{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,12]],"date-time":"2026-05-12T17:17:37Z","timestamp":1778606257792,"version":"3.51.4"},"reference-count":45,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2022,4,7]],"date-time":"2022-04-07T00:00:00Z","timestamp":1649289600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"The Natural Science Foundation of Hunan Province, China","award":["2021JJ40358"],"award-info":[{"award-number":["2021JJ40358"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62173140"],"award-info":[{"award-number":["62173140"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Hunan Province Natural Science Foundation","award":["2021JJ30452"],"award-info":[{"award-number":["2021JJ30452"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Due to the small size and various types of foreign object debris (FOD), radar detection of FOD on airport runways is a great challenge, and there are often a large number of false alarms in the detection results. Arc-scanning synthetic aperture radar (AS-SAR) is an emerging method for detecting FOD targets, which achieves omnidirectional coverage with a very high azimuth resolution. However, this method faces a similar challenge. A direct way to reduce false alarms is to increase the detection threshold based on enhancing the target signal-to-noise ratio (SNR), and in this paper, the coherent accumulation of multiple images is used to improve the target SNR. The stable phase is also an important feature of the target distinguishing background. Therefore, it is important to maintain the stability of the target phase. Aiming at the systematic phase drift (SPD) caused by atmospheric disturbance and system hardware, a spatial and temporal model is established, a corresponding correction approach is proposed, and the performance of the correction approach is validated by field experiments.<\/jats:p>","DOI":"10.3390\/rs14081787","type":"journal-article","created":{"date-parts":[[2022,4,7]],"date-time":"2022-04-07T21:08:22Z","timestamp":1649365702000},"page":"1787","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["A Correction Method to Systematic Phase Drift of a High Resolution Radar for Foreign Object Debris Detection"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4552-592X","authenticated-orcid":false,"given":"Yuming","family":"Wang","sequence":"first","affiliation":[{"name":"College of Information Science and Engineering, Hunan Normal University, Changsha 410081, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qian","family":"Song","sequence":"additional","affiliation":[{"name":"Hunan GHz Information Technology Co., Ltd., Changsha 410073, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4840-9716","authenticated-orcid":false,"given":"Jian","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Electronic Science and Engineering, National University of Defense Technology, Changsha 410073, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3951-5699","authenticated-orcid":false,"given":"Baoqiang","family":"Du","sequence":"additional","affiliation":[{"name":"College of Information Science and Engineering, Hunan Normal University, Changsha 410081, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Pengyu","family":"Wang","sequence":"additional","affiliation":[{"name":"Hunan GHz Information Technology Co., Ltd., Changsha 410073, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,4,7]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"65","DOI":"10.1016\/j.ast.2014.01.001","article-title":"Foreign object damage on the leading edge of gas turbine blades","volume":"33","author":"Marandi","year":"2014","journal-title":"Aerosp. Sci. Technol."},{"key":"ref_2","unstructured":"ICAO (2019, January 24\u201326). Proposals for amendment to pans-aerodromes (DOC 9981). Proceedings of the third meeting of the aerodromes operations and planning-Working Group (AOP\/WG\/3), Bangkok, Thailand. Available online: https:\/\/www.icao.int\/APAC\/Meetings\/Pages\/2019-AOP-SG3-GRF-Seminar.aspx."},{"key":"ref_3","first-page":"22","article-title":"Foreign Object Debris (FOD) Detection Research","volume":"11","author":"Patterson","year":"2008","journal-title":"Int. Airpt. Rev."},{"key":"ref_4","unstructured":"Woodworth, E. (2010, January 20\u201322). Procedures for FOD Detection System Performance Assessments: Radar-Based and Dual Sensor Systems. Proceedings of the 2010 FAA Worldwide Airport Technology Transfer Conference, Atlantic City, NJ, USA."},{"key":"ref_5","unstructured":"Lazar, P., and Herricks, E.E. (2010, January 20\u201322). Procedures for FOD Detection System Performance Assessments: Electro-Optical FOD Detection System. Proceedings of the FAA Worldwide AirportTechnology Transfer Conference, Atlantic City, NJ, USA."},{"key":"ref_6","unstructured":"Shelley, P.H., Vahey, P.G., Werner, G.J., and Kisch, R.A. (2014). Multispectral Imaging System and Method for Detecting Foreign Object Debris. (14\/552,697), US Patent."},{"key":"ref_7","unstructured":"Herricks, E.E., Woodworth, E., and Patterson, J. (2021, October 20). Performance Assessment of a Hybrid Radar and Electro-Optical Foreign Object Debris Detection System. DOT\/FAA\/TC-12\/22. U.S. Department of Transportation Federal Aviation Administration. 