Optimal and suboptimal state estimation for linear systems with additive cauchy noises

Only few estimation methods can converge in the presence of impulsive measurement and process noises without the use of augmented heuristic schemes. To understand the numerical behavior of these schemes, the performance of the optimal Idan/Speyer Cauchy Estimator (ISCE) is compared with those of the particle filter (PF) and Gaussian sum filter (GSF) while allowing similar computation times for the different estimators. In addition, the number of particles at each step for the PF and the number of Gaussian components kept at each step for the GSF are increased and their performance relative to the ISCE is numerically studied for a scalar and a two-state dynamic system.