Hostname: page-component-78c5997874-dh8gc Total loading time: 0 Render date: 2024-11-10T14:18:45.287Z Has data issue: false hasContentIssue false
  • English
  • Français

Aspect-dependent efficient multipath ghost suppression in TWRI with sparse reconstruction

Published online by Cambridge University Press:  19 June 2017

Ali Hussein Muqaibel ,
Abdi Talib Abdalla ,
Mohammad Tamim Alkhodary  and
Suhail Al-Dharrab
Ali Hussein Muqaibel
Affiliation:
Electrical Engineering Department, King Fahd University of Petroleum & Minerals, Dhahran, 31261, Saudi Arabia
Abdi Talib Abdalla
Affiliation:
Electronics and Telecommunication Engineering Department, University of Dar es Salaam, Tanzania
Mohammad Tamim Alkhodary*
Affiliation:
Electrical Engineering Department, King Fahd University of Petroleum & Minerals, Dhahran, 31261, Saudi Arabia
Suhail Al-Dharrab
Affiliation:
Electrical Engineering Department, King Fahd University of Petroleum & Minerals, Dhahran, 31261, Saudi Arabia
*
Corresponding author: M.T. Alkhodary Email: mtamim@kfupm.edu.sa
Get access Rights & Permissions [Opens in a new window]

Abstract

In through-the-wall radar imaging, multipath propagation can create ghost targets, which can adversely affect the image reconstruction process. However, unlike genuine targets, ghost positions are aspect-dependent, which means their position changes with the transceiver location. This paper proposes efficient ghost suppression methods exploiting aspect dependence feature under compressive sensing framework. This paper proposes a generalized signal model that accommodates for the reflections of the front-wall and target-to-target interactions, making the scheme more practical, yet the knowledge of the location of reflecting geometry is not a requirement as in most of the recent literatures. In addition, the sensing matrix is greatly reduced making the methods more attractive. Moreover, this paper investigates the influence of array configurations by examining two antenna array configurations: multimonostatic, and single-view bistatic configurations. Results based on synthesized data and real experiment show that the proposed method can greatly suppress multipath ghosts and hence increase signal-to-clutter ratio.

Keywords

RadarAntenna designModeling and measurementsAspect dependence
Type
Research Paper
Information
International Journal of Microwave and Wireless Technologies , Volume 9 , Issue 9 , November 2017 , pp. 1839 - 1852
Copyright
Copyright © Cambridge University Press and the European Microwave Association 2017 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

