{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T04:00:05Z","timestamp":1760241605628,"version":"build-2065373602"},"reference-count":33,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2018,5,31]],"date-time":"2018-05-31T00:00:00Z","timestamp":1527724800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>This work explores an innovative strategy for increasing the efficiency of compressed sensing applied on mm-wave SAR sensing using multiple weighted side information. The approach is tested on synthetic and on real non-destructive testing measurements performed on a 3D-printed object with defects while taking advantage of multiple previous SAR images of the object with different degrees of similarity. The tested algorithm attributes autonomously weights to the side information at two levels: (1) between the components inside the side information and (2) between the different side information. The reconstruction is thereby almost immune to poor quality side information while exploiting the relevant components hidden inside the added side information. The presented results prove that, in contrast to common compressed sensing, good SAR image reconstruction is achieved at subsampling rates far below the Nyquist rate. Moreover, the algorithm is shown to be much more robust for low quality side information compared to coherent background subtraction.<\/jats:p>","DOI":"10.3390\/s18061761","type":"journal-article","created":{"date-parts":[[2018,6,1]],"date-time":"2018-06-01T03:02:50Z","timestamp":1527822170000},"page":"1761","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Compressed Sensing mm-Wave SAR for Non-Destructive Testing Applications Using Multiple Weighted Side Information"],"prefix":"10.3390","volume":"18","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4433-2624","authenticated-orcid":false,"given":"Mathias","family":"Becquaert","sequence":"first","affiliation":[{"name":"CISS Department, Royal Military Academy, 30 Av. de la Renaissance, B-1000 Brussels, Belgium"},{"name":"ETRO Department, Vrije Universiteit Brussel, Pleinlaan 2, B-1050 Brussels, Belgium"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9299-238X","authenticated-orcid":false,"given":"Edison","family":"Cristofani","sequence":"additional","affiliation":[{"name":"CISS Department, Royal Military Academy, 30 Av. de la Renaissance, B-1000 Brussels, Belgium"},{"name":"ETRO Department, Vrije Universiteit Brussel, Pleinlaan 2, B-1050 Brussels, Belgium"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Huynh","family":"Van Luong","sequence":"additional","affiliation":[{"name":"ETRO Department, Vrije Universiteit Brussel, Pleinlaan 2, B-1050 Brussels, Belgium"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Marijke","family":"Vandewal","sequence":"additional","affiliation":[{"name":"CISS Department, Royal Military Academy, 30 Av. de la Renaissance, B-1000 Brussels, Belgium"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Johan","family":"Stiens","sequence":"additional","affiliation":[{"name":"ETRO Department, Vrije Universiteit Brussel, Pleinlaan 2, B-1050 Brussels, Belgium"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9300-5860","authenticated-orcid":false,"given":"Nikos","family":"Deligiannis","sequence":"additional","affiliation":[{"name":"ETRO Department, Vrije Universiteit Brussel, Pleinlaan 2, B-1050 Brussels, Belgium"},{"name":"IMEC, Kapeldreef 75, 3001 Leuven, Belgium"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2018,5,31]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Kim, T., Navagato, M.D., James, R., and Narayanan, R. (2017, January 22\u201325). Design and performance of a microwave nondestructive testing system for damage analysis of FRP composites. Proceedings of the 32nd American Society for Composites Technical Conference, West Lafayette, IN, USA.","DOI":"10.12783\/asc2017\/15356"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Kemp, I., Peterson, M., Benton, C., and Petkie, D.T. (2009, January 21\u201323). Sub-mm wave imaging techniques for non-destructive aerospace materials evaluation. Proceedings of the IEEE 2009 National Aerospace & Electronics Conference, Dayton, OH, USA.","DOI":"10.1109\/NAECON.2009.5426634"},{"key":"ref_3","unstructured":"Cristofani, E., Becquaert, M., Vandewal, M., and Jonusheit, J. (2012, January 14\u201316). Ultra-wideband, non-destructive testing SAR systems towards compressive sensing. Proceedings of the 1st International Workshop on Compressed Sensing Applied to Radar (CoSeRa 2012), Bonn, Germany."