A nonlinear filter is developed by representing the state probability density function by a
finite sum of Gaussian density kernels whose mean and covariance are propagated from …

This paper introduces a novel method for the automatic detection and handling of
nonlinearities in a generic transformation. A nonlinearity index that exploits second-order …

There are several techniques implemented, in an underwater target tracking environment,
for the nonlinear dynamic systems in Gaussian and non-Gaussian environments. It is …

This paper presents an adaptive splitting and merging scheme for dynamic selection of
Gaussian kernels in a Gaussian mixture model. The Gaussian kernel in the Gaussian …

ORBIT determination, ground tracking, as well many other aerospace and nonaerospace
applications require very accurate estimates of system states paired with accurate …

When physical sensors are involved, such as image sensors, the uncertainty over the input
data is often a major component of the output uncertainty of machine learning models. In this …

In underwater surveillance, three-dimensional target tracking is a challenging task. The
angles-only measurements (ie, bearing and elevation) obtained by hull mounted sensors …

The paper deals with state estimation problem of nonlinear non-Gaussian discrete dynamic
systems for improvement of accuracy and consistency. An efficient new algorithm called the …

The aim of this paper is to evaluate the performance of different filtering algorithms in the
presence of non-Gaussian noise environment for tracking underwater targets, using Doppler …

A multifidelity method for the nonlinear propagation of uncertainties in the presence of
stochastic accelerations is presented. The proposed algorithm treats the uncertainty …