Localization via Radio Frequency Identification (RFID) is frequently used in different applications nowadays. It has the advantage that next to its ostensible purpose of identifying objects via their unique IDs it can simultaneously be used for the localization of these objects. In this work it is shown how Received Signal Strength Indicator (RSSI) measurements at different antennae of a passiv...

BACKGROUND The emergence of the role of microRNAs (miRNAs) in exacerbating drug resistance of tumours is recently being highlighted as a crucial research field for future clinical management of drug resistant tumours. The purpose of this study was to identify dys-regulations in expression of individual and/or networks of miRNAs that may have direct effect on neuroblastoma (NB) drug resistance. ...

In this paper, an approach is proposed for relative state estimation for satellites in formation flying. To estimate the relative states of two satellites, the Kalman Filter algorithms (EKF, UKF) are adopted with the relative range and range rate between two satellites and attitude of a satellite as measurement variables. In case that the initial state and measurements errors are moderate, both...

Abstract: This paper presents an application of nonlinear filtering techniques for the tracking control design of tracked mobile robot under slip condition. The slip is represented only by the longitudinal wheels slip that is described by just an unknown parameter. The extended Kalman filter (EKF), the unscented Kalman filter (UKF) and the particle filter (PF) are used to estimate the states of...

This paper is motivated by the goal of a visual perception system for the RoboCup 2050 challenge to win against the human worldcup champion. Its contribution is to answer two questions on the subproblem of predicting the motion of a flying ball. First, if we could detect the ball in images, is that enough information to predict its motion precise enough? And second, how much do we lose by using...

In order to overcome the limitation of the traditional adaptive Unscented Kalman Filtering (UKF) algorithm in noise covariance estimation for statement and measurement, we propose a hybrid adaptive UKF algorithm based on combining Maximum a posteriori (MAP) criterion and Maximum likelihood (ML) criterion, in this paper. First, to prevent the actual noise covariance deviating from the true value...

Multi-sensor sonar tracking has many advantages, such as the potential to reduce the overall measurement uncertainty and the possibility to hide the receiver. However, the use of multi-target multi-sensor sonar tracking is challenging because of the complexity of the underwater environment, especially the low target detection probability and extremely large number of false alarms caused by reve...

STUKF (Strong tracking UKF) algorithm uses the time-varying fading factor to fade the past data and reduce the impact on current filter value, thus achieves the goal of adjusting the filter gain matrix in real time. But STUKF algorithm needs three UT for each filtering, and compared with the UKF filter, calculating amount of three UT increases seriously, and it is not conducive to application o...

An improved state estimation technique for bioprocess control applications is proposed where a hybrid version of the Unscented Kalman Filter (UKF) is employed. The underlying dynamic system model is formulated as a conventional system of ordinary differential equations based on the mass balances of the state variables biomass, substrate, and product, while the observation model, describing the ...

A novel adaptive unscented Kalman filter (AUKF) based estimation algorithm is proposed for a 3U Cubsat. This small satellite employs a three axis magnetometer and three MEMS gyroscopes as well as three magnetic torque rods and one reaction wheel on the pitch axis. Unlike the existing UKF, in this paper, an n+1 sigma set is used to estimate the nanosatellite attitude instead of 2n + 1 sigma poin...