Empirical Model for Fast Estimation of Decorrelation Induced by Ocean Waves in Interferometric Radar Altimeter

As a new type of ocean observation sensor, interferometric radar altimeter (IRA) will enable spaceborne observation of global mesoscale and sub-mesoscale ocean phenomena. IRA measurements can be contaminated by layover, generating random noise and leading to the decrease in the correlation coefficient of the master and slave images, mainly due to ocean waves. The influence of layover on the decorrelation between the master and slave images has not been adequately explained. We presented a theoretical model for the decorrelation induced by ocean waves in our previous study.In order to quantitatively analyze the variation of layover on the correlation coefficient more easily, the numerical simulated correlation coefficients for different incidence angles (1°–15°), different wind speeds (3 m/s–15 m/s), different wind directions (0°–180°) and different slant range resolution (0.2m–1.0m) have been fitted on the basis of the polynomial fitted algorithm. The fitted model is compared with simulation results and airborne experimental data and the agreement is good. The comparison indicates that the fitted model can be used to directly estimate the correlation coefficients for different sea state conditions. The quantitative analysis shows that the fitted model is useful for designing payloads and processing IRA measurements.