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

Authors :
Runqi Liu
Fan Gao
Cheng Jing
Xiao Li
Dongmei Song
Bin Wang
Huyu Sun
Yahui Kong
Zhenyao Zhong
Shuo Gu
Cong Yin
Weihua Bai
Source :
Remote Sensing, Vol 16, Iss 13, p 2346 (2024)
Publication Year :
2024
Publisher :
MDPI AG, 2024.

Abstract

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.

Details

Language :
English
ISSN :
20724292
Volume :
16
Issue :
13
Database :
Directory of Open Access Journals
Journal :
Remote Sensing
Publication Type :
Academic Journal
Accession number :
edsdoj.1aefd85aa4bc42808b6c377ef4798a4e
Document Type :
article
Full Text :
https://doi.org/10.3390/rs16132346