Hatipoglu, Cansu BeselKayikci, Emine Tanir2025-03-232025-03-2320250039-62651752-2706https://doi.org/10.1080/00396265.2025.2455374https://hdl.handle.net/11486/5878Quality control is a crucial step in GNSS-IR data processing and is performed in this study using two methods: the peak-to-noise ratio and K-means clustering. Both quality control methods are applied to the SNR data at the MERS, TRBZ, and SNOP sites. K-means clustering shows better performance for the MERS GPS L1, Galileo L1, and SNOP GPS L2, while the peak-to-noise ratio shows better performance for the TRBZ GPS L1. The correlation coefficient between the GNSS-IR sea levels from the L1 signal and tide gauge is greater than 85%. These results demonstrate that K-means clustering is promising for quality control.eninfo:eu-repo/semantics/closedAccessSea levelGlobal navigation satellite system interferometric reflectometry (GNSS-IR)Signal-to-noise ratio (SNR)Quality controlK-means clusteringArticle10.1080/00396265.2025.24553742-s2.0-85216266068Q2WOS:001406756700001Q3