Spatial resolution improvement in GNSS-based SAR using multi-static acquisitions and feature extraction

Fabrizio Santi, Marta Bucciarelli, Debora Pastina, Michail Antoniou, Mikhail Cherniakov

Research output: Contribution to journalArticlepeer-review

42 Citations (Scopus)
306 Downloads (Pure)


This paper considers the exploitation of navigation satellite systems as opportunity transmitters for bistatic and multistatic synthetic aperture radar (SAR). The simultaneous availability of multiple satellites over a scene of interest at different viewing angles allows multistatic SAR acquisitions using a single receiver on or near the ground. The resulting spatial diversity could be used to drastically improve image resolution or to enhance image information space. To exploit the availability of multiple satellites, two data fusion approaches are here considered. In the former, point features of the single images obtained from different perspectives are extracted and then combined, whereas in the latter, a multistatic image is first obtained by combining the single channel data at the image level and then the point features are extracted. This is achieved by considering ad hoc CLEAN-like techniques. These techniques have been developed on both the analytical and simulation levels and experimentally verified with real GNSS-based SAR imagery. The techniques described here are not limited to GNSS-based SAR but may be applied to any multistatic SAR system.
Original languageEnglish
Article number7515203
Pages (from-to)6217 - 6231
Number of pages15
JournalIEEE Transactions on Geoscience and Remote Sensing
Issue number10
Early online date18 Jul 2016
Publication statusPublished - Oct 2016


  • Bistatic synthetic aperture radar (BSAR)
  • feature extraction
  • global navigation satellite system (GNSS)-based SAR
  • multistatic SAR (MSAR)
  • Passive SAR

ASJC Scopus subject areas

  • Earth and Planetary Sciences(all)
  • Electrical and Electronic Engineering


Dive into the research topics of 'Spatial resolution improvement in GNSS-based SAR using multi-static acquisitions and feature extraction'. Together they form a unique fingerprint.

Cite this