w x C y a x f x , 1 ABSTRACT In this paper, we consider chaotic communication schemes using nonlinear filtering techniques. Two different previously proposed Extended Kalman Filter based chaotic schemes are revisited and implemented using the Unscented Kalman Filter. Also, a recently proposed antipodal chaotic communication scheme is implemented with both the Extended Kalman Filter and the Unsc...

In order to improve the soil temperature profile predictions in land-surface models, an assimilation scheme using the extended Kalman filter is developed. This formulation is based on the discretized diffusion equation of heat transfer through the soil column. The scheme is designed to incorporate the knowledge of the uncertainties in both the model and the measurement. Model uncertainty is est...

In this paper, we consider chaotic communication using nonlinear filtering techniques. The main contribution of the paper is proposing a novel antipodal chaotic communication scheme, which is implemented with both the Extended Kalman Filter and the Unscented Kalman Filter. Two different previously proposed Extended Kalman Filter based chaotic schemes are also revisited and implemented using the...

In radar tracking target motion is best modeled in Cartesian coordinates. Its position is however measured in polar coordinates (range and azimuth). Tracking in Cartesian coordinates with noisy polar measurements requires either converting the measurements to a Cartesian frame of reference and then applying the linear Kalman lter to the converted measurement [1] or using the extended Kalman lte...

In this study, it is aimed to design a speed sensorless DTC system for induction motors (IMs). All the states required for DTC system in addition to the load torque are estimated using an Extended Kalman Filter (EKF). Simulation results demonstrate a good performance and robustness.

The focus of study is to review the FIM statistical behavior in each EKF update and determine its potential in providing sufficient information about Robotic Localization and Mapping problem with intermittent measurements. We provide theoretical analysis and prove that the FIM can successfully describe both upper and lower bounds for the state covariance matrix whenever measurement data is not ...

This paper presents the first progress made at FGAN/FHR-RWA towards the development of a robust autonomous method for the tracking of space objects with the Tracking and Imaging Radar (TIRA). For the acquisition phase an algorithm based on a Least-Squares Estimation of the state vector and f and g series will be presented and tested. For the tracking phase the suitability of the Extended Kalman...

In this paper, a hybrid model which combines Extended Kalman Filter (EKF) and Genetic Programming (GP) for forecasting of water demand in Tehran is developed. The initial goal of the current work is forecasting monthly water demand using GP for achieving an explicit optimum formula. In the proposed model, the EKF is applied to infer latent variables in order to make a forecasting based on GP re...

This paper provides a new fully-decentralized algorithm for Collaborative Localization based on the extended Kalman filter. The major challenge in decentralized collaborative localization is to track inter-robot dependencies – which is particularly difficult in situations where sustained synchronous communication between robots cannot be guaranteed. Current approaches suffer from the need for p...