Vol. 11 No. 9 (2025): September
Open Access
Peer Reviewed

Application of GNSS Interferometric Reflectometry (GNSS-IR) for Monitoring Tidal Variations in Coastal Zones

Authors

Hairul Zulkifli , Danar Guruh Pratomo , Khomsin

DOI:

10.29303/jppipa.v11i9.12539

Published:

2025-09-25

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Abstract

GNSS-Interferometric Reflectometry (GNSS-IR) utilizes Signal-to-Noise Ratio (SNR) data from GNSS satellites to estimate sea level variations. This study applied GNSS-IR using GPS L1 SNR data from four CORS stations (CBEL, CLKI, CHAI, CLMP), paired with their nearest tide gauge stations (BLTG, LBKI, AMHI, LMPA) for validation. Data in RINEX 2.11 format at 30-second intervals were processed, considering antenna heights above the sea surface to extract reflection frequencies. Results indicate strong agreement at the LMPA (r = 0.94, RMSE = 0.17 m) and BLTG (r = 0.90, RMSE = 0.37 m) pairs, demonstrating the reliability of GNSS-IR under favorable conditions. The AMHI pair showed moderate correlation (r = 0.68, RMSE = 0.45 m), while the LBKI pair exhibited no meaningful correlation (r = –0.07), likely due to severe multipath disturbance and local site limitations. These findings suggest that GNSS-IR can provide cost-efficient and accurate sea level estimates, but performance is highly site-dependent and influenced by environmental and instrumental factors. The study highlights the potential of GNSS-IR to complement conventional tide gauges in Indonesia, while emphasizing the need for careful station selection and multi-frequency analysis in future applications.

Keywords:

GNSS GNSS-IR Harmonic analysis Signal to noise ratio (SNR) Tides

References

Axelrad, P., Larson, K., & Jones, B. (2005). Use of the correct satellite repeat period to characterize and reduce site-specific multipath errors. Proceedings of the 18th International Technical Meeting of the Satellite Division of The Institute of Navigation, ION GNSS 2005, 2005(January 2005), 2638–2648. https://epic.awi.de/id/eprint/35979/

Bolbakov, R. G., Sinitsyn, A. V., & Tsvetkov, V. Y. (2020). Methods of comparative analysis. Journal of Physics: Conference Series, 1679(5). https://doi.org/10.1088/1742-6596/1679/5/052047

Cahyadi, M. N., Bawasir, A., Susilo, & Arief, S. (2023). Analysis of Water Level Monitoring using GNSS Interferometric Reflectometry in River Waters. IOP Conference Series: Earth and Environmental Science, 1276(1), 0–12. https://doi.org/10.1088/1755-1315/1276/1/012020

Chai, H., Chen, K., & Lin, J. (2025). Transforming Coastal GNSS Stations Into Tsunami Gauges With Adaptive Window Interferometric Reflectometry. IEEE Transactions on Geoscience and Remote Sensing, 63, 1–10. https://doi.org/10.1109/TGRS.2025.3550744

Chamoli, V., Prakash, R., & Vidyarthi, A. (2024). First Pioneering Soil Moisture Estimation Software Leveraging Navigation Signals from India’s NavIC Satellite. 2024 IEEE Space, Aerospace and Defence Conference (SPACE), 808–811. https://doi.org/10.1109/SPACE63117.2024.10667839

Chen, Z., & Jin, S. (2024). High-frequency Water Level Estimation in the Yangtze River from GNSS-Interferometric Reflectometry. 2024 Photonics & Electromagnetics Research Symposium (PIERS), 1–5. https://doi.org/10.1109/PIERS62282.2024.10618080

Ding, Q., Liang, Y., Liang, X., Ren, C., Yan, H., Liu, Y., Zhang, Y., Lu, X., Lai, J., & Hu, X. (2023). Soil Moisture Retrieval Using GNSS-IR Based on Empirical Modal Decomposition and Cross-Correlation Satellite Selection. Remote Sensing, 15(13). https://doi.org/10.3390/rs15133218

