The continue-time unscented Kalman filter (UKF) is developed to estimate the state of a jet transport aircraft. The UKF is based on the nonlinear longitudinal aircraft equations of motion, and it is designed to provide estimates of horizontal and vertical atmospheric wind inputs. The optimal state and disturbance estimates are incorporated in feedback control laws based on the slowand fast-time...

The extended Kalman filter (EKF) and unscented Kalman filter (UKF) for nonlinear state estimation with both additive and nonadditive noise structures are presented and compared. Three different Global Positioning System (GPS)/inertial navigation system (INS) sensor fusion formulations for attitude estimation are used as case studies for the nonlinear state estimation problem. A diverse set of a...

The Unscented Kalman Filter (UKF) was applied to state and parameter estimation of a one degree of freedom robot link with an elastic, cable-driven transmission. Only motor encoder and command torque data was used as input to the filter. The UKF was used offline for joint state and model-parameter estimation, and online for state estimation. This paper presents an analysis of the robustness of ...

This paper proposes a method for mobile robot localization in a partially unknown indoor environment. The method fuses two types of range measurements: the range from the robot to the beacons measured by ultrasonic sensors and the range from the robot to the walls surrounding the robot measured by a laser range finder (LRF). For the fusion, the unscented Kalman filter (UKF) is utilized. Because...

Diffusion MRI tractography is increasingly used in pre-operative neurosurgical planning to visualize critical fiber tracts. However, a major challenge for conventional tractography, especially in patients with brain tumors, is tracing fiber tracts that are affected by vasogenic edema, which increases water content in the tissue and lowers diffusion anisotropy. One strategy for improving fiber t...

This paper presents sensor data fusion using Unscented Kalman Filter (UKF) to implement high performance vestibulo-ocular reflex (VOR) based vision tracking system for mobile robots. Information from various sensors is required to be integrated using an efficient sensor fusion algorithm to achieve a continuous and robust vision tracking system. We use data from low cost accelerometer, gyroscope...

BACKGROUND Diffusion imaging tractography is increasingly used to trace critical fiber tracts in brain tumor patients to reduce the risk of post-operative neurological deficit. However, the effects of peritumoral edema pose a challenge to conventional tractography using the standard diffusion tensor model. The aim of this study was to present a novel technique using a two-tensor unscented Kalma...

Target tracking using bistatic bearings-only measurements has obtained distinct interest recently. It is a nonlinear problem that traditional Kalman filter (KF) can not be applied directly. In this paper, the triangular ranging formula has been derived first for bistatic bearings-only tracking. The ranging error is then proved to be Gaussian noises, which enable the traditional KF applicable. T...

To ensure safe and reliable battery operations, an accurate battery state of charge (SOC) estimation is critical for the battery systems used in electric vehicles and hybrid electric vehicles because of the arduous operation conditions. This paper presents a SOC estimator designed based on the unscented Kalman filter (UKF), which is very popular in the state estimation in non-linear systems. Th...

Accurate position and velocity estimation of a re-entry vehicle is essential for realizing its deviation from the desired descent trajectory and providing necessary guidance command in real-time. Generally the Extended Kalman Filter (EKF) is utilized for position and velocity estimation of a space vehicle. However, in the EKF the error covariance is predicted by linearizing the non-linear dynam...