{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,7]],"date-time":"2026-07-07T04:09:37Z","timestamp":1783397377907,"version":"3.54.6"},"reference-count":23,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2018,9,3]],"date-time":"2018-09-03T00:00:00Z","timestamp":1535932800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["U1633106, U1733116 , 61471365"],"award-info":[{"award-number":["U1633106, U1733116 , 61471365"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"National University\u2019s Basic Research Foundation of China","award":["No.3122017007"],"award-info":[{"award-number":["No.3122017007"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>This paper presents a high-fidelity inhomogeneous ground clutter simulation method for airborne phased array Pulse Doppler (PD) radar aided by a digital elevation model (DEM) and digital land classification data (DLCD). The method starts by extracting the basic geographic information of the Earth\u2019s surface scattering points from the DEM data, then reads the Earth\u2019s surface classification codes of Earth\u2019s surface scattering points according to the DLCD. After determining the landform types, different backscattering coefficient models are selected to calculate the backscattering coefficient of each Earth surface scattering point. Finally, the high-fidelity inhomogeneous ground clutter simulation of airborne phased array PD radar is realized based on the Ward model. The simulation results show that the classifications of landform types obtained by the proposed method are more abundant, and the ground clutter simulated by different backscattering coefficient models is more real and effective.<\/jats:p>","DOI":"10.3390\/s18092925","type":"journal-article","created":{"date-parts":[[2018,9,3]],"date-time":"2018-09-03T10:50:51Z","timestamp":1535971851000},"page":"2925","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["High-Fidelity Inhomogeneous Ground Clutter Simulation of Airborne Phased Array PD Radar Aided by Digital Elevation Model and Digital Land Classification Data"],"prefix":"10.3390","volume":"18","author":[{"given":"Hai","family":"Li","sequence":"first","affiliation":[{"name":"Tianjin Key Lab for Advanced Signal Processing, Civil Aviation University of China, Tianjin 300300, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jie","family":"Wang","sequence":"additional","affiliation":[{"name":"Tianjin Key Lab for Advanced Signal Processing, Civil Aviation University of China, Tianjin 300300, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yi","family":"Fan","sequence":"additional","affiliation":[{"name":"Tianjin Key Lab for Advanced Signal Processing, Civil Aviation University of China, Tianjin 300300, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jungong","family":"Han","sequence":"additional","affiliation":[{"name":"School of Computing &amp; Communications, Lancaster University, Lancaster LA1 4YW, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2018,9,3]]},"reference":[{"key":"ref_1","first-page":"1","article-title":"Prospect for Technology of Airborne Early Warning Radar","volume":"1","author":"Zhang","year":"2015","journal-title":"Mod. Radar"},{"key":"ref_2","first-page":"113","article-title":"A method of feature selection in the aspect of specific identification of radar signals","volume":"65","author":"Dudczyk","year":"2017","journal-title":"Bull. Pol. Acad. Sci.-Tech. Sci."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Dudczyk, J. (2016). Radar Emission Sources Identification Based on Hierarchical Agglomerative Clustering for Large Data Sets. J. Sens., 2016.","DOI":"10.1155\/2016\/1879327"},{"key":"ref_4","first-page":"46","article-title":"Object Detection and Recognition System Using Artificial Neural Networks and Drones","volume":"6","author":"Piedrow","year":"2018","journal-title":"J. Electr. Eng."},{"key":"ref_5","unstructured":"Matuszewski, J., and Paradowski, L. (1998, January 20\u201322). The knowledge based approach for emitter identification. Proceedings of the International Conference on Microwaves and Radar, Krakow, Poland."