This paper describes two methodologies for performing distributed particle filtering in a
sensor network. It considers the scenario in which a set of sensor nodes make multiple …

This paper addresses the problem of sensor management for a large network of agile
sensors. Sensor management, as defined here, is the process of dynamically retasking agile …

This paper presents a distributed particle filter over sensor networks. We propose two major
steps to make a particle filter to work in a distributed way. The first step is the estimation of …

We present particle filtering algorithms for tracking a single target using data from binary
sensors. The sensors transmit signals that identify them to a central unit if the target is in their …

Two novel distributed particle filters with Gaussian mixer approximation are proposed to
localize and track multiple moving targets in a wireless sensor network. The distributed …

Target tracking is investigated using particle filtering of data collected by distributed sensors.
In lieu of a fusion center, local measurements must be disseminated across the network for …

This paper investigates target tracking using a distributed particle filter over sensor networks.
Gaussian mixture model is adopted to approximate the posterior distribution of weighted …

The work reported in this paper investigates the performance of the Particle Filter (PF)
algorithm for tracking a moving object using a wireless sensor network (WSN). It is well …

Particle filters estimate the state of dynamical systems from sensor information. In many real
time applications of particle filters, however, sensor information arrives at a significantly …

In this paper, we introduce three novel distributed Kalman filtering (DKF) algorithms for
sensor networks. The first algorithm is a modification of a previous DKF algorithm presented …