We present an underwater localization system for medium-sized Autonomous Underwater
Vehicles (AUVs) that leverages a broadband wireless acoustic communication system for …

We model the tracking of Bluetooth low-energy (BLE) transmitters as a three layer hidden
Markov model with joint state and parameter estimation. We are after a filtering distribution …

An adaptive meshfree approach is proposed to solve the nonlinear filtering problem based
on forward backward stochastic differential equations. The algorithm relies on the fact that …

In this paper, we present a novel high-degree cubature particle filter for nonlinear systems
with missing measurements to limit particle degradation. For the proposed particle filter, we …

As a special nonperiodic transient system, the electromagnetic launch system realizes the
conversion of ultrahigh power of energy in a few seconds, which is harmful when the system …

Abstract This paper develops Rao-Blackwellized particle filter with asynchronous
dependence between system noise and measurement noise. It is pointed out that this …

Particle filter is the most widely used Bayesian sequential state estimation method for
nonlinear dynamic systems. When importance sampling is adopted, it is still a challenge to …

This article presents a filter for state-space models based on Bellman's dynamic
programming principle applied to the mode estimator. The proposed Bellman filter (BF) …

Conventional resampling for particle filters suffers from discarding much potentially useful
information due to using less information of spatial distribution of sampling particles set. An …

Optimal filtering problem estimates an unknown underlying state variable St from associated
noisy observation data O t, and it has applications in a wide range of fields. Different …