[1] Abdalla, A.T.; Muqaibel, A.H.; Al-Dharrab, S.: Aspect dependent multipath ghost suppression in TWRI under compressive sensing framework, in 2015 Int. Conf. Communications, Signal Processing, and their Applications (ICCSPA), Sharjah, 2015, 1–6.CrossRefGoogle Scholar
[2] Abdalla, A.T.; Muqaibel, A.H.: Multiple target sparse reconstruction in TWRI utilizing ghost's aspect dependence feature, in 2015 IEEE International RF and Microwave Conf. (RFM), Kuching, 2015, 280–284.Google Scholar
[3] Amin, M.G.; Ahmad, F.: Compressive sensing for through-the-wall radar imaging. J. Electron. Imaging, 22 (3) (2013), 30901.Google Scholar
[4] Amin, M.G.: Through-the-Wall Radar Imaging, CRC Press, Taylor and Francis Group, New York, 2010.Google Scholar
[5] Baranoski, E.J.: Through wall imaging: historical perspective and future directions, 2008 IEEE Int. Conf. Acoustics, Speech and Signal Processing, Las Vegas, NV, 2008, 5173–5176.Google Scholar
[6] Burchett, H.: Advances in through wall radar for search, rescue and security applications, in Proc. Institute of Engineering and Technology Conf. Crime and Security, London, UK, 2006, 511–525.CrossRefGoogle Scholar
[7] Charvat, G.L.; Kempel, L.C.; Rothwell, E.J.; Coleman, C.M.; Mokole, E.L.: A through-dielectric radar imaging system. IEEE Trans. Antennas Propag., 58 (8) (2010), 2594–2603.Google Scholar
[8] Leigsnering, M.; Ahmad, F.; Amin, M.; Zoubir, A.: Multipath exploitation in through-the-wall radar imaging using sparse reconstruction, IEEE Trans . Aerosp. Electron. Syst., 50 (2) (2014), 920–939.Google Scholar
[9] Setlur, P.; Alli, G.; Nuzzo, L.: Multipath exploitation in through-wall radar imaging via point spread functions. IEEE Trans. Image Process., 22 (12) (2013), 4571–4586.CrossRefGoogle ScholarPubMed
[10] Chakraborty, B.; Li, Y.; Zhang, J.J.; Trueblood, T.; Papandreou-Suppappola, A.; Morrell, D.: Multipath exploitation with adaptive waveform design for tracking in urban terrain, in 2010 IEEE Int. Conf. Acoustics, Speech and Signal Processing, Dallas, TX, 2010, 3894–3897.Google Scholar
[11] Linnehan, R.; Schindler, J.: Multistatic scattering from moving targets in multipath environments, in 2009 IEEE Radar Conf., Pasadena, CA, 2009, 1–6.Google Scholar
[12] Krolik, J.L.; Farrell, J.; Steinhardt, A.: Exploiting multipath propagation for GMTI in urban environments, in IEEE Conf. on Radar, New York, USA, 2006, 4–9.Google Scholar
[13] Yoon, Y.-S.; Amin, M.: Compressed sensing technique for high resolution radar imaging, Proc. SPIE Signal Processing Sensor Fusion Target Recognition. XVII, 2008, 69681A-69681A-10.Google Scholar
[14] Setlur, P.; Amin, M.; Ahmad, F.; Member, S.: Multipath model and exploitation in through-the-wall and urban radar sensing. IEEE Trans. Geosci. Remote Sens., 49 (10) (2011), 4021–4034.Google Scholar
[15] Tan, Q.: A new method for multipath interference suppression in through-the-wall UWB radar imaging, in 2nd Int. Conf. on Advanced Computer Control, Shenyang China, 2010, 535–540.Google Scholar
[16] Li, Z.; Kong, L.; Jia, Y.; Zhao, Z.; Lan, F.: A novel approach of multi-path suppression based on sub-aperture imaging in through-wall-radar imaging, in 2013 IEEE Radar Conf. (RadarCon13), Ottawa, ON, 2013, 1–4.Google Scholar
[17] Tan, Q.; Leung, H.; Song, Y.; Wang, T.: Multipath ghost suppression for through-the-wall radar. IEEE Trans. Aerosp. Electron. Syst., 50 (3) (2014), 2284–2292.Google Scholar
[18] Gennarelli, G.; Soldovieri, F.: Multipath ghosts in radar imaging: physical insight and mitigation strategies. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens., 8 (3) (2015), 1078–1086.CrossRefGoogle Scholar
[19] Yan, D.; Cui, G.; Guo, S.; Kong, L.; Yang, X.; Liu, T.: Multipath ghosts location and sub-aperture based suppression algorithm for TWIR, in 2016 IEEE Radar Conf. (RadarConf), Philadelphia, PA, 2016, 1–4.Google Scholar
[20] Chen, X.; Chen, W.: Multipath ghost elimination for through-wall radar imaging. IET Radar Sonar Navig., 10 (2) (2016), 299–310.CrossRefGoogle Scholar
[21] Leigsnering, M.; Ahmad, F.; Amin, M.G.; Zoubir, A.M.: Compressive sensing based specular multipath exploitation for through-the-wall radar imaging, in 2013 IEEE Int. Conf. Acoustics, Speech and Signal Processing, Vancouver, BC, 2013, 6004–6008.Google Scholar