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1182","DOI":"10.1002\/mrm.21391","article-title":"Sparse MRI: The application of compressed sensing for rapid MR imaging","volume":"58","author":"Lustig","year":"2007","journal-title":"Magnet. Reson. Med."},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Tian, Z., and Giannakis, G.B. (2007, January 15\u201320). Compressed sensing for wideband cognitive radios. Proceedings of the 2007 International Conference on Acoustics, Speech and Signal Processing, Honolulu, HI, USA.","DOI":"10.1109\/ICASSP.2007.367330"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Baraniuk, R., and Steeghs, P. (2007, January 17\u201320). Compressive radar imaging. Proceedings of the 2007 Radar Conference, Boston, MA, USA.","DOI":"10.1109\/RADAR.2007.374203"},{"key":"ref_7","unstructured":"Rilling, G., Davies, M., and Mulgrew, B. (2009, January 6\u20139). Compressed sensing based compression of SAR raw data. Proceedings of the Signal Processing with Adaptive Sparse Structured Representations, Malo, France."},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Cevher, V., Sankaranarayanan, A., Duarte, M.F., Reddy, D., Baraniuk, R.G., and Chellappa, R. (2008). Compressive Sensing for Background Subtraction, Springer. European Conference on Computer Vision.","DOI":"10.1007\/978-3-540-88688-4_12"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Trzasko, J., Haider, C., and Manduca, A. (July, January 28). Practical nonconvex compressive sensing reconstruction of highly-accelerated 3D parallel MR angiograms. Proceedings of the 2009 IEEE International Symposium Biomedical Imaging: From Nano to Macro, Boston, MA, USA.","DOI":"10.1109\/ISBI.2009.5193037"},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Martone, A., Ranney, K., and Innocenti, R. (2010, January 10\u201314). Automatic through the wall detection of moving targets using low-frequency ultra-wideband radar. Proceedings of the 2010 Radar Conference, Washington, DC, USA.","DOI":"10.1109\/RADAR.2010.5494655"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"660","DOI":"10.1118\/1.2836423","article-title":"Prior image constrained compressed sensing (PICCS): A method to accurately reconstruct dynamic CT images from highly undersampled projection data sets","volume":"35","author":"Chen","year":"2008","journal-title":"Med. Phys."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"4472","DOI":"10.1109\/TIT.2017.2695614","article-title":"Compressed sensing with prior information: Strategies, geometry, and bounds","volume":"63","author":"Mota","year":"2017","journal-title":"IEEE Trans. Inf. Theory"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"427","DOI":"10.1109\/TSP.2012.2225051","article-title":"Compressed sensing with prior information: Information-theoretic limits and practical decoders","volume":"61","author":"Scarlett","year":"2013","journal-title":"IEEE Trans. Signal Process."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"5195","DOI":"10.1118\/1.4928148","article-title":"Compressed sensing for longitudinal MRI: An adaptive-weighted approach","volume":"42","author":"Weizman","year":"2015","journal-title":"Med. Phys."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Van Luong, H., Seiler, J., Kaup, A., and Forchhammer, S. (2016, January 25\u201328). Sparse signal reconstruction with multiple side information using adaptive weights for multiview sources. Proceedings of the 2016 IEEE International Conference on Image Processing (ICIP), Phoenix, AZ, USA.","DOI":"10.1109\/ICIP.2016.7532816"},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Van Luong, H., Deligiannis, N., Seiler, J., Forchhammer, S., and Kaup, A. (2017, January 14\u201316). Compressive online robust principal component analysis with multiple prior information. Proceedings of the IEEE Global Conference on Signal and Information Processing, Montreal, QC, Canada.","DOI":"10.1109\/GlobalSIP.2017.8309163"},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Van Luong, H., Deligiannis, N., Forchhammer, S., and Kaup, A. (2018). Compressive online robust principal component analysis via n-l1 minimization. IEEE Trans. Image Process.","DOI":"10.1109\/GlobalSIP.2017.8309163"},{"key":"ref_18","unstructured":"Zimos, E., Mota, J.F., Rodrigues, M.R., and Deligiannis, N. (April, January 30). Bayesian compressed sensing with heterogeneous side information. Proceedings of the Data Compression Conference (DCC), Snowbird, UT, USA."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"30","DOI":"10.5402\/2012\/208760","article-title":"A review of additive manufacturing","volume":"2012","author":"Wong","year":"2012","journal-title":"ISRN Mech. Eng."