Georgiadou, Y., & Kleusberg, A. (1988). On carrier signal multipath effects in relative GPS positioning. Map Collector, 13(3), 172–179. https://doi.org/10.1007/BF03655245

Ghiasi, Y., Farzaneh, S., Parvazi, K., & Duguay, C. R. (2021). Amplitue Estimation of Dominant Tidal Constituents Using Gnss Interferometric Reflectometry Technique. 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, 8546–8549. https://doi.org/10.1109/IGARSS47720.2021.9554876

Ha, J., Kambe, M., & Pe, J. (2012). Data Mining. In Data Mining: Concepts and Techniques. Elsevier. https://doi.org/10.1016/C2009-0-61819-5

Handoko, E. Y., Richasari, D. S., & Pratomo, D. G. (2021). Seasonal and Interannual of Sea Level Variability in the Indonesian Seas using Satellite Altimetry. IOP Conference Series: Earth and Environmental Science, 731(1). https://doi.org/10.1088/1755-1315/731/1/012004

Hofmann-Wellenhof, B., Lichtenegger, H., & Wasle, E. (2007). GNSS – Global Navigation Satellite Systems GPS, GLONASS, Galileo, and more. Vienna: Springer Vienna.

Hsiao, S. C., Fu, H. S., Wu, H. L., Liang, T. Y., Chang, C. H., Chen, Y. M., Lin, L. Y., & Chen, W. B. (2024). Impact assessment of sea level rise-induced high tide flooding and socioeconomic losses in a highly vulnerable coastal region. Journal of Hydrology: Regional Studies, 55(August), 101921. https://doi.org/10.1016/j.ejrh.2024.101921

Khomsin, Mutiara Anjasmara, I., Guruh Pratomo, D., & Ristanto, W. (2019). Accuracy Analysis of GNSS (GPS, GLONASS and BEIDOU) Obsevation for Positioning. E3S Web of Conferences, 94, 0–6. https://doi.org/10.1051/e3sconf/20199401019

Khomsin, Pratomo, D. G., & Rohmawati, C. N. (2021). Analysis of accuracy comparison tidal global (FES2014, TPXO9) and regional (BIG Prediction) models to the existing tides in Surabaya and surrounding waters. IOP Conference Series: Earth and Environmental Science, 936(1). https://doi.org/10.1088/1755-1315/936/1/012028

Khomsin, Pratomo, D. G., Syariz, M. A., Hariyanto, I. H., & Harisa, H. C. (2024). Dense Neural Network for Classification of Seafloor Sediment using Backscatter Mosaic Feature. BIO Web of Conferences, 89. https://doi.org/10.1051/bioconf/20248907004

Kim, S.-K., Park, J., Wengrove, M. E., & Dickey, J. E. (2021). Feasibility Study of GNSS Interferometric Reflectometry (GNSS-IR) For Retrieving Significant Wave Height. 2021 IEEE Specialist Meeting on Reflectometry Using GNSS and Other Signals of Opportunity (GNSS+R), 69–72. https://doi.org/10.1109/GNSSR53802.2021.9617691

Larson, K. M. (2024). Gnssrefl: an open source software package in python for GNSS interferometric reflectometry applications. GPS Solutions, 28(4), 1–7. https://doi.org/10.1007/s10291-024-01694-8

Larson, K. M., Löfgren, J. S., & Haas, R. (2013). Coastal sea level measurements using a single geodetic GPS receiver. Advances in Space Research, 51(8), 1301–1310. https://doi.org/10.1016/j.asr.2012.04.017

Larson, K. M., & Williams, S. D. P. (2023). Water level measurements using reflected GNSS signals. The International Hydrographic Review, 29(2), 66–76. https://doi.org/10.58440/ihr-29-2-a30

Lei, J., Li, W., & Zhang, S. (2023). Improving Consistency of GNSS-IR Reflector Height Estimates between Different Frequencies Using Multichannel Singular Spectrum Analysis. Remote Sensing, 15(7). https://doi.org/10.3390/rs15071779

