{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T04:21:00Z","timestamp":1760242860370,"version":"build-2065373602"},"reference-count":33,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2016,9,1]],"date-time":"2016-09-01T00:00:00Z","timestamp":1472688000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100010418","name":"IITP","doi-asserted-by":"publisher","award":["IITP-2016-R2718-16-0011"],"award-info":[{"award-number":["IITP-2016-R2718-16-0011"]}],"id":[{"id":"10.13039\/501100010418","id-type":"DOI","asserted-by":"publisher"}]},{"name":"KSMBA","award":["Grant No. C0351676"],"award-info":[{"award-number":["Grant No. C0351676"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The detection of a moving target using an IR-UWB Radar involves the core task of separating the waves reflected by the static background and by the moving target. This paper investigates the capacity of the low-rank and sparse matrix decomposition approach to separate the background and the foreground in the trend of UWB Radar-based moving target detection. Robust PCA models are criticized for being batched-data-oriented, which makes them inconvenient in realistic environments where frames need to be processed as they are recorded in real time. In this paper, a novel method based on overlapping-windows processing is proposed to cope with online processing. The method consists of processing a small batch of frames which will be continually updated without changing its size as new frames are captured. We prove that RPCA (via its Inexact Augmented Lagrange Multiplier (IALM) model) can successfully separate the two subspaces, which enhances the accuracy of target detection. The overlapping-windows processing method converges on the optimal solution with its batch counterpart (i.e., processing batched data with RPCA), and both methods prove the robustness and efficiency of the RPCA over the classic PCA and the commonly used exponential averaging method.<\/jats:p>","DOI":"10.3390\/s16091409","type":"journal-article","created":{"date-parts":[[2016,9,1]],"date-time":"2016-09-01T10:04:28Z","timestamp":1472724268000},"page":"1409","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":15,"title":["Low-Rank Matrix Recovery Approach for Clutter Rejection in Real-Time IR-UWB Radar-Based Moving Target Detection"],"prefix":"10.3390","volume":"16","author":[{"given":"Donatien","family":"Sabushimike","sequence":"first","affiliation":[{"name":"Department of Electronics and Computer Engineering, Chonnam National University, 77 Yongbong-ro, Buk-gu, Gwangju 61186, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8754-6230","authenticated-orcid":false,"given":"Seung","family":"Na","sequence":"additional","affiliation":[{"name":"Department of Electronics and Computer Engineering, Chonnam National University, 77 Yongbong-ro, Buk-gu, Gwangju 61186, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jin","family":"Kim","sequence":"additional","affiliation":[{"name":"Department of Electronics and Computer Engineering, Chonnam National University, 77 Yongbong-ro, Buk-gu, Gwangju 61186, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ngoc","family":"Bui","sequence":"additional","affiliation":[{"name":"MOMED Solution, Gwangju 61008, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kyung","family":"Seo","sequence":"additional","affiliation":[{"name":"MOMED Solution, Gwangju 61008, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Gil","family":"Kim","sequence":"additional","affiliation":[{"name":"MOMED Solution, Gwangju 61008, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2016,9,1]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1388","DOI":"10.1109\/TVT.2015.2397312","article-title":"Blind Selection of Representative Observations for Sensor Radar Networks","volume":"64","author":"Bartoletti","year":"2015","journal-title":"IEEE Trans. Veh. Technol."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"157","DOI":"10.1109\/WCL.2013.120513.130760","article-title":"Sensor Radar Networks for Indoor Tracking","volume":"3","author":"Bartoletti","year":"2014","journal-title":"IEEE Wirel. Commun. Lett."