An unscented Kalman filter (UKF) for matrix Lie groups is proposed where the time propagation of state formulated on algebra. This done with kinematic differential equation logarithm, inverse right Jacobian used. The sigma points can then be expressed as logarithms in vector form, and computation mean covariance resulting formulation to a large extent based form is, therefore, closer UKF system...

To develop an advanced battery estimation unit for electric vehicles application, the state-of-charge (SoC) estimation is proposed with an unscented Kalman filter (UKF) and realized with the RTOS lCOS-II platform. Kalman filters are broadly used to deploy various battery SoC estimators recently. Herein, an UKF algorithm has been employed to develop a systematic adaptive SoC estimation framework...

The electrical network measurements by measuring device Phasor Measurement Device (PMU) are usually sent to the control centers using data acquisition system and other communication protocols available. However, these measurements contain uncertainties due to the measurements and communication noise (errors), incomplete metering or unavailability of some of measurements. The overall aim of stat...

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 SINS, the inertial components are directly mounted on the carrier.The error can be divided into deterministic error and random drift error (dynamic error), in which, the formercan be compensated. In this case, the initial alignment of the pure static base can achieve a high accuracy. In the practical application, the dynamic error is directly reflected in the inertial device because of influ...

Over the last 20-30 years, the extended Kalman filter (EKF) has become the algorithm of choice in numerous nonlinear estimation and machine learning applications. These include estimating the state of a nonlinear dynamic system as well estimating parameters for nonlinear system identification (e.g., learning the weights of a neural network). The EKF applies the standard linear Kalman filter met...

An arithmetic of fast two-position initial alignment for Strapdown Inertial Navigation System (SINS) using Unscented Kalman Filter (UKF) is proposed in this paper to solve the initial alignment problems of SINS. Based on the analysis of initial alignment method of SINS, the nonlinear model for two-position attitude calculation is derived, and the two-position method is used to eliminate the con...

Vehicle motion trajectory prediction is the basis of vehicle collision early warning or conflict resolution. In order to improve accuracy prediction, a method based on “current” statistical (CS) model and cubature Kalman filter (CKF) proposed. This considers acceleration variation rules in actual process state equation, so that estimated value can be consistent with real range. condition overco...

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...