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Local Detection of Moving Targets in SAR Image Based on NRS Hypotheses
Blekinge Institute of Technology, Faculty of Engineering, Department of Mathematics and Natural Sciences.ORCID iD: 0000-0003-3945-8951
2018 (English)In: IEEE Transactions on Geoscience and Remote Sensing, ISSN 0196-2892, E-ISSN 1558-0644, Vol. 56, no 10, p. 6101-6110Article in journal (Refereed) Published
Abstract [en]

Ground moving target indication (GMTI) is one of the important applications of synthetic aperture radar (SAR). This paper introduces a GMTI method for local detection of the ground moving targets in SAR image based on normalized relative speed (NRS) hypotheses. The input of the GMTI method is a complex SAR image where areas of interest for GMTI are locally selected. The output of the method includes the detected targets, the NRSs with respect to the SAR platform, the locations where the detected targets are focused, and the SAR images of the detected targets. The mathematical background of the GMTI method is presented in detail. The method is validated with the data delivered by the Coherent All-Radio Band Sensor, an airborne ultrawideband-ultrawidebeam low-frequency SAR system. The shortcomings of the introduced method are investigated and followed with the solutions. IEEE

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers Inc. , 2018. Vol. 56, no 10, p. 6101-6110
Keywords [en]
Azimuth, Clutter, Doppler effect, Focusing, Ground moving target indication (GMTI), History, likelihood-ratio, normalized relative speed (NRS), Synthetic aperture radar, synthetic aperture radar (SAR), Trajectory, ultrawideband ultrawidebeam (UWB), Clutter (information theory), Trajectories, Ultra-wideband (UWB), Complex SAR images, Ground moving target indication, Ground moving targets, Likelihood ratios, Low-frequency, Moving targets, Relative speed, Radar imaging
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:bth-16335DOI: 10.1109/TGRS.2018.2831908ISI: 000446300700040Scopus ID: 2-s2.0-85047646188OAI: oai:DiVA.org:bth-16335DiVA, id: diva2:1214784
Available from: 2018-06-07 Created: 2018-06-07 Last updated: 2021-03-26Bibliographically approved

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Vu, Viet Thuy

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