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"149","DOI":"10.5369\/JSST.2014.23.3.149","article-title":"An Analysis of 2D Positional Accuracy of Human Bodies Detection Using the Movement of Mono-UWB Radar","volume":"23","author":"Mohammad","year":"2014","journal-title":"J. Sens. Sci. Technol."},{"key":"ref_4","first-page":"29","article-title":"Analysis of Clutter Reduction Techniques for Through the Wall Imaging in UWB Range","volume":"17","author":"Verma","year":"2009","journal-title":"PIERB"},{"key":"ref_5","unstructured":"Piccardi, M. (2004, January 10\u201313). Background subtraction techniques: A review. Proceedings of the IEEE International Conference on Systems, Man and Cybernetics, The Hague, The Netherlands."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Ganesh, A., Lin, Z., Wright, J., Wu, L., Chen, M., and Yi, M. (2009, January 13\u201316). Fast algorithms for recovering a corrupted low-rank matrix. Proceedings of the 3rd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, Aruba, Dutch Antilles.","DOI":"10.1109\/CAMSAP.2009.5413299"},{"key":"ref_7","unstructured":"Parinya, S. (2009). Principal Component Analysis, INTECH."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"223","DOI":"10.2174\/2213275910902030223","article-title":"Subspace learning for background modeling: A survey","volume":"2","author":"Bouwmans","year":"2009","journal-title":"Recent Pat. Comput. Sci."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"1509","DOI":"10.1016\/j.patcog.2003.11.010","article-title":"On incremental and robust subspace learning","volume":"34","author":"Li","year":"2004","journal-title":"Pat. Recognit."},{"key":"ref_10","unstructured":"He, J., Balzano, L., and Szlam, A. (2012, January 16\u201321). Incremental gradient on the grassmannian for online foreground and background separation in subsampled video. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Providence, RI, USA."},{"key":"ref_11","unstructured":"Feng, J., Xu, H., and Yan, S. (2013, January 5\u201310). Online robust PCA via stochastic optimization. Proceedings of the 26th Annual Conference on Neural Information Processing Systems, Lake Tahoe, NV, USA."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Qiu, C., Vaswani, N., and Hogben, L. (2013, January 26\u201331). Recursive robust PCA or recursive sparse recovery in large but structured noise. Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing, Vancouver, BC, Canada.","DOI":"10.1109\/ICASSP.2013.6638807"},{"key":"ref_13","unstructured":"Balzano, L., Nowak, R., and Recht, B. (October, January 29). Online identification and tracking of subspaces from highly incomplete information. Proceedings of the Allerton Conference on Communication, Control and Computing, Monticello, IL, USA."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Balzano, L., Recht, B., and Nowak, R. (2010, January 13\u201318). High-dimensional matched subspace detection when data are missing. Proceedings of the 2010 IEEE International Symposium on Information Theory, Austin, TX, USA.","DOI":"10.1109\/ISIT.2010.5513344"},{"key":"ref_15","unstructured":"Xu, X. (2014). Online Robust Principal Component Analysis for Background Subtraction: A System Evaluation on Toyota Car Data. [Master\u2019s Thesis, University of Illinois at Urbana Champaign]."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Zetik, R., Crabbe, S., Krajnak, J., Peyerl, P., Sachs, J., and Thoma, R. (2006). Detection and localization of persons behind obstacles using M-sequence through-the-wall radar. Proc. SPIE, 6201.","DOI":"10.1117\/12.667989"},{"key":"ref_17","unstructured":"Abujarad, F., and Omar, A. (2006, January 29). GPR data processing using the component-separation methods PCA and ICA. Proceedings of the IEEE International Workshop on Imaging Systems and Techniques, Minori, Italy."