Kalman filter is a well known adaptive filtering Algorithm, widely used for target tracking applications. When the system model and measurements are non linear, variation of Kalman filter like extended Kalman filter (EKF) and Unscented Kalman filters (UKF) are used. For obtaining reliable estimate of the target state, filter has to be tuned before the operation (off line).Tuning an UKF is the p...

The unscented Kalman filter (UKF) is formulated for the continuous-discrete state space model. The exact moment equations are solved approximately by using the unscented transform (UT) and the measurement update is obtained by computing the normal correlation, again using the UT. In contrast to the usual treatment, the system and measurement noise sequences are included from the start and are n...

In a network robot system, a robot and a sensor network are integrated smoothly to develop their advantages and benefit from each other. Robot localization, sensor network calibration and environment mapping are three coupled issues to be solved once network robot system is introduced into a service environment. In this article, the problem of simultaneous localization, calibration and mapping ...

In this article, we propose a new particle filtering scheme, called a switching particle filter, which allows robust and accurate visual tracking under typical circumstances of real-time visual tracking. This scheme switches two complementary sampling algorithms, Condensation and Auxiliary Particle Filter, in an on-line fashion based on the confidence of the filtered state of the visual target....

Accurate prediction of the remaining useful life of a faulty component is important to the health management of the system. It gives operators information about when the component should be replaced. This paper studied the remaining useful life prediction of the lithium-ion batteries. Some work has been done to solve this problem, but it still remains challengeable. Particle filter (PF) is a re...

In this research, a non-infrastructure-based and low-cost indoor navigation method is proposed through the integration of smartphone built-in microelectromechanical systems (MEMS) sensors and indoor map information using an auxiliary particle filter (APF). A cascade structure Kalman particle filter algorithm is designed to reduce the computational burden and improve the estimation speed of the ...

This paper explores and compares the nature of the non-linear filtering techniques on mobile robot pose estimation. Three non-linear filters are implemented including the extended Kalman filter (EKF), the unscented Kalman filter (UKF) and the particle filter (PF). The criteria of comparison is the magnitude of the error of pose estimation, the computational time, and the robustness of each filt...

Rapidly increasing growth and demand in CNS/ATM, the advanced scheme for air traffic management, ADS-B system which is based on digital communication is being implemented in the field of surveillance. ADS-B concept appears to be an economically viable solution to obtain accurate aircraft position information. ADS-B system has better performance than the traditional radar and ADS-B system replac...