The goal of this study is to compare the performances of the ensemble Kalman filter and a reduced-rank extended Kalman filter when applied to different dynamic regimes. Data assimilation experiments are performed using an eddy-resolving quasi-geostrophic model of the winddriven ocean circulation. By changing eddy viscosity, this model exhibits two qualitatively distinct behaviors: strongly chao...

The purpose of this paper is to attitude estimation of Nano-satellite which requires navigation sensors data to less cost function and effection movement of Nano-satellite focus of the research is to using data of navigation sensors and methods to achieve the requirement of the attitude estimation. in this paper the following attitude estimation of the according to direction of sun of the Nano-...

The Kalman filter formula, given by the linear recursive algorithm, is usually used for estimation of the time-varying parameter model. The filtering formula, introduced by Kalman (1960) and Kalman and Bucy (1961), requires the initial state variable. The obtained state estimates are influenced by the initial value when the initial variance is not too large. To avoid the choice of the initial s...

In this article we consider the linear filtering problem in continuous-time. We develop and apply multilevel Monte Carlo (MLMC) strategies for ensemble Kalman-Bucy filters (EnKBFs). These can be viewed as approximations of conditional McKean-Vlasov-type diffusion processes. They are also interpreted continuous-time analogue \textit{ensemble Kalman filter}, which has proven to successful due its...

the error of inertial navigation systems increase versus time, therefore for achieving higher accuracy specially in long time navigations we have to use an aiding system. global positioning system is the best aiding system in this case. in this paper we first simulate a gps and ins; then simulate tightly integration and finally review adaptation method of kalman filtering a fuzzy adaptive kalma...

An industrial robot today uses measurements of its joint positions and models of its kinematics and dynamics to estimate and control its end-effector position. Substantially better end-effector position estimation and control performance would be obtainable if direct measurements of its end-effector position were also used. The subject of this paper is extended Kalman filtering for precise esti...

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...