Tsunami-wave parameter estimation using GNSS-based sea surface height measurement

Kegen Yu*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

25 Citations (Scopus)


This paper focuses on the estimation of tsunami-wave parameters (propagation direction, propagation speed, and wavelength) using the Global Navigation Satellite System (GNSS) reflectometry (GNSS-R)-based sea surface height (SSH) measurements. By exploiting multiple surface specular reflection tracks of GNSS signals as well as the geometry of wave propagation direction and the multiple tracks, concise mathematical expressions are derived to determine the propagation direction and speed and wavelength of a tsunami wave. Real tsunami-wave data measured by buoy sensors are employed to model GNSS-R-based SSH measurements by adding Gaussian measurement noise. The simulation results demonstrate that the proposed method can achieve a propagation direction estimation accuracy of about 4.4 ^{\circ} and 5.9 ^{\circ} when the SSH error standard deviations are 10 and 20 cm, respectively. The propagation speed estimation accuracies are about 12.7 and 17.7 m/s, respectively, under the same conditions when the speed ground truth is 200 m/s. The results also show that the wavelength estimation error can be as large as 100 km when the wavelength ground truth is about 400 km. Better filtering methods are needed to improve the wavelength estimation accuracy by mitigating the effect of the SSH estimation error particularly on the wave trailing edge of small negative magnitudes.

Original languageEnglish
Article number6936299
Pages (from-to)2603-2611
Number of pages9
JournalIEEE Transactions on Geoscience and Remote Sensing
Issue number5
Publication statusPublished - 1 May 2015
Externally publishedYes


  • Global Navigation Satellite System (GNSS) reflectometry
  • multiple specular reflection tracks
  • propagation direction and speed
  • tsunami-wave parameter estimation
  • wavelength


Dive into the research topics of 'Tsunami-wave parameter estimation using GNSS-based sea surface height measurement'. Together they form a unique fingerprint.

Cite this