A new approach for robust Hinfty filtering for a class of Lipschitz nonlinear systems with time-varying uncertainties both in the linear and nonlinear parts of the system is proposed in an LMI framework. The admissible Lipschitz constant of the syste
m and the disturbance attenuation level are maximized simultaneously through convex multiobjective optimization. The resulting Hinfty filter guarantees asymptotic stability of the estimation error dynamics with exponential convergence and is robust against nonlinear additive uncertainty and time-varying parametric uncertainties. Explicit bounds on the nonlinear uncertainty are derived based on norm-wise and element-wise robustness analysis.
The application of Synthetic Aperture Radar (SAR) techniques to classical radar altimetry offers the potential for greatly improved Earth surface mapping. This paper provides an overview of the progress of SAMOSA, Development of SAR Altimetry Studies
and Applications over Ocean, Coastal zones and Inland waters, an on-going ESA-funded project. The main objective of SAMOSA is to better quantify the improvement of SAR altimetry over conventional altimetry on water surfaces. More specifically, one of the tasks focuses on the reduction of SAR mode data to pulse-limited altimeter data, and a theoretical modelling to characterize the expected gain between high Pulse Repetition Frequency (PRF) reduced SAR mode data and low PRF classical Low-Resolution Mode (LRM) data. To this end, theoretical modelling using the Cramer-Rao bound (CRB) will be used and the results will be compared to previous theoretical estimates [7], using an analysis akin to that in [8].