[22] Wang, J.; Wang, P.; Li, Y.; Song, Q.; Zhou, Z.: A multipath suppression technique for through-the-wall radar, in 2013 IEEE Int. Conf. on Ultra-Wideband (ICUWB), Ieee, 2013, 215–220.Google Scholar
[23] Ralston, T.S.; Charvat, G.L.; Peabody, J.E.: Real-time through-wall imaging using an ultrawideband multiple-input multiple-output (MIMO) phased array radar system, in 2010 IEEE Int. Symp. on Phased Array Systems and Technology, Waltham, MA, 2010, 551–558.CrossRefGoogle Scholar
[24] Ahmed, F.; Amin, M.G.; Kassam, S.: A beamforming approach to stepped-frequency synthetic aperture through-the-wall radar imaging, in Proc. of the IEEE First Int. Workshop on Computational Advances in Multi-Sensor Adaptive Processing, Puerto Vallarta, Mexico, 2005, 24–27.Google Scholar
[25] Gurbuz, A.C.; McClellan, J.H.; Scott, W.R.: A compressive sensing data acquisition and imaging method for stepped frequency GPRs. IEEE Trans. Signal Process., 57 (7) (2009), 2640–2650.Google Scholar
[26] Setlur, P.; Amin, M.; Ahmad, F.: Multipath model and exploitation in through-the-wall and urban radar sensing. IEEE Trans. Geosci. Remote Sens., 49 (10) (2011), 4021–4034.CrossRefGoogle Scholar
[27] Karousos, A.; Koutitas, G.; Tzaras, C.: Transmission and reflection coefficients in time-domain for a dielectric slab for UWB signals, in VTC Spring 2008 – IEEE Vehicular Technology Conf., Singapore, 2008, 455–458.Google Scholar
[28] Yoon, Y.-S.; Amin, M.: Spatial filtering for wall-clutter mitigation in through-the-wall radar imaging. IEEE Trans. Geosci. Remote Sens., 47 (9) (2009), 3192–3208.Google Scholar
[29] Tivive, F.H.C.; Amin, M.G.; Bouzerdoum, A.: Wall clutter mitigation based on Eigen-analysis in through-the-wall radar imaging, in 2011 17th Int. Conf. Digital Signal Processing (DSP), Corfu, 2011, 1–8.Google Scholar
[30] Lagunas, E.; Amin, M.G.; Ahmad, F.; Nájar, M.: Wall mitigation techniques for indoor sensing within the compressive sensing framework. IEEE Trans. Geosci. Remote Sens., 51 (2) (2013), 891–906.Google Scholar
[31] Leigsnering, M.; Amin, M.G.; Ahmad, F.; Zoubir, A.M.: Multipath exploitation and suppression for SAR imaging of building interiors [an overview of recent advances]. IEEE Signal Process. Mag., 31 (4) (2014), 110–119.Google Scholar
[32] Tivive, F.; Bouzerdoum, A.; Moeness, A.: A subspace projection approach for wall clutter mitigation in through-the-wall radar Imaging. IEEE Trans. Geosci. Remote Sens., 53 (4) (2015), 2108–2122.Google Scholar
[33] Amin, M.; Ahmad, F.; Zhang, W.: A compressive sensing approach to moving target indication for urban sensing, in 2011 IEEE RadarCon (RADAR), Ieee, 2011, 509–512.Google Scholar
[34] Donoho, D.L.; Tsaig, Y.; Drori, I.; Starck, J.L.: Sparse solution of underdetermined systems of linear equations by stage wise orthogonal matching pursuit. IEEE Trans. Inf. Theory, 58 (2) (2012), 1094–1121.CrossRefGoogle Scholar
[35] Leigsnering, M.: Sparsity-Based Multipath Exploitation for Through-the-Wall Radar Imaging. Technische Universität, Darmstadt, Ph.D. Thesis, 2015.Google Scholar
[36] Li, L.; Boufounos, P.; Liu, D.; Mansour, H.; Sahinoglu, S.: Sparse MIMO architectures for through-the-wall imaging, in 2014 IEEE 8th Sensor Array and Multichannel Signal Processing Workshop (SAM), A Coruna, 2014, 513–516.Google Scholar
[37] Vaidyanathan, P.P.; Pal, P.: Sparse sensing with coprime arrays. Conf. Rec. – Asilomar Conf. Signals Syst. Comput., 59 (2) (2010), 1405–1409.Google Scholar
[38] Donoho, D.L.: Compressed sensing. IEEE Trans. Inf. Theory, 52 (4) (2006), 1289–1306.Google Scholar
[39] Candès, E.J.: Compressive sampling, in Proc. of the Int. Congress of Mathematicians, Eur. Mathematical Society, Madrid, Spain (2006).Google Scholar
[40] Huang, Q.; Qu, L.; Wu, B.; Fang, G.: UWB through-wall imaging based on compressive sensing. IEEE Trans. Geosci. Remote Sens., 48 (2010), (3 PART2), 1408–1415.Google Scholar
[41] Yang, J.; Zhang, Y.: Alternating direction algorithms for L1-problems in compressive sensing. SIAM J. Sci. Comput., 33 (1–2) (2011), 250–278.Google Scholar