Weak Tsunami Detection Using GNSS-R-Based Sea Surface Height Measurement

This paper investigates weak tsunami detection using noisy sea surface height (SSH) measurement data such as that recorded by a satellite-borne receiver and produced by the Global Navigation Satellite System (GNSS) reflectometry (GNSS-R) technique. By studying the patterns of many real tsunamis, a triangle function is proposed to model the shape of tsunami lead waves for theoretical studies. Very similar simulation results are produced when the modeled and real tsunami data are used separately, indicating good modeling accuracy. A bin averaging (BA) technique is proposed for detecting a tsunami, and a hypothesis testing method is developed to decide whether a tsunami is present by examining the BA outputs against a predefined threshold. Mathematical formulas are derived for the probability of detection (PD) and the probability of false alarm (PFA), which can be employed as a guideline in parameter selection and performance evaluation. Simulation results using both modeled and real tsunami data demonstrate that, given a PFA of 10%, the PD can be around 60% when the wave height is 45 cm, and the SSH measurement error standard deviation (STD) is 76 cm. The results also show that, when a suitable bin length is selected, a two-stage hypothesis testing scheme and a one stage one produce very similar results. Based on the methods developed here and elsewhere, the GNSS-R technique has the potential for future tsunami detection.