most citedMultivariable Feedback Particle Filter

22 citations · 24 across the 4 of their papers we have counts for

collaborators

5 papers

math.PR2014

Probabilistic Data Association-Feedback Particle Filter for Multiple Target Tracking Applications

Tao Yang, Prashant G. Mehta

This paper is concerned with the problem of tracking single or multiple targets with multiple non-target specific observations (measurements). For such filtering problems with data…

math.NA2013

Interacting Multiple Model-Feedback Particle Filter for Stochastic Hybrid Systems

Tao Yang, Henk A. P. Blom, Prashant G. Mehta

In this paper, a novel feedback control-based particle filter algorithm for the continuous-time stochastic hybrid system estimation problem is presented. This particle filter is re…

math.NA2013★ 1 cited

Joint Probabilistic Data Association-Feedback Particle Filter for Multiple Target Tracking Applications

Tao Yang, Geng Huang, Prashant G. Mehta

This paper introduces a novel feedback-control based particle filter for the solution of the filtering problem with data association uncertainty. The particle filter is referred to…

math.NA2013★ 22 cited

Multivariable Feedback Particle Filter

Tao Yang, Richard S. Laugesen, Prashant G. Mehta +1

In recent work it is shown that importance sampling can be avoided in the particle filter through an innovation structure inspired by traditional nonlinear filtering combined with…

math.NA2013★ 1 cited

Feedback Particle Filter

Tao Yang, Prashant G. Mehta, Sean P. Meyn

A new formulation of the particle filter for nonlinear filtering is presented, based on concepts from optimal control, and from the mean-field game theory. The optimal control is c…