Li, Y., Yu, K., Jin, T., Chang, X., Wang, Q., & Li, J. (2021). Development of a GNSS-IR instrument based on low-cost positioning chips and its performance evaluation for estimating the reflector height. GPS Solutions, 25(4), 127. https://doi.org/10.1007/s10291-021-01163-6

Lombardi, M. A., Nelson, L. M., Novick, A. N., & Zhang, V. S. (2001). Time and Frequency Measurements Using the Global Positioning System. The International Journal of Metrology, 8(3), 26–33. Retrieved from http://tf.nist.gov/general/pdf/1424.pdf

Ma, P., Huang, C., Hou, J., Zhang, Y., Han, W., & Dou, P. (2023). Snow Depth Retrieval With Multiazimuth and Multisatellite Data Fusion of GNSS-IR Considering the Influence of Surface Fluctuation. IEEE Transactions on Geoscience and Remote Sensing, 61, 1–14. https://doi.org/10.1109/TGRS.2023.3323642

Mahmoodi, K., & Ghassemi, H. (2018). Outlier detection in ocean wave measurements by using unsupervised data mining methods. Polish Maritime Research, 25(1), 44–50. https://doi.org/10.2478/pomr-2018-0005

Orihan, M., Borisov, M., Marinković, G., & Petrović, M. V. (2019). the Influence of Ocean Tides To Determine the Earth’S Orientation Parameters. Archives for Technical Sciences, 2(21), 43–53. https://doi.org/10.7251/afts.2019.1121.043o

Padrón, N., & Vorobyov, S. (2025). A GNSS-IR Aided Multispectral Satellite Data Fusion for Meter-Level Wide-Area Volumetric Soil Moisture Estimation. ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 1–5. https://doi.org/10.1109/ICASSP49660.2025.10890009

Pan, H., Xu, T., & Wei, Z. (2023). A modified tidal harmonic analysis model for short-term water level observations. Ocean Modelling, 186, 102251. https://doi.org/10.1016/j.ocemod.2023.102251

Peng, D., Lin, Y. N., Lee, J.-C., Su, H.-H., & Hill, E. M. (2024). Multi-constellation GNSS interferometric reflectometry for tidal analysis: mitigations for K1 and K2 biases due to GPS geometrical errors. Journal of Geodesy, 98(1), 5. https://doi.org/10.1007/s00190-023-01812-3

Pestana, A. (2016). Technical Report : Reading RINEX 2 . 11 Observation Data Files António Pestana. Observation Data Files. https://doi.org/10.13140/RG.2.1.4888.4087

Pratomo, D. G., Khomsin, K., & Syaputra, K. (2019). Comparison of Sea Surface Variation Derived from Global Navigation Satellite System (GNSS) and Co-Tidal in Java Sea. E3S Web of Conferences, 94, 8–13. https://doi.org/10.1051/e3sconf/20199401007

Rajabi, M., Hoseini, M., Nahavandchi, H., Semmling, M., Ramatschi, M., Goli, M., Haas, R., & Wickert, J. (2022). Polarimetric GNSS-R Sea Level Monitoring Using I/Q Interference Patterns at Different Antenna Configurations and Carrier Frequencies. IEEE Transactions on Geoscience and Remote Sensing, 60(May). https://doi.org/10.1109/TGRS.2021.3123146

Roesler, C., & Larson, K. M. (2018). Software tools for GNSS interferometric reflectometry (GNSS-IR). GPS Solutions, 22(3), 80. https://doi.org/10.1007/s10291-018-0744-8

Roussel, N., Ramillien, G., Frappart, F., Darrozes, J., Gay, A., Biancale, R., Striebig, N., Hanquiez, V., Bertin, X., & Allain, D. (2015). Sea level monitoring and sea state estimate using a single geodetic receiver. Remote Sensing of Environment, 171, 261–277. https://doi.org/10.1016/j.rse.2015.10.011

Shekhar, S., Prakash, R., Pandey, D. K., & Vidyarthi, A. (2024). Vegetation-Specific Correction for Improved Soil Moisture Estimation Through Multipath Phase Analysis Using NavIC-IR. IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium, 3089–3092. https://doi.org/10.1109/IGARSS53475.2024.10642110

