In light of the intuition that a better symmetrical structure can further increase the numerical accuracy, the paper by Fan and Zeng 2009 developed a new sigma point construction strategy for the unscented Kalman filter UKF , namely, geometric simplex sigma points GSSP . This comment presents a different perspective from the standpoint of the numerical integration. In this respect, the GSSP con...

Sigma-Point Kalman Filters (SPKFs) are popular estimation techniques for high nonlinear system applications. The benefits of using SPKFs include (but not limited to) the following: the easiness of linearizing the nonlinear matrices statistically without the need to use the Jacobian matrices, the ability to handle more uncertainties than the Extended Kalman Filter (EKF), the ability to handle di...

An accurate Linear Regression Kalman Filter (LRKF) for nonlinear systems called Smart Sampling Kalman Filter (S2KF) is introduced. It is based on a new low-discrepancy Dirac Mixture approximation of Gaussian densities. The approximation comprises an arbitrary number of optimally and deterministically placed samples in the entire state space, so that the filter resolution can be adapted to eithe...

In this paper, after defining pure proportional navigation guidance in the 3-dimensional state from a new point of view, range estimation for passive homing missiles isexplained. Modeling has been performed by using line of sight coordinates with a particulardefinition. To obtain convergent estimates of those state variables involved particularly inrange channel and unavailable from IR trackers...

Micro electromechanical sensors (MEMS) play a vital role along with global positioning devices in navigation of autonomous vehicles .These sensors are low cost ,easily available but depict colored noises and unpredictable discontinuities .Conventional filters like Kalman filters and Sigma point filters are not able to cope with nonwhite noises. This research has utilized H∞ filter in nonlinear ...

A 12-state dynamical model of a quadcopter is detailed. A vision-based measurement model is implemented for full state estimation of the quadcopter, with traditional translation and rotation measurement models used for comparison. An Unscented Kalman Filter using van der Merwe sigma point weights is implemented, and analysis of the vision-based estimator is conducted under varying measurement i...

The paper describes integration of Inertial Navigation System (INS) and Global Positioning System (GPS) navigation systems using new approaches for navigation information processing based on efficient SigmaPoint Kalman filtering and Particle filtering. The paper points out the inherent shortcomings in using the linearization techniques in standard Kalman filters (like Linearized Kalman filter o...

A tiny absolute orientation estimating device equipped with a network function has been developed using accelerometers and magnetometers to estimate gravity and the geomagnetic field, respectively. Because accelerometers measure motion other than gravity, a method has been proposed to eliminate the effect of motion. An estimation method is proposed that excludes the effect of magnetic disturban...

the error of inertial navigation systems increase versus time, therefore for achieving higher accuracy specially in long time navigations we have to use an aiding system. global positioning system is the best aiding system in this case. in this paper we first simulate a gps and ins; then simulate tightly integration and finally review adaptation method of kalman filtering a fuzzy adaptive kalma...

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...