Tracking and data association
Alternatives to Monte-Carlo simulation evaluations of two multisensor fusion algorithms
Automatica (Journal of IFAC)
Ranking and optimization of target tracking algorithms
Ranking and optimization of target tracking algorithms
Tracking in a cluttered environment with probabilistic data association
Automatica (Journal of IFAC)
Hi-index | 22.14 |
In this paper, variance estimation and ranking methods are developed for stochastic processes modeled by Gaussian mixture distributions. It is shown that the variance estimate from a Gaussian mixture distribution has the same properties as the variance estimate from a single Gaussian distribution based on a reduced number of samples. Hence, well-known tools for variance estimation and ranking of single Gaussian distributions can be applied to Gaussian mixture distributions. As an application example, we present optimization of sensor processing order in the sequential multi-target multi-sensor joint probabilistic data association (MSJPDA) algorithm.