Abstract
This chapter focuses on sparse reconstruction of targets in an indoor environment. Due to the front wall and surrounding scatterers, multipath propagation arises which is exploited to improve reconstruction results. The sparsity of the scene and the structure therein is leveraged to obtain a clean image from few measurements. Throughout this chapter, perfect knowledge of the room geometry is assumed and suppression of any wall or corner returns is required.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
F. Ahmad, M.G. Amin, Multi-location wideband synthetic aperture imaging for urban sensing applications. J. Franklin Inst. 345(6), 618–639 (2008)
F. Ahmad, M.G. Amin, Wall clutter mitigation for MIMO radar configurations in urban sensing, in 11th International Conference on Information Science, Signal Processing and their Applications (ISSPA), Montreal, Canada, pp. 1165–1170, July 2012
F. Ahmad, M.G. Amin, S. Kassam, A beamforming approach to stepped-frequency synthetic aperture through-the-wall radar imaging, in IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, Puerto Vallarta, Mexico, pp. 24–27, December 2005
F. Ahmad, G. Frazer, S. Kassam, M.G. Amin, Design and implementation of near-field, wideband synthetic aperture beamformers. IEEE Trans. Aerosp. Electron. Syst. 40(1), 206–220 (2004)
R. Baraniuk, V. Cevher, M. Duarte, C. Hegde, Model-based compressive sensing. IEEE Trans. Inf. Theory 56, 1982–2001 (2010)
G. Beylkin, On the fast Fourier transform of functions with singularities. Appl. Comput. Harmonic Anal. 2(4), 363–381 (1995)
V. Dang, O. Kilic, Joint DoA-range-doppler tracking of moving targets based on compressive sensing, in IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, pp. 141–142, Memphis, TN (2014)
T. Dogaru, C. Le, SAR images of rooms and buildings based on FDTD computer models. IEEE Trans. Geosci. Remote Sens. 47(5), 1388–1401 (2009)
A. Dutt, V. Rokhlin, Fast Fourier transforms for nonequispaced data, II. Appl. Comput. Harmonic Anal. 2(1), 85–100 (1995)
W. Deng, W. Yin, Y. Zhang, Group sparse optimization by alternating direction method, Department of Computational and Applied Mathematics, Rice University, Technical Report TR11-06 (2011)
Y.C. Eldar, P. Kuppinger, H. Bolcskei, Block-sparse signals: uncertainty relations and efficient recovery. IEEE Trans. Signal Process. 58(6), 3042–3054 (2010)
M. Leigsnering, F. Ahmad, M.G. Amin, A. Zoubir, Compressive sensing based specular multipath exploitation for through-the-wall radar imaging, in IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Vancouver, Canada, pp. 6004–6008, May 2013
M. Leigsnering, F. Ahmad, M.G. Amin, A. Zoubir, Multipath exploitation in through-the-wall radar imaging using sparse reconstruction. IEEE Trans. Aerosp. Electron. Syst. 50(2), 920–939 (2014)
M. Leigsnering, F. Ahmad, M.G. Amin, A. Zoubir, Specular multipath exploitation for improved velocity estimation in through-the-wall radar imaging, in IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Florence, Italy, pp. 1060–1064, May 2014
M. Leigsnering, M.G. Amin, F. Ahmad, A.M. Zoubir, Multipath exploitation and suppression for SAR imaging of building interiors: an overview of recent advances. IEEE Signal Process. Mag. 31(4), 110–119 (2014)
M. Leigsnering, F. Ahmad, M.G. Amin, A. Zoubir, Compressive sensing based multipath exploitation for stationary and moving indoor target localization. IEEE J. Selected Topics Signal Process. 9(8), 1469–1483 (2015)