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Matuszewski, J. (2012, January 21\u201323). The radar signature in recognition system database. Proceedings of the International Conference on Microwave Radar and Wireless Communications, Warsaw, Poland.","DOI":"10.1109\/MIKON.2012.6233565"},{"key":"ref_7","first-page":"1199","article-title":"An overview of knowledge-aided clutter mitigation methods for airborne radar","volume":"40","author":"Fan","year":"2012","journal-title":"Chin. J. Electron."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"41","DOI":"10.1109\/MSP.2006.1593336","article-title":"Knowledge-aided adaptive radar at DARPA: An overview","volume":"23","author":"Guerci","year":"2006","journal-title":"IEEE Signal Process. Mag."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Wang, A.G. (2013). Terrain Clutter Modeling and Simulation for Airborne Radar System Based on Digital Elevation Model. [Master\u2019s Thesis, University of Electronic Science and Technology of China].","DOI":"10.1109\/MMWCST.2012.6238182"},{"key":"ref_10","first-page":"5","article-title":"Clutter Simulation for Airborne Pulse-Doppler Radar Based on Natural Ground Scene","volume":"29","author":"Fan","year":"2007","journal-title":"Mod. Radar"},{"key":"ref_11","unstructured":"Hellard, D.L., Henry, J.P., Agnesina, E., and Moruzzis, M. (1995, January 8\u201311). Ground clutter simulation for surface-based radars. Proceedings of the IEEE International Radar Conference, Alexandria, VA, USA."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"374","DOI":"10.1049\/iet-rsn.2010.0036","article-title":"New method for generating site-specific clutter map for land-based radar by using multimodal remote-sensing images and digital terrain data","volume":"5","author":"Kurekin","year":"2011","journal-title":"IET Radar Sonar Navig."},{"key":"ref_13","first-page":"511","article-title":"Research on Ground Clutter Modeling of Airborne Cognitive Radar Based on Digital Elevation Model Data","volume":"45","author":"Rao","year":"2016","journal-title":"J. Univ. Electron. Sci. Technol. China"},{"key":"ref_14","unstructured":"Zhou, M. (2016). Detection of Low-Altitude Wind Shear Based on Knowledge. [Master\u2019s Thesis, Civil Aviation University of China]."},{"key":"ref_15","unstructured":"Hong, L.N. (2003). Research on Radar Land Clutter Modeling and Simulation. [Master\u2019s Thesis, National University of Defense Technology]."},{"key":"ref_16","first-page":"52","article-title":"Simulation and Analysis of the Sea Surface Backscattering Coefficient for Radio Fuze","volume":"38","author":"Su","year":"2017","journal-title":"J. Ordnance Equip. Eng."},{"key":"ref_17","first-page":"1","article-title":"Reflectivity Model of Ground\/Sea Clutter","volume":"14","author":"Peng","year":"2000","journal-title":"J. Airforce Radar Acad."},{"key":"ref_18","unstructured":"Huang, P.K., and Wang, Y.F. (1987). Microwave Remote Sensing Volume II: Radar Remote Sensing and Surface Scattering and Emission Theory, Science Press."},{"key":"ref_19","first-page":"18","article-title":"Reflectivity Model of Low Grazing Angle Radar Land Clutter","volume":"30","author":"Feng","year":"2005","journal-title":"Fire Control Command Control"},{"key":"ref_20","unstructured":"Ward, J. (1994). Space-Time Adaptive Processing for Airborne Radar, MIT Lincoln Laboratory. MIT Technical Report 1015."},{"key":"ref_21","unstructured":"Wang, Y.L., and Peng, Y.N. (2000). Space-Time Adaptive Signal Processing, Tsinghua University Press."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Tachikawa, T., Hato, M., Kaku, M., and Iwasaki, A. (2011, January 24\u201329). Characteristics of ASTER GDEM version 2. Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, Vancouver, BC, Canada.","DOI":"10.1109\/IGARSS.2011.6050017"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"1080","DOI":"10.1109\/TAES.2006.248199","article-title":"Implementing digital terrain data in knowledge-aided space-time adaptive processing","volume":"42","author":"Capraro","year":"2006","journal-title":"IEEE Trans. Aerosp. Electron. 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