A hybrid non-linear filter for an unmanned aerial vehicle (UAV) dynamics

Abstract

In this paper, we derive and apply a hybrid nonlinear filter for the state estimation of an unmanned aerial vehicle dynamics from discrete-time noisy observables. An UAV dynamics can be formalized as a differential system from a formal stochastic perspective. An UAV dynamics is formalized as a non-linear dynamics with process noise coupled with linear discrete range measurement, the measurement is masked with the measurement noise. Then, we wish to compute the filtered estimates of the UAV stochastic differential equation from given discrete noisy observations using a hybrid non-linear filter. The filter efficacy is adjudged by utilizing numerical experimentations accounting for two sets of data. Note that the process noise is state-independent the Ito and Stratonovich differentials coincide for the UAV stochastic system.