An Analytical Method for Dynamic Wave-Related Errors of Interferometric SAR Ocean Altimetry under Multiple Sea States

Abstract

The spaceborne interferometric synthetic aperture radar (InSAR) is expected to measure the sea surface height (SSH) with high accuracy over a wide swath. Since centimeter-level accuracy is required to monitor the ocean sub-mesoscale dynamics, the high accuracy implies that the altimetric errors should be totally understood and strictly controlled. However, for the dynamic waves, they move randomly all the time, and this will lead to significant altimetric errors. This study proposes an analytical method for the dynamic wave-related errors of InSAR SSH measurement based on the wave spectrum and electromagnetic scattering model. Additionally, the mechanisms of the dynamic wave-related errors of InSAR altimetry are analyzed, and the detailed numerical model is derived. The proposed analytical method is validated with NASA’s Surface Water and Ocean Topography (SWOT) project error budget, and the Root-Mean-Square Errors (RMSEs) are in good agreement (0.2486 and 0.2470 cm on a 0.5 km2 grid, respectively). Instead of analysis for a typical project, the proposed method can be applied to different radar parameters under multiple sea states. The RMSEs of Ka-band under low sea state, moderate sea state, and high sea state are 0.2670, 1.3154, and 6.6361 cm, respectively. Moreover, the RMSEs of X-band and Ku-band are also simulated and presented. The experimental results demonstrate that the dynamic wave-related errors of InSAR altimetry are not sensitive to the frequencies but are sensitive to the sea states. The error compensation method is necessary for moderate and higher sea states for centimetric accuracy requirements. This can provide feasible suggestions on system design and error budget for the future interferometric wide-swath altimeter.

Ocean Wave Inversion Based on a Ku/Ka Dual-Band Airborne Interferometric Imaging Radar Altimeter

“…The significant factors affecting the inversion of the ocean waves are velocity bunching and the layover effect, sea surface morphology, and the payload performance. In this respect, Chen et al, (2021) [45] analyzed the altimetric accuracy of the X, Ku, and Ka bands under different sea states based on numerical simulations. The experimental results demonstrated that the dynamic wave-related errors of the InSAR altimetry were not sensitive to the frequencies but to the sea states.…”

Simulation research on the whole process of spaceborne XTI-SAR oceanic eddy detection

“…In high sea state 2, wind direction (180 degrees) is parallel to range direction, the SSH fluctuation caused by the background sea wave fluctuates greatly along the range direction. From the research [10] it can recognize that the random movement of the sea surface will cause the target point to shift in the azimuth and range directions in the SAR image, which is the main factor causing the height measurement error, while the range direction shift will have a great impact on the height measurement error. Therefore, when the radar look-directions are parallel to the wind direction, the height measurement error will increase significantly.…”

Overlapping-calibration of wide-swath altimeter baseline errors using two satellites formation flying design

“…However, multi-source errors of wide-swath altimetry, including random noise (RN), baseline roll and length errors, dry and wet troposphere delay, and sea state bias (Ren et al, 2020), will directly limit the precision of the retrieved SSH data. As a result, one of the most critical studies on the wide-swath altimetry mission is how to reduce the SSH errors (Chen et al, 2021), and for each error source, specific reduction methods should be developed according to the corresponding error model. On this basis, this study focuses on the research of SSH errors associated with baselines, involving height error associated with the both baseline roll (HEBR) and baseline length (HEBL).…”

“…Hence, this method inevitably generates the leakage of SSH signals, whereas the other three methods can only be applied to reduce local errors, and the residual errors are related with the variation of ocean topography during the time interval of two crossovers or overlap passes (Dibarboure and Ubelmann, 2014). Moreover, the ocean topography must be various (Chen et al, 2021). When the interval time of two passes is longer than three days, the difference between these two passes will influence the reduction results (Dibarboure et al, 2012;Dibarboure and Ubelmann, 2014).…”