A typical way to update map is to compare recent satellite images with existing map data, detect new roads and add them as cartographic entities to the road layer. At present image processing and pattern recognition are not robust enough to automate the image interpretation system feasible. For this reason we have to develop an image interpretation system that rely on human guidance. More impor...

In this paper, phasor measurement unit (PMU) data-based synchronous generator model identification is carried out using unscented Kalman filter (UKF). The identification not only gives the model of a synchronous generator’s swing dynamics, but also gives its turbine-governor model along with the primary and secondary frequency control block models. PMU measurements of active power and voltage m...

Based on the Unscented Kalman Filter (UKF), the nonlinear filter is presented for parameter estimation in linear system with correlated noise where the unknown parameters are estimated as a part of an enlarged state vector. To avoid the computational burden in determining the state estimates when only the parameter estimates are required, a new form of UKF, where the state consists only of the ...

This paper presents the novel Rao-Blackwellised particle filter (RBPF) for mobile robot simultaneous localization and mapping (SLAM) using monocular vision. The particle filter is combined with unscented Kalman filter (UKF) to extending the path posterior by sampling new poses that integrate the current observation which drastically reduces the uncertainty about the robot pose. The landmark pos...

We investigate the problem of tracking a moving source in shallow ocean in a Bayesian framework, using acoustic field measurements which are more informative than the commonly employed bearings-only or time-delay measurements. The acoustic field measurement model is described and compared with the bearings-only measurement model. A general approach to Bayesian filtering based on the Gaussian ap...

This work proposes a novel application of existing powerful nonlinear filters, such as the standard Extended Kalman Filter (EKF), some of its variants and the standard Unscented Kalman Filter (UKF), to the estimation of a continuous spatio-temporal field that is spread over a wide area, and hence represented by a large number of parameters when parameterized. We couple these filters with the po...

In-motion alignment of Strapdown Inertial Navigation Systems (SINS) without any geodetic-frame observations is one of the toughest challenges for Autonomous Underwater Vehicles (AUV). This paper presents a novel scheme for Doppler Velocity Log (DVL) aided SINS alignment using Unscented Kalman Filter (UKF) which allows large initial misalignments. With the proposed mechanism, a nonlinear SINS er...

The global positioning system (GPS) with accurate positioning and timing properties has become integral part of all applications around the world. Radio frequency interference can significantly decrease the performance of GPS receivers or even completely prohibit the acquisition or tracking of satellites. The approaches of system performances that can be further enhanced by preprocessing to rej...

Satellites provide various services essential to the modern life of human being. For example, satellite images are used for many applications such as reconnaissance, geographic information system, etc. Therefore, design and operation requirements of the satellite system have become more severe, and also the system reliability during the operation is required. Satellite attitude control systems ...

This paper describes an estimator incorporating the Unscented Kalman Filter (UKF) technique and multibody system dynamics, to determine state of flexible applications. The dynamic equation mechanism is formed using a set non-linear equations as functions reference modal coordinates. Since both coordinates have no physical meaning, their information not able be obtained directly from sensors. Th...