The paper proposes a two-stage Kalman filter combining a robust and optimal algorithm for state and disturbance estimation. A practical case coming from automotive application is studied in detail to show the effectiveness of the proposed technique.

In this paper we address the problem of fault resilient estimation for large-scale systems, where the measurements are possibly corrupted due to faults of low-cost sensors. As a toy application, we consider the problem of localization in Sensor Networks (SN). We propose a distributed solution based on a recently developed generalized descent algorithm. To cope with real-world applications, the ...

We present a path independent (global) algorithm for phase unwrapping based on the minimisation of a robust cost function. The algorithm incorporates an outlier rejection mechanism making it robust to large inconsistencies and discontinuities. The proposal consists on an iterative incremental scheme that unwraps a sub–estimation of the residual phase at each iteration. The sub–estimation degree...