Soulat, F., Caparrini, M., Germain, O., Lopez-Dekker, P., Taani, M., & Ruffini, G. (2004). Sea state monitoring using coastal GNSS-R. Geophysical Research Letters, 31(21). https://doi.org/10.1029/2004GL020680

Wang, F., Yang, D., Li, J., Xing, J., & Zhang, G. (2024). Statistical Analysis of Reflected GNSS Signal Off Sea Surfaces From a Coastal Scenario. IEEE Transactions on Geoscience and Remote Sensing, 62, 1–15. https://doi.org/10.1109/TGRS.2024.3500014

Wang, H., Wei, N., Li, M., Han, S. C., Fang, R., & Zhao, Q. (2023). Estimation of GPS-observed ocean tide loading displacements with an improved harmonic analysis in the northwest European shelf. Journal of Geodesy, 97(12), 0–21. https://doi.org/10.1007/s00190-023-01796-0

Wang, X., Niu, Z., Chen, S., & He, X. (2022). A correction method of height variation error based on one SNR arc applied in GNSS–IR sea-level retrieval. Remote Sensing, 14(1). https://doi.org/10.3390/rs14010011

Wei, Z., Ren, C., Liang, X., Liang, Y., Yin, A., Liang, J., & Yue, W. (2023). Sea-Level Estimation from GNSS-IR under Loose Constraints Based on Local Mean Decomposition. Sensors, 23(14). https://doi.org/10.3390/s23146540

Wei, Z., Ren, C., Liang, Y., Liu, Y., Liang, J., Yin, A., Yue, W., Zhang, X., & Lin, X. (2024). Can the phase of SNR oscillations in GNSS-IR be used to estimate sea-level height? GPS Solutions, 28(3), 1–17. https://doi.org/10.1007/s10291-024-01663-1

Williams, S. D. P., Bell, P. S., McCann, D. L., Cooke, R., & Sams, C. (2020). Demonstrating the Potential of Low-Cost GPS Units for the Remote Measurement of Tides and Water Levels Using Interferometric Reflectometry. Journal of Atmospheric and Oceanic Technology, 37(10), 1925–1935. https://doi.org/10.1175/JTECH-D-20-0063.1

Yalçin, G. (2023). Modeling of Sea Level Changes With GNSS-IR Method and Comparative Analysis With Tide Gauge Data. Advances in Geomatics, 1(1), 32–47. https://doi.org/10.5281/zenodo.10202317

Yang, T., Wang, J., & Sun, Z. (2024). Can the Soil Salinity be Retrieved Using GNSS Interferometric Reflectometry Data? IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 17, 10612–10620. https://doi.org/10.1109/JSTARS.2024.3391321

Yuan, X., Hu, Y., Liu, W., & Wickert, J. (2024). GNSS-IR Snow Depth Retrieval Based on the PSO-NFP Method With Multi-GNSS Constellations. IEEE Transactions on Geoscience and Remote Sensing, 62, 1–10. https://doi.org/10.1109/TGRS.2024.3492495

Zhu, H., Gui, Y., Shen, Y., Wang, Q., & Zheng, W. (2024). Improving Water Level Retrieval Accuracy of GNSS-IR Based on Ionospheric Refraction Correction Optimization Method. IEEE Geoscience and Remote Sensing Letters, 21, 1–5. https://doi.org/10.1109/LGRS.2024.3451697

Author Biographies

Hairul Zulkifli, Climatology and Geophysics Agency

Author Origin : Indonesia

Danar Guruh Pratomo, Sepuluh Nopember Institute of Technology

Author Origin : Indonesia

Khomsin, Sepuluh Nopember Institute of Technology

Author Origin : Indonesia

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How to Cite

Zulkifli, H., Pratomo, D. G., & Khomsin. (2025). Application of GNSS Interferometric Reflectometry (GNSS-IR) for Monitoring Tidal Variations in Coastal Zones. Jurnal Penelitian Pendidikan IPA, 11(9), 258–267. https://doi.org/10.29303/jppipa.v11i9.12539