M. Leigsnering, F. Ahmad, M.G. Amin, A. Zoubir, Multipath-aware velocity estimation for sparsity-based through-the-wall radar imaging, in IEEE International Radar Conference, Arlington, VA (2015)
M. Leigsnering, F. Ahmad, M.G. Amin, A. Zoubir, Multipath exploitation in sparse scene recovery using sensing-through-wall distributed radar sensor configurations, in IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Brisbane, Australia, April 2015
M. Leigsnering, F. Ahmad, M.G. Amin, A. Zoubir, Parametric dictionary learning for sparsity-based TWRI in multipath environments. IEEE Trans. Aerosp. Electron. Syst. 52(2), 532–547 (2016)
M. Leigsnering, A. Zoubir, Fast wideband near-field imaging using the non-equispaced FFT with application to through-wall radar, in European Signal Processing Conference (EUSIPCO), pp. 1708–1712, Spain, Barcelona (2011)
M. Leigsnering, A.M. Zoubir, Compressive sensing for urban multipath exploitation, in Compressive Sensing for Urban Radar (CRC Press, Boca Raton, 2014), pp. 153–196
J. Moulton, S. Kassam, F. Ahmad, M.G. Amin, K. Yemelyanov, Target and change detection in synthetic aperture radar sensing of urban structures, in IEEE Radar Conference (RADAR), Rome, Italy (2008)
D. Potts, G. Steidl, M. Tasche, Fast Fourier transforms for nonequispaced data: a tutorial. Birkhäuser, pp. 247–269 (2001). chap. 12
O. Pele, M. Werman, Fast and robust earth mover’s distances, in IEEE 12th International Conference on Computer Vision, Kyoto, Japan, pp. 460–467, September 2009
J. Qian, F. Ahmad, M.G. Amin, Joint localization of stationary and moving targets behind walls using sparse scene recovery. J. Electron. Imaging 22(2), 021002 (2013)
M.A. Richards, J.A. Scheer, W.A. Holm (eds.), Principles of Modern Radar: Basic Principles (SciTech Publishing, Raleigh, NC, 2010)
Y. Rubner, C. Tomasi, L.J. Guibas, The earth mover’s distance as a metric for image retrieval. Int. J. Comput. Vision 40(2), 99–121 (2000)
P. Setlur, M.G. Amin, F. Ahmad, Multipath model and exploitation in through-the-wall and urban radar sensing. IEEE Trans. Geosci. Remote Sens. 49(10), 4021–4034 (2011)
P. Setlur, G. Alli, L. Nuzzo, Multipath exploitation in through-wall radar imaging via point spread functions. IEEE Trans. Image Process. 22(12), 4571–4586 (2013)
M. Soumekh, Synthetic Aperture Radar Signal Processing with MATLAB Algorithms (Wiley, New York, 1999)
S. Wright, R. Nowak, M. Figueiredo, Sparse reconstruction by separable approximation. IEEE Trans. Signal Process. 57(7), 2479–2493 (2009)
Y.-S. Yoon, M. Amin, Compressed sensing technique for high-resolution radar imaging, in Proceedings of SPIE Signal Processing, Sensor Fusion, and Target Recognition XVII, vol. 6968, no. 1, Orlando, FL, p. 69681A, March 2008
M. Yuan, Y. Lin, Model selection and estimation in regression with grouped variables. J. Roy. Stat. Soc. B 68(1), 49–67 (2006)
L. Yuan, J. Liu, J. Ye, Efficient methods for overlapping group lasso. IEEE Trans. Pattern Anal. Mach. Intell. 35(9), 2104–2116 (2013)
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG
About this chapter
Cite this chapter
Leigsnering, M. (2018). Sparsity-Based Multipath Exploitation. In: Sparsity-Based Multipath Exploitation for Through-the-Wall Radar Imaging. Springer Theses. Springer, Cham. https://doi.org/10.1007/978-3-319-74283-0_4
Download citation
DOI: https://doi.org/10.1007/978-3-319-74283-0_4
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-74282-3
Online ISBN: 978-3-319-74283-0
eBook Packages: EngineeringEngineering (R0)