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"168","DOI":"10.1016\/j.ijfatigue.2016.07.005","article-title":"Additive manufacturing in the context of structural integrity","volume":"94","author":"Gorelik","year":"2017","journal-title":"Int. J. Fatigue"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1016\/j.mattod.2017.07.001","article-title":"Additive manufacturing: Scientific and technological challenges, market uptake and opportunities","volume":"21","author":"Tofail","year":"2017","journal-title":"Mater. Today"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"44","DOI":"10.1016\/j.matdes.2014.11.017","article-title":"Design and manufacture of high performance hollow engine valves by additive layer manufacturing","volume":"69","author":"Cooper","year":"2015","journal-title":"Mater. Des."},{"key":"ref_23","unstructured":"Lasagni, F., Zorrilla, A., Peri\u00f1\u00e1n, T.S., and Vilanova, J. (2014, January 14\u201315). On the investigation of processing parameters and NDT inspection on additive manufacturing materials for future launchers. Proceedings of the Workshop on Additive Manufacturing for Space Applications, ESA-ESTEC, Noordwijk, The Netherlands."},{"key":"ref_24","first-page":"3","article-title":"Digital processing of synthetic aperture radar data","volume":"1","author":"Cumming","year":"2005","journal-title":"Artech House"},{"key":"ref_25","unstructured":"Anitori, L., Otten, M., and Hoogeboom, P. (2010, January 7\u201310). Compressive sensing for high resolution radar imaging. Proceedings of the 2010 Asia-Pacific Microwave Conference Proceedings (APMC), Yokohama, Japan."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"4203","DOI":"10.1109\/TIT.2005.858979","article-title":"Decoding by linear programming","volume":"51","author":"Cands","year":"2005","journal-title":"IEEE Trans. Inf. Theory"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"e3576","DOI":"10.1002\/dac.3576","article-title":"A performance comparison of measurement matrices in compressive sensing","volume":"31","author":"Arjoune","year":"2018","journal-title":"Int. J. Commun. Syst."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"805","DOI":"10.1007\/s10208-012-9135-7","article-title":"The convex geometry of linear inverse problems","volume":"12","author":"Chandrasekaran","year":"2012","journal-title":"Found. Comput. Math."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Arjoune, Y., Kaabouch, N., El Ghazi, H., and Tamtaoui, A. (2017, January 9\u201311). Compressive sensing: Performance comparison of sparse recovery algorithms. Proceedings of the 7th Annual Computing and Communication Workshop and Conference (CCWC), Las Vegas, NV, USA.","DOI":"10.1109\/CCWC.2017.7868430"},{"key":"ref_30","unstructured":"Mota, J., Deligiannis, N., Sankaranarayanan, A.C., Cevher, V., and Rodrigues, M. (2015, January 19\u201324). Dynamic sparse state estimation using a l1-l1 minimization: Adaptive-rate measurement bounds, algorithms and applications. Proceedings of the 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Brisbane, Australia."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Mota, J.F., Deligiannis, N., and Rodrigues, M.R. (2014, January 3\u20135). Compressed sensing with side information: Geometrical interpretation and performance bounds. Proceedings of the 2014 IEEE Global Conference on Signal and Information Processing (GlobalSIP), Atlanta, Georgia.","DOI":"10.1109\/GlobalSIP.2014.7032170"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"183","DOI":"10.1137\/080716542","article-title":"A fast iterative shrinkage-thresholding algorithm for linear inverse problems","volume":"2","author":"Beck","year":"2009","journal-title":"SIAM J. Imaging Sci."},{"key":"ref_33","unstructured":"Becquaert, M., Cristofani, E., and Vandewal, M. (2013, January 9\u201311). On the applicability of compressive sensing on FMCW synthetic aperture radar data for sparse scene recovery. Proceedings of the 2013 European Radar Conference (EuRAD), Nuremberg, Germany."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/18\/6\/1761\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T15:06:43Z","timestamp":1760195203000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/18\/6\/1761"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,5,31]]},"references-count":33,"journal-issue":{"issue":"6","published-online":{"date-parts":[[2018,6]]}},"alternative-id":["s18061761"],"URL":"https:\/\/doi.org\/10.3390\/s18061761","relation":{},"ISSN":["1424-8220"],"issn-type":[{"type":"electronic","value":"1424-8220"}],"subject":[],"published":{"date-parts":[[2018,5,31]]}}}