2012; pp. 1\u201346, Available online: https:\/\/www.tc.faa.gov\/its\/worldpac\/techrpt\/tc12-22.pdf."},{"key":"ref_8","unstructured":"Leonard, T., Lamont-Smith, T., Hodges, R., and Beasley, P. 94-GHz Tarsier radar measurements of wind waves and small targets. European Microwave Week 2011: Wave to the Future, EuMW 2011, Proceedings of the 8th European Radar Conference, EuRAD, Manchester, UK, 12\u201314 October 2011, IEEE. Available online: https:\/\/ieeexplore.ieee.org\/document\/6100969."},{"key":"ref_9","unstructured":"(2021, October 20). Trex Aviation Systems. FOD Finder. Available online: www.fodfinder.com\/index.html."},{"key":"ref_10","unstructured":"(2021, October 20). Xsight Systems. FODetect Installation Manual. Available online: www.xsightsys.com."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Feil, P., Menzel, W., Nguyen, T.P., Pichot, C., and Migliaccio, C. (2008, January 30\u201331). Foreign objects debris detection (FOD) on airport runways using a broadband 78 GHz sensor. Proceedings of the 2008 European Radar Conference, Amsterdam, The Netherlands.","DOI":"10.1109\/EUMC.2008.4751779"},{"key":"ref_12","first-page":"917","article-title":"Echo Modeling of Radar for Foreign Objects Debris Detection on Airport Runways","volume":"11","author":"Wu","year":"2013","journal-title":"J. Terahertz Sci. Electron. Inf. Technol."},{"key":"ref_13","first-page":"909","article-title":"Study and design on FOD detection and surveillance system for airport runway","volume":"41","author":"Yu","year":"2011","journal-title":"Laser Infrared"},{"key":"ref_14","first-page":"73","article-title":"Airport runway radar image de-noising based on 2-D shift-invariance hybrid transform","volume":"37","author":"Liu","year":"2015","journal-title":"Syst. Eng. Electron."},{"key":"ref_15","unstructured":"Cao, T.T. (2012). The Build of Airport Runway Fod Detection System and Algorithm Study Based on Radar Image. [Master\u2019s Thesis, Beijing Jiaotong University]."},{"key":"ref_16","unstructured":"Curlander, J.C., and McDonough, R.N. (1991). Synthetic Aperture Radar: Systems and Signal Processing, Wiley."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Huang, Z., Pan, Z., and Lei, B. (2017). Transfer Learning with Deep Convolutional Neural Network for SAR Target Classification with Limited Labeled Data. Remote Sens., 9.","DOI":"10.3390\/rs9090907"},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Wang, Y., Wang, C., Zhang, H., Dong, Y., and Wei, S. (2019). A SAR Dataset of Ship Detection for Deep Learning under Complex Backgrounds. Remote Sens., 11.","DOI":"10.3390\/rs11070765"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Bianchini Ciampoli, L., Gagliardi, V., Ferrante, C., Calvi, A., D\u2019Amico, F., and Tosti, F. (2020). Displacement Monitoring in Airport Runways by Persistent Scatterers SAR Interferometry. Remote Sens., 12.","DOI":"10.3390\/rs12213564"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"3757","DOI":"10.1109\/JSTARS.2018.2863369","article-title":"Impact of Wind-Induced Scatterers Motion on GB-SAR Imaging","volume":"11","author":"Lort","year":"2018","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Aguasca, A., Broquetas, A., F\u00e1bregas, X., Mallorqui, J.J., Vilalvilla, P., Biscamps, J., Llop, J., Gallart, M., Gil, E., and Gras, A. (2021, January 17\u201322). Hydrosoil, Soil Moisture and Vegetation Parameters Retrieval with a C-Band GB-SAR: Campaign Implementation and First Results. Proceedings of the 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, Brussels, Belgium.","DOI":"10.1109\/IGARSS47720.2021.9554572"},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Andre, D., Morrison, K., Blacknell, D., Muff, D., Nottingham, M., and Stevenson, C. (2015, January 27\u201330). Very high resolution Coherent Change Detection. Proceedings of the 2015 IEEE Radar Conference (RadarCon), Arlington, VA, USA.","DOI":"10.1109\/RADAR.2015.7131074"},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Andr\u00e9, D., Blacknell, D., and Morrison, K. (May, January 29). Spatially variant incoherence trimming for improved bistatic SAR CCD. Proceedings of the 2013 IEEE Radar Conference (RadarCon13), Ottawa, ON, Canada.","DOI":"10.1109\/RADAR.2013.6586156"},{"key":"ref_24","first-page":"41","article-title":"Monitoring of displacements with ground-based microwave interferometry: IBIS-S and IBIS-L","volume":"4","author":"Roedelsperger","year":"2010","journal-title":"J. Appl. Geod."},{"key":"ref_25","unstructured":"(2022, February 20). Federal Aviation Administration. Airport Engineering, Design, & Construction\u2014Airports, Available online: https:\/\/www.faa.gov\/airports\/engineering\/."},{"key":"ref_26","unstructured":"(2022, February 20). Civil Aviation Administration of China. Regulations on the Administration of Special Equipment for Civil Airports. CCAR-137CA-R4, Available online: http:\/\/www.caac.gov.cn\/XXGK\/XXGK\/MHGZ\/201706\/t20170612_44707.html."