Study of Different Types of Gaussian Filters

Abstract

Filtering and estimation are two of the most pervasive tools of engineering. Whenever the state of a system must be estimated from noisy sensor information, some kind of state estimator is employed to fuse the data from different sensors together to produce an accurate estimate of the true system state. When the system dynamics and observation models are linear, the minimum mean squared error (MMSE) estimate may be computed using the Kalman filter. However, in most applications of interest the system dynamics and observation equations are nonlinear and suitable extensions to the Kalman Filter have been sought like the extended kalman filters ,the unscented ones and the extended complex kalman filters