Integration of Global Positioning System (GPS) and Inertial Navigation System (INS) integrated system involves nonlinear motion state and measurement models. However, the extended Kalman filter (EKF) is commonly used as the estimation filter, which might lead to solution divergence. This is usually encountered during GPS outages, when low-cost micro-electro-mechanical sensors (MEMS) inertial se...

Accurate estimation of the motion and shape of a moving object is a challenging task due to great variety of noises present from sources such as electronic components and the influence of the external environment, etc. To alleviate the noise, the filtering/estimation approach can be used to reduce it in streaming video to obtain better estimation accuracy in feature points on the moving objects...

This paper develops a Square Root Unscented Kalman Filter (SRUKF) for performing video-rate visual simultaneous localization and mapping (SLAM) using a single camera. The conventional UKF has been proposed previously for SLAM, improving the handling of non-linearities compared with the more widely-used Extended Kalman Filter. However, no account was taken of the comparative complexity of the al...

This paper presents a new hybrid methodology for learning Sugeno-type fuzzy models via subtractive clustering, Adaptive Boosting Regression (AdaBoostR) and Unscented Kalman Filter (UKF). The generated fuzzy models are used for modeling nonlinear benchmark processes. In the proposed procedure, first one fuzzy rule is generated by subtractive clustering algorithm from available data of a given no...

This paper describes the application of an unscented Kalman filter to a coal runof-mine bin. A dynamic model of the bin is derived using the principle of mass conservation. The dynamic model is nonlinear with unknown parameters that are identified using actual plant production data. The identified dynamic model is used by an unscented Kalman filter to update the states of the system to improve ...

The extended Kalman filter, which linearizes the relationship between security prices and state variables, is widely used in fixed income applications. We investigate if the unscented Kalman filter should be used to capture nonlinearities, and compare the performance of the Kalman filter to that of the particle filter. We analyze the cross section of swap rates, which are mildly nonlinear in th...

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...

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 ...

Accurate state of charge (SOC) estimation is great significance to promote the development new energy vehicles. And a battery model’s accuracy for SOC accuracy. To this end, method based on back propagation neural network-Ant Lion Optimizer (BPNN-ALO) and unscented Kalman filter (UKF) proposed. First, 2-RC model established BPNN used fit OCV-SOC corresponding relationship. Second, ALO are combi...

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...