Remote Sensing (Jun 2024)

Experiment for Oil Spill Detection Based on Dual-Frequency QZSS Reflected Signals Using Drone-Borne GNSS-R

  • Runqi Liu,
  • Fan Gao,
  • Cheng Jing,
  • Xiao Li,
  • Dongmei Song,
  • Bin Wang,
  • Huyu Sun,
  • Yahui Kong,
  • Zhenyao Zhong,
  • Shuo Gu,
  • Cong Yin,
  • Weihua Bai

DOI
https://doi.org/10.3390/rs16132346
Journal volume & issue
Vol. 16, no. 13
p. 2346

Abstract

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Oil spill detection plays an important role in marine environment protection. The technique of global navigation satellite system-reflectometry (GNSS-R) has the advantage of a short revisit time, which could help with timely cleanup of marine oil pollution. The conventional GNSS-R oil spill detection algorithm can resolve only the dielectric constant of oil based on power ratio measurements, while that of water cannot be realized. This is because the dielectric constant of water is much larger than that of oil such that the range of the equation used in the conventional algorithm is inadequate. To resolve this problem, we proposed a new algorithm containing a new equation with a larger scope, which has never been applied previously to GNSS-R oil spill detection. We derived a lookup method to resolve the dielectric constant of both oil and water. To validate our method, a drone-borne GNSS-R experiment based on dual-frequency QZSS reflection signals was conducted on 17 July 2023 using experimental pools simulating oil spills. Raw IF data in the L1 and L5 bands, collected using dual antennas and a data recorder, were processed using a software-defined receiver to deduce the power ratios and SNR of the GNSS signals. Results showed that the proposed algorithm is capable of resolving the dielectric constants of the reflected surface. In addition, the L5 signal was found to provide more detail and better contrast than the L1 C/A signal.

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