In this book, the extended Kalman filter (EKF) has been used as the standard technique for performing recursive nonlinear estimation. The EKF algorithm, however, provides only an approximation to optimal nonlinear estimation. In this chapter, we point out the underlying assumptions and flaws in the EKF, and present an alternative filter with performance superior to that of the EKF. This algorit...

Report [1] compares the Extended Kalman Filter [2, 3, 4], the Iterated Extended Kalman Filter, IEKF, [2, 3, 4] and the Linear Regression Kalman Filter [5] (e.g. the Unscented Kalman Filter, UKF, [6, 7, 8]) on (i) consistency and (ii) information content of their results (estimates and covariance matrices). The nonlinear filter proposed by Bellaire et al. in [9] is not discussed in report [1]. T...

The problem of tracking a vessel modelled at a distance by an equivalent magnetic dipole is investigated. Tracking a magnetic dipole from magnetic field measurements is a complex non-linear problem. The determination of target position, velocity and magnetic moment is formulated as an optimal stochastic estimation problem, which could be solved using the non-linear Kalman filtering methods. The...

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...

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...

This paper investigates the application, design and implementation of unscented Kalman filter observer using the various scaling parameters for the sensorless speed control of a permanent magnet synchronous motor. The principles of unscented transformation and unscented Kalman filter are examined and their applications are explained. Typically the mapping transformation process is divided into ...

The paper reports about the design of an object tracker which utilizes a family of unscented Kalman filters, one for each tracked object. This is a more efficient design than having one unscented Kalman filter for the family of all moving objects. The performance of the designed and implemented filter is shown by using simulated movements, and also for object movements in 2D an 3D space.

One of the most important problems when designing controller is how to deal with all kinds of uncertainties, which, along with the high nonlinearities of most real systems, makes it difficult to guarantee the desired closed loop performance. Recently, nonlinear Kalman-class filter has been extensively researched and several well-known algorithms, including Extended Kalman Filter (EKF), Unscente...

SLAM (Simultaneous Localization and Mapping) is a fundamental problem when an autonomous mobile robot explores an unknown environment by constructing/updating the environment map and localizing itself in this built map. The all-important problem of SLAM is revisited in this paper and a solution based on Adaptive Unscented Kalman Filter (AUKF) is presented. We will explain the detailed algorithm...