In this thesis, research for tsunami remote sensing using the Global Navigation
Satellite System-Reflectometry (GNSS-R) delay-Doppler maps (DDMs) is presented.
Firstly, a process for simulating GNSS-R DDMs of a tsunami-dominated sea sur-
face is described. In this method, the bistatic scattering Zavorotny-Voronovich (Z-V)
model, the sea surface mean square slope model of Cox and Munk, and the tsunami-
induced wind perturbation model are employed. The feasibility of the Cox and Munk
model under a tsunami scenario is examined by comparing the Cox and Munk model-
based scattering coefficient with the Jason-1 measurement. A good consistency be-
tween these two results is obtained with a correlation coefficient of 0.93. After con-
firming the applicability of the Cox and Munk model for a tsunami-dominated sea,
this work provides the simulations of the scattering coefficient distribution and the
corresponding DDMs of a fixed region of interest before and during the tsunami. Fur-
thermore, by subtracting the simulation results that are free of tsunami from those
with presence of tsunami, the tsunami-induced variations in scattering coefficients
and DDMs can be clearly observed.
Secondly, a scheme to detect tsunamis and estimate tsunami parameters from such
tsunami-dominant sea surface DDMs is developed. As a first step, a procedure to de-
termine tsunami-induced sea surface height anomalies (SSHAs) from DDMs is demon-
strated and a tsunami detection precept is proposed. Subsequently, the tsunami
parameters (wave amplitude, direction and speed of propagation, wavelength, and
the tsunami source location) are estimated based upon the detected tsunami-induced
SSHAs. In application, the sea surface scattering coefficients are unambiguously re-
trieved by employing the spatial integration approach (SIA) and the dual-antenna
technique. Next, the effective wind speed distribution can be restored from the scat-
tering coefficients. Assuming all DDMs are of a tsunami-dominated sea surface, the
tsunami-induced SSHAs can be derived with the knowledge of background wind speed
distribution. In addition, the SSHA distribution resulting from the tsunami-free DDM
(which is supposed to be zero) is considered as an error map introduced during the
overall retrieving stage and is utilized to mitigate such errors from influencing sub-
sequent SSHA results. In particular, a tsunami detection procedure is conducted to
judge the SSHAs to be truly tsunami-induced or not through a fitting process, which
makes it possible to decrease the false alarm. After this step, tsunami parameter
estimation is proceeded based upon the fitted results in the former tsunami detec-
tion procedure. Moreover, an additional method is proposed for estimating tsunami
propagation velocity and is believed to be more desirable in real-world scenarios.
The above-mentioned tsunami-dominated sea surface DDM simulation, tsunami
detection precept and parameter estimation have been tested with simulated data
based on the 2004 Sumatra-Andaman tsunami event
