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Local-polynomial-approximation-based phase unwrapping using state space analysis
Related publications (38)
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San Diego2023Data-Driven Unknown-Input Observers and State Estimation
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Unknown-input observers (UIOs) allow for estimation of the states of an LTI system without knowledge of all inputs. In this letter, we provide a novel data-driven UIO based on behavioral system theory and the result known as Fundamental Lemma proposed by J ...
2022Simultaneous unwrapping and low pass filtering of continuous phase maps based on autoregressive phase model and wrapped Kalman filtering
Pramod Rastogi, Rishikesh Dilip Kulkarni
We propose a simultaneous noise filtering and phase unwrapping algorithm. Spatial evolution of phase is modeled as an autoregressive Gaussian Markov random field. Accordingly, phase value at a pixel is related to phase values at surrounding pixels in a pro ...
2020Multiple ergodic averages along functions from a Hardy field: convergence, recurrence and combinatorial applications
We obtain new results pertaining to convergence and recurrence of multiple ergodic averages along functions from a Hardy field. Among other things, we confirm some of the conjectures posed by Frantzikinakis in [Fra10; Fra16] and obtain combinatorial applic ...
2020Measurement of Displacement and Its Derivatives from a Phase Fringe Pattern
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Noting the fact that the phase and phase derivatives carry the information on the mechanical deformation in optical interferometric measurements techniques, we propose a noise robust fringe analysis technique for the simultaneous estimation of unwrapped ph ...
SPRINGER INTERNATIONAL PUBLISHING AG2019MATHICSE Technical Report : Efficient state/Parameter estimation in nonlinear unsteady PDEs by reduced basis ensemble Kalman filter
Alfio Quarteroni, Andrea Manzoni, Stefano Pagani
The ensemble Kalman filter is a computationally efficient technique to solve state and/or parameter estimation problems in the framework of statistical inversion when relying on a Bayesian paradigm. Unfortunately its cost may become moderately large for sy ...
MATHICSE2019Two-step phase demodulation algorithm based on quadratic phase parameter estimation using state space analysis
Pramod Rastogi, Rishikesh Dilip Kulkarni
We propose a noise robust two-step phase shifting algorithm for the evaluation of random and unknown phase step. In this algorithm, the phase within a small size two-dimensional window around a user selected pixel in an interferogram is approximated as a q ...
2018Distributed State Estimation and Cooperative Path-Following Under Communication Constraints
Francisco Fernandes Castro Rego
The main topics of this thesis are distributed estimation and cooperative path-following in the presence of communication constraints, with applications to autonomous marine vehicles. To this end, we study algorithms that take explicitly into account the c ...
EPFL2018Perception-aware Receding Horizon Navigation for MAVs
To reach a given destination safely and accurately, a micro aerial vehicle needs to be able to avoid obstacles and minimize its state estimation uncertainty at the same time. To achieve this goal, we propose a perception-aware receding horizon approach. In ...
2018MATHICSE Technical Report : Multilevel ensemble Kalman filtering for spatio-temporal processes
Fabio Nobile, Hakon Andreas Hoel
This work concerns state-space models, in which the state-space is an infinite-dimensional spatial field, and the evolution is in continuous time, hence requiring approximation in space and time. The multilevel Monte Carlo (MLMC) sampling strategy is lever ...
MATHICSE2017