4.7 Article

DVB-S Based Passive Polarimetric ISAR-Methods and Experimental Validation

期刊

IEEE SENSORS JOURNAL
卷 21, 期 5, 页码 6056-6070

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JSEN.2020.3037091

关键词

Passive radar; Surveillance; Digital video broadcasting; Scattering; Satellite broadcasting; Sensors; Transponders; Passive ISAR; polarimetric data; satellite signals of opportunity; DVB-S-based passive radar

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This study focuses on passive polarimetric ISAR for ship target imaging using DVB-S signals of opportunity. The research shows that polarimetric diversity can be beneficial for target classification by separating different scattering mechanisms in the polarimetric domain and enhancing ISAR image quality.
In this work, we focus on passive polarimetric ISAR for ship target imaging using DVB-S signals of opportunity. A first goal of the research is to investigate if, within the challenging passive environment, different scattering mechanisms, belonging to distinct parts of the imaged target, can be separated in the polarimetric domain. Furthermore, a second goal is at verifying if polarimetric diversity could enable the formation of ISAR products with enhanced quality with respect to the single channel case, particularly in terms of better reconstruction of the target shape. To this purpose, a dedicated trial has been conducted along the river Rhine in Germany by means of an experimental DVB-S based system developed at Fraunhofer FHR and considering a ferry as cooperative target. To avoid inaccuracies due to data-driven motion compensation procedures and to fairly interpret the polarimetric results, we processed the data by means of a known-motion back-projection algorithm obtaining ISAR images at each polarimetric channel. Then, different approaches in the polarimetric domain have been introduced. The first one is based on the well-known Pauli Decomposition. The others can be divided in two main groups: (i) techniques aimed at separating the different backscattering mechanisms, and (ii) image domain techniques to fuse the polarimetric information in a single ISAR image with enhanced quality. The different considered techniques have been applied to several data sets with distinct bistatic geometries. The obtained results clearly demonstrate the potentialities of polarimetric diversity that could be fruitfully exploited for classification purposes.

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