Compressive Sensing for No-Contact 3D Ground Penetrating Radar

No-contact Ground Penetrating Radars (GPRs) are popular microwave sensors for investigating soils or masonry/stone walls. In this paper the authors evaluated the compressive sensing (CS) as possible technique for speeding up the acquisition time of this kind of application. In effect the CS approach could reduce the number of acquisition points, and then the measurement time by using only a random pattern of the antennas positions. The authors found that the data reconstruction loses quality even with a reduction of 25 % of the number of acquisitions, but the features of the targets still visible. With a reduction of 50 % the SNR decrease sensibly and most of the targets are not detectable. Such a time reduction results rather marginal in most practical cases.

[1]  Sungyoung Lee,et al.  Compressive sensing: From theory to applications, a survey , 2013, Journal of Communications and Networks.

[2]  Deanna Needell,et al.  CoSaMP: Iterative signal recovery from incomplete and inaccurate samples , 2008, ArXiv.

[3]  Richard Bamler,et al.  Tomographic SAR Inversion by $L_{1}$ -Norm Regularization—The Compressive Sensing Approach , 2010, IEEE Transactions on Geoscience and Remote Sensing.

[4]  Massimiliano Pieraccini,et al.  ArcSAR: Theory, Simulations, and Experimental Verification , 2017, IEEE Transactions on Microwave Theory and Techniques.

[5]  Jin Jiang,et al.  Analysis in Theory and Technology Application of Compressive Sensing , 2014, 2014 Sixth International Conference on Intelligent Human-Machine Systems and Cybernetics.

[6]  Motoyuki Sato,et al.  3D image reconstruction algorithm for a sparse array radar system based on compressive sensing , 2017, 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS).

[8]  Yachao Li,et al.  Resolution Enhancement for Inversed Synthetic Aperture Radar Imaging Under Low SNR via Improved Compressive Sensing , 2010, IEEE Transactions on Geoscience and Remote Sensing.

[9]  M. Sato,et al.  High-resolution imaging of damaged wooden structures for building inspection by polarimetric radar , 2014, Proceedings of the 15th International Conference on Ground Penetrating Radar.

[10]  Lie Wang,et al.  Orthogonal Matching Pursuit for Sparse Signal Recovery With Noise , 2011, IEEE Transactions on Information Theory.

[11]  J. Tropp,et al.  CoSaMP: Iterative signal recovery from incomplete and inaccurate samples , 2008, Commun. ACM.

[12]  H. Griffiths,et al.  Preliminary results on multi offset GPR for imaging of landmines , 2017, 2017 9th International Workshop on Advanced Ground Penetrating Radar (IWAGPR).

[13]  Carlo Atzeni,et al.  Non-contact intrawall penetrating radar for heritage survey: the search of the 'Battle of Anghiari' by Leonardo da Vinci , 2005 .