Stochastic control of light UAV at landing with the aid of bearing-only observations

Abstract

This work considers the tracking of the UAV (unmanned aviation vehicle) at landing on unprepared field. Despite the advantages in UAV guidance the autonomous landing remains to be one of most serious problems. The principal difficulties are the absence of the precise UAV position measurements with respect to the landing field and the action of external atmospheric perturbations (turbulence and wind). So the control problem for UAV landing is the nonlinear stochastic one with incomplete information. The aim of the article is the development of stochastic control algorithms based on pseudomeasurement Kalman filter in the problem of the UAV autonomous landing with the aid of ground-based optical/radio radars in the case of strong wind and large initial error of the UAV entrance into the area covered by radars. The novelty of the article is the joint control-observation algorithm based on unbiased pseudomeasurement Kalman filter which provides the quadratic characteristics of the estimation errors. The later property is highly important for the UAV control based on the data fusion from INS (inertial navigation system) and the bearing observations obtained from external terrain based locators. The principal difficulty in the UAV landing control is the absence of the direct control tools at the terrain end, so the possible control can be based on the angular-range data obtained by terrain locators which must be transmitted from terrain location station to the UAV control unit. Thus the stochastic approach looks very effective in this challenging problem of the UAV landing.