{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T01:53:12Z","timestamp":1760147592246,"version":"build-2065373602"},"reference-count":55,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2023,2,15]],"date-time":"2023-02-15T00:00:00Z","timestamp":1676419200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>A dedicated signal and data processing chain is proposed for a fully polarimetric Doppler surveillance S-band radar to extract the polarimetric signatures of moving targets. To extract the target\u2019s polarimetric features, detection, clustering, and tracking steps are realized for a multi-target environment in the range-Doppler domain. A dedicated data fusion method for all four polarimetric radar channel signals is implemented to take full advantage of the additional polarimetric information and improve the detection performance. While tracking each particular target, polarization information is collected and used to describe their polarization scattering characteristics. Using the polarimetric H\/A\/\u03b1 decomposition technique, the polarimetric features of moving automotive targets are extracted and investigated. The developed processing chain has been applied to the signals scattered from vehicles moving in a highway. By employing both time averaging and spatial averaging of the statistical coherency matrix, the polarimetric signatures of both moving vehicles and static clutter have been presented in the two-dimensional H\/\u03b1 plane. It has been found that the spatial averaging approach results in polarimetric signatures of moving vehicles that give the opportunity to directly and without consideration of the motion of the targets compare the polarization features of moving targets and static clutter. Therefore, this method can be used to improve the performance of target detection or target classification.<\/jats:p>","DOI":"10.3390\/rs15041060","type":"journal-article","created":{"date-parts":[[2023,2,15]],"date-time":"2023-02-15T04:47:24Z","timestamp":1676436444000},"page":"1060","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["An Advanced Data Processing Algorithm for Extraction of Polarimetric Radar Signatures of Moving Automotive Vehicles Using the H\/A\/\u03b1 Decomposition Technique"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5928-5528","authenticated-orcid":false,"given":"Detmer A.","family":"Bosma","sequence":"first","affiliation":[{"name":"Microwave Sensing, Signals & Systems (MS3), Faculty of Electrical Engineering, Computer Science and Mathematics, Delft University of Technology, Mekelweg 4, 2628 CD Delft, The Netherlands"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6791-0402","authenticated-orcid":false,"given":"Oleg A.","family":"Krasnov","sequence":"additional","affiliation":[{"name":"Microwave Sensing, Signals & Systems (MS3), Faculty of Electrical Engineering, Computer Science and Mathematics, Delft University of Technology, Mekelweg 4, 2628 CD Delft, The Netherlands"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Alexander","family":"Yarovoy","sequence":"additional","affiliation":[{"name":"Microwave Sensing, Signals & Systems (MS3), Faculty of Electrical Engineering, Computer Science and Mathematics, Delft University of Technology, Mekelweg 4, 2628 CD Delft, The Netherlands"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2023,2,15]]},"reference":[{"key":"ref_1","unstructured":"Richards, M.A. (2013). 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