},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Klausing, H. (1989, January 4\u20137). Feasibility of a synthetic aperture radar with rotating antennas (ROSAR). Proceedings of the Ninth European Microwave Conf., London, UK.","DOI":"10.1109\/EUMA.1989.333979"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"2773","DOI":"10.1109\/TGRS.2013.2265700","article-title":"Development of a Truck-Mounted Arc-Scanning Synthetic Aperture Radar","volume":"52","author":"Lee","year":"2014","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Wang, Y., Song, Y., Lin, Y., Li, Y., Zhang, Y., and Hong, W. (2019). Interferometric DEM-Assisted High Precision Imaging Method for ArcSAR. Sensors, 19.","DOI":"10.3390\/s19132921"},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Takenaka, H., Sakashita, T., Higuchi, A., and Nakajima, T. (2020). Geolocation Correction for Geostationary Satellite Observations by a Phase-Only Correlation Method Using a Visible Channel. Remote Sens., 12.","DOI":"10.3390\/rs12152472"},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Zebker, H. (2021). Accuracy of a Model-Free Algorithm for Temporal InSAR Tropospheric Correction. Remote Sens., 13.","DOI":"10.3390\/rs13030409"},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Hu, Z., and Mallorqu\u00ed, J.J. (2019). An Accurate Method to Correct Atmospheric Phase Delay for InSAR with the ERA5 Global Atmospheric Model. Remote Sens., 11.","DOI":"10.3390\/rs11171969"},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Qin, F., Bu, X., Liu, Y., Liang, X., and Xin, J. (2021). Foreign Object Debris Automatic Target Detection for Millimeter-Wave Surveillance Radar. Sensors, 21.","DOI":"10.3390\/s21113853"},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Wan, Y., Liang, X., Bu, X., and Liu, Y. (2021). FOD Detection Method Based on an Iterative Adaptive Approach for Millimeter-Wave Radar. Sensors, 21.","DOI":"10.3390\/s21041241"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"537","DOI":"10.1109\/LGRS.2010.2090647","article-title":"Atmospheric Phase Screen in Ground-Based Radar: Statistics and Compensation","volume":"8","author":"Iannini","year":"2011","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_36","first-page":"72","article-title":"Atmospheric artifact compensation for deformation monitoring with ground-based radar","volume":"23","author":"Dong","year":"2014","journal-title":"Eng. Surv. Mapp."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/TGRS.2022.3229302","article-title":"A Grid Partition Method for Atmospheric Phase Compensation in GB-SAR","volume":"60","author":"Deng","year":"2022","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"1459","DOI":"10.1109\/TGRS.2005.848707","article-title":"Permanent Scatterers Analysis for Atmospheric Correction in Ground Based SAR Interferometry","volume":"43","author":"Noferini","year":"2005","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"5989","DOI":"10.1109\/TGRS.2014.2325905","article-title":"Arc FMCW SAR and Applications in Ground Monitoring","volume":"52","author":"Luo","year":"2014","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_40","first-page":"637","article-title":"FOD Detection on Airport Runway with an Adaptive CFAR Technique","volume":"Volume 246","author":"Liu","year":"2014","journal-title":"International Conference on Communications Signal Processing and Systems Lecture Notes in Electrical Engineering"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"1769","DOI":"10.1109\/TAES.2017.2672018","article-title":"Multimodel CFAR Detection in Foliage Penetrating SAR Images","volume":"53","author":"Izzo","year":"2017","journal-title":"IEEE Trans. Aerosp. Electron. Syst."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"106299","DOI":"10.1016\/j.asoc.2020.106299","article-title":"Feature selection via normative fuzzy information weight with application into tumor classification","volume":"92","author":"Dai","year":"2020","journal-title":"Appl. Soft Comput."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"2174","DOI":"10.1109\/TFUZZ.2017.2768044","article-title":"Maximal Discernibility Pairs based Approach to Attribute Reduction in Fuzzy Rough Sets","volume":"26","author":"Dai","year":"2018","journal-title":"IEEE Trans. Fuzzy Syst."},{"key":"ref_44","first-page":"1","article-title":"The evidence framework applied to fuzzy hypersphere SVM for UWB SAR landmine detection","volume":"3","author":"Jin","year":"2006","journal-title":"ICSP2006 Proc."},{"key":"ref_45","doi-asserted-by":"crossref","unstructured":"Webb, A.R. (2002). Statistical Pattern Recognition, John Wiley & Sons Ltd.. [3rd ed.].","DOI":"10.1002\/0470854774"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/8\/1787\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T22:50:06Z","timestamp":1760136606000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/8\/1787"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,4,7]]},"references-count":45,"journal-issue":{"issue":"8","published-online":{"date-parts":[[2022,4]]}},"alternative-id":["rs14081787"],"URL":"https:\/\/doi.org\/10.3390\/rs14081787","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,4,7]]}}}