Scale Estimators in Target Mapping from an Aerial Vehicle

Abstract This paper describes the use of scale estimators in field trials for mapping ground targets by an aerial vehicle with onboard sensing. Targets are assumed to be static and of a known shape. The vehicle is a lightweight, tethered, airship with onboard global positioning system, magnetometer, 3-axis accelerometer and gyro sensors, and a camera. The dynamics, trajectory, and sensing noise characteristics, are assumed a priori unknown. The paper focus on the use of scale estimators to minimize the influence of the outlier measurements in the mean and covariance of the target positions observed as the vehicle moves. The results obtained show an interesting performance, better than that obtained with common maximum likelihood mean and covariance estimators, namely a smaller uncertainty is achieved.

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