The univariate non-stationary growth model (UNGM) is widely used in the verification of nonlinear filters, and unscented Kalman filter (UKF) often as reference for comparative analysis when using this to evaluate performance. However, due strong nonlinearity UNGM change properties with different parameter settings, estimation misalignment problem reasons will occur UKF filtering. To solve these...

A convergence analysis of the modified unscented Kalman filter (UKF), used as an observer for a class nonlinear deterministic continuous time systems, is presented. Under certain conditions, extended (EKF) exponential non-linear i.e., dynamics estimation error exponentially stable. It shown that unlike EKF, UKF not converging observer. modification – proposed, which better candidate This paper ...

<span lang="EN-US">This paper presents the comparison between optimized unscented Kalman filter (UKF) and extended (EKF) for sensorless direct field orientation control induction motor (DFOCIM) drive. The high performance of UKF EKF depends on accurate selection state noise covariance matrices. For this goal, multi objective function genetic algorithm is used to find optimal values main o...

Acoustic travel-time tomography of the atmosphere is a nonlinear inverse problem which attempts to reconstruct temperature and wind velocity fields in the atmospheric surface layer using the dependence of sound speed on temperature and wind velocity fields along the propagation path. This paper presents a statistical-based acoustic travel-time tomography algorithm based on dual state-parameter ...

Some applications are constrained only to implement low cost receivers. In this case, designers are required to use less complex and non-expensive modulation techniques. Differential Quadrature Phase Shift Keying (DQPSK) and Gaussian Frequency Shift Keying (GFSK) can be non-coherently demodulated with simple algorithms. However, these types of demodulation are not robust and suffer from poor pe...

In this paper a new Adaptive Unscented Kalman Filter (AUKF) is proposed and applied for the state estimation of a LEO (Low earth Orbit) satellite planar model. The Unscented Kalman Filter (UKF) is preferred here because of its derivative free calculation process and superior performance in highly non linear systems. Further the choice of adaptive filter gives the opportunity to estimate the sta...

the radar tracking is one of the best leo satellite tracking methods. while the tracking filters which are mostly linear, and them are not able to have a precise estimation of the objects with nonlinear motion dynamic such as satellite, we should use nonlinear filters. in this paper , firstly, we deal with the problem of the leo satellites motion path modeling according to the satellite motion ...

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...

Performance of any tracking algorithm depends upon the model selected to capture the target dynamics. In real world applications, no apriori knowledge about the target motion is available. Moreover, it could be a maneuvering target. The proposed method is able to track maneuvering or nonmaneuvering multiple point targets with large motion ( pixels) using multiple filter bank in an IR image sequ...

One of the major challenges in human-robot interaction is how to enable the use of unrestricted hand motion as a tool for communication. The direct use of hand as an input tool enables the user to connect to systems more naturally, allowing them to become an integral part of our daily lives. A vision-based approach, using cameras to capture data, supports non-contact and unrestricted movement o...