The recently published optimal Cauchy estimator poses practical implementation challenges due to its time-growing complexity. Alternatively, addressing impulsive measurement and process noises, while using common estimation approaches, requires heuristic schemes. Approximate methods, such as particle and Gaussian-sum filters, were suggested to tackle the estimation problem in a heavy-tailed-noise environment when constraining the computational load. In this paper, the performances of a particle filter and a Gaussian-sum filter, designed for a linear system with specified Cauchy-noise parameters, are compared numerically to a Cauchy filter-based approximation showing the advantages of the latter.
Approximate Estimators for Linear Systems with Additive Cauchy Noises
Journal of Guidance, Control, and Dynamics ; 40 , 11 ; 2820-2827
01.11.2017
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
Optimal and Suboptimal State Estimation for Linear Systems with Additive Cauchy Noises
British Library Conference Proceedings | 2016
|A Sliding Mode Stochastic Controller for Scalar Linear Systems with Additive Cauchy Noises
British Library Conference Proceedings | 2018
|Smoothing of Linear Scalar Systems with Cauchy Distributed Noises
British Library Conference Proceedings | 2019
|Model Predictive Control for Scalar Linear Systems with Cauchy Noises
British Library Conference Proceedings | 2011
|