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Lin, Z., Ganesh, A., Wright, J., Wu, L., Chen, M., and Ma, Y. (2009, January 13\u201316). Fast convex optimization algorithms for exact recovery of a corrupted low-rank matrix. Proceedings of the International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, Aruba, Dutch Antilles.","DOI":"10.1109\/CAMSAP.2009.5413299"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Candes, E.J., Li, X., Ma, Y., and Wright, J. (2011). Robust principal component analysis?. JACM, 58.","DOI":"10.1145\/1970392.1970395"},{"key":"ref_20","unstructured":"Feng, J., Xu, H., and Yan, S. (July, January 26). Robust PCA in high-dimension: A deterministic approach. Proceedings of the International Conference on Machine Learning, Edinburgh, UK."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"64","DOI":"10.1198\/004017004000000563","article-title":"Robpca: A new approach to robust principal component analysis","volume":"47","author":"Hubert","year":"2005","journal-title":"Technometrics"},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Xu, H., Caramanis, C., and Mannor, S. (2009, January 10\u201312). Principal component analysis with contaminated data: The high dimensional case. Proceedings of the Information Theory Workshop, Volos, Greece.","DOI":"10.1109\/ITWNIT.2009.5158580"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"3047","DOI":"10.1109\/TIT.2011.2173156","article-title":"Robust PCA via outlier pursuit","volume":"58","author":"Xu","year":"2012","journal-title":"Trans. Inf. Theory"},{"key":"ref_24","unstructured":"Wright, J., Ganesh, A., Rao, S., and Ma, Y. (2009, January 7\u201310). Robust principal component analysis: Exact recovery of corrupted low-rank matrices via convex optimization. Proceedings of the 23rd Annual Conference on Neural Information Processing Systems, Vancouver, BC, Canada."},{"key":"ref_25","unstructured":"Bertsekas, D. (1982). Constrained Optimization and Lagrange Multiplier Method, Academic Press. [1st ed.]."},{"key":"ref_26","unstructured":"Lin, Z., Chen, M., Wu, L., and Ma, Y. (2010). The augmented Lagrange multiplier method for exact recovery of corrupted low-rank matrices."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1002\/ecjc.20303","article-title":"Performance Analysis of UWB Impulse Radar Receiver Using Parallel IPCP","volume":"90","author":"Hiroyuki","year":"2007","journal-title":"Electron. Commun. Jpn."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Hu, J., Yuan, Z., Zhu, G., Wang, L., and Huang, X. (2013, January 5\u201318). Moving Human Target CFAR Detection along Slow Time Profile in Ultrawide-Band Through-Wall Radar. Proceedings of the International Conference on Ultra-Wideband, Sydney, Australia.","DOI":"10.1109\/ICUWB.2013.6663834"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1007\/s12369-009-0039-x","article-title":"People Tracking with UWB Radar Using a Multiple-Hypothesis Tracking of Clusters (MHTC) Method","volume":"2","author":"Chang","year":"2010","journal-title":"Int. J. Soc. Robot."},{"key":"ref_30","unstructured":"Skolnik, M. I. (2001). Introduction to Radar Systems, McGraw-Hill. [3rd ed.]."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Daniels, D.J. (2004). Ground Penetrating Radar, The Institution of Electrical Engineers. [2nd ed.].","DOI":"10.1049\/PBRA015E"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"125","DOI":"10.1109\/JSTSP.2013.2286771","article-title":"Target Tracking for UWB Multistatic Radar Sensor Networks","volume":"8","author":"Sobhani","year":"2014","journal-title":"IEEE J. Sel. Top. Signal Process."},{"key":"ref_33","first-page":"203","article-title":"Investigation of Localization Accuracy for UWB Radar Operating in Complex Environment","volume":"10","year":"2013","journal-title":"Acta Polytech. Hung."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/16\/9\/1409\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T19:29:53Z","timestamp":1760210993000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/16\/9\/1409"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,9,1]]},"references-count":33,"journal-issue":{"issue":"9","published-online":{"date-parts":[[2016,9]]}},"alternative-id":["s16091409"],"URL":"https:\/\/doi.org\/10.3390\/s16091409","relation":{},"ISSN":["1424-8220"],"issn-type":[{"type":"electronic","value":"1424-8220"}],"subject":[],"published":{"date-parts":[[2016,9,1]]}}}