The demand for seamless positioning has been significantly high. The methods of providing continuous indoor/outdoor positions seamlessly and the algorithms for smoothly transferring the estimation of positions from multiple positioning systems have attracted a great interest in the Location Based Services (LBS) research community. Most seamless positioning techniques are based on integrated met...

An accurate Linear Regression Kalman Filter (LRKF) for nonlinear systems called Smart Sampling Kalman Filter (S2KF) is introduced. In order to get a better understanding of this new filter, a general introduction to Nonlinear Kalman Filters based on statistical linearization and LRKFs is given. The S2KF is based on a new low-discrepancy Dirac mixture approximation of Gaussian densities. This ap...

This paper discusses the Instrument Pointing Frame (IPF) Kalman Filter, which is an algorithm developed for focal plane calibration of NASA’s Space Infrared Telescope Facility (SIRTF). The IPF Kalman filter is a high-order square-root iterated linearized Kalman filter which is parametrized specifically for calibrating the telescope focal plane and aligning the science instrument arrays with res...

Core to integrated navigation systems is the concept of fusing noisy observations from GPS, Inertial Measurement Units (IMU), and other available sensors. The current industry standard and most widely used algorithm for this purpose is the extended Kalman filter (EKF) [6]. The EKF combines the sensor measurements with predictions coming from a model of vehicle motion (either dynamic or kinemati...

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...

In this note, we illustrate the effect of nonlinear state propagation in the unscented Kalman filter (UKF). We consider a simple nonlinear system, consisting of a two-axis inertial measurement unit. Our intent is to show that the propagation of a set of sigma points through a nonlinear process model in the UKF can produce a counterintuitive (but correct) updated state estimate. We compare the r...

In this paper, adaptive sensor fusion INS/GNSS is proposed to solve specific problem of non linear time variant state space estimation with measurement outliers, different algorithms are used to solve this specific problem generally occurs in intentional and non-intentional interferences caused by other radio navigation sources, or by the GNSS receiver’s deterioration. Non linear approximation ...

In order to improve estimation accuracy of nonliear system with linear measurement model, simplified gauss hermite filter based on sparse grid gauss hermite quadrature (SGHF) is proposed. Comparing to conventional Gauss-Hermite filter (GHF) based on tensor product gauss quadrature rule, simplified SGHF not only maintains GHF’s advantage of precission controllable, high estimation accuracy, but ...