), pages 3397-3404, St. Louis, MO, June 2009.
5. M. C. Wicks. Rf tomography with application to ground penetrating radar. In Asilomar Conference on Signals, Systems and Computers, pages 2017-2022, November 2007.
6. A. M. Haimovich, R. S. Blum, and L. J. Cimini. Mimo radar with widely separated antennas. In IEEE Signal Processing Magazine, pages 116-129, January 2008.
7. J. Wilson and N. Patwari. Radio tomographic imaging with wireless networks. accepted to appear in IEEE Trans. on Mobile Comp., 2010.
8. M. Kanso and M. Rabbat. Compressed RF tomography for wireless sensor networks: Centralized and decentralized approaches. In IEEE Intl. Conference on Distributed Computing in Sensor Systems, June 2009.
9. E. Candès, J. Romberg, and T. Tao. Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information. IEEE Trans. on Information Theory, 52(2):489-509, February 2006. (Pubitemid 43174093)
10. D. L. Donoho. Compressed sensing. IEEE Transactions on Information Theory, 52(4):1289-1306, April 2006.
11. D. Needell and R. Vershynin. Uniform uncertainty principle and signal recovery via regularized orthogonal matching pursuit, 2007. Preprint.
12. F. Santosa and W. W. Symes. Linear inversion of band-limited reflection seismograms. SIAM Journal on Scientific and Statistical Computing, 7(4):1307-1330, 1986.
13. R. Gribonval and M. Nielsen. Sparse representations in unions of bases. IEEE Trans. on Information Theory, 49(12):3320-3325, December 2003.
14. E. J. Candès, J. Romberg, and T. Tao. Stable signal recovery from incomplete and inaccurate measurements. Comm. Pure Appl. Math, 59(8):1207-1223, 2005.
15. http://www.dsp.ece.rice.edu/cs/.
16. M. Rudelson and R. Vershynin. Sparse reconstruction by convex relaxation: Fourier and Gaussian measurements, 2006. Preprint.
17. W. B. Johnson and J. Lindenstrauss (editors). Handbook of the Geometry of Banach Spaces, volume 1,2. Elsevier Science Ltd, North-Holland, Amsterdam, 2001.
18. S. J. Szarek. Condition numbers of random matrices. J. of Complexity, 7(2):131-149, 1991.
19. A. E. Litvak, A. Pajor, M. Rudelson, and N. Tomczak-Jaegermann. Smallest singular value of random matrices and geometry of random polytopes. Advances in Mathematics, 195(2):491-523, 2005.
20. E. J. Candès. The restricted isometry property and its implications for compressed sensing. Compte Rendus de l'Academie des Sciences, 346:589-592, 2008.
21. S. Boyd and L. Vandenberghe. Convex Optimization. Cambridge University Press, 2004.
22. 1 magic toolbox. http://www.acm.caltech.edu/l1magic/.
23. S.J. Wright, R.D. Nowak, and M.A.T. Figueiredo. Sparse reconstruction by separable approximation. In IEEE International Conference on Acoustics, Speech and Signal Processing, pages 3373-3376, April 2008.
24. M.A.T. Figueiredo, R.D. Nowak, and S.J. Wright. Gradient projection for sparse reconstruction: Application to compressed sensing and other inverse problems. IEEE Journal of Selected Topics in Signal Processing, 1(4):586-597, Dec. 2007. (Pubitemid 351276802)
25. Y. Nesterov. Gradient methods for minimizing composite objective function. Center for Operations Research and Econometrics Discussion Paper, (76), 2007.
26. J. Tropp and A. Gilbert. Signal recovery from random measurements via orthogonal matching pursuit. IEEE Trans. on Information Theory, 53(12):4655-4666, December 2007.
27. Chengbo Li. An Efficient Algorithm For Total Variation Regularization with Applications to the Single Pixel Camera and Compressive Sensing. PhD thesis, RICE University, 2009.
28. W. C. Jakes. Microwave Mobile Communications. Wiley-IEEE Press, New York, 1994.
29. Y. Mostofi, A. Gonzalez-Ruiz, A. Ghaffarkhah, and D. Li. Characterization and Modeling of Wireless Channels for Networked Robotic and Control Systems - A Comprehensive Overview. In Proceedings of 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), St. Louis, MO, October 2009.
30. A. Goldsmith. Wireless Communications. Cambridge University Press, 2005.
31. A. C. Kak and M. Slaney. Principles of Computerized Tomographic Imaging. IEEE, 1988.