Strapdown Celestial Attitude Estimation from Long Exposure Images for UAV Navigation

Abstract

Strapdown celestial imaging sensors provide a compact, lightweight alternative to their gimbaled counterparts. Strapdown imaging systems typically require a wider field of view, and consequently longer exposure intervals, leading to significant motion blur. The motion blur for a constellation of stars results in a constellation of trails on the image plane. We present a method that extracts the path of these star trails, and uses a linearized weighted least squares approach to correct noisy inertial attitude measurements. We demonstrate the validity of this method through its application to synthetically generated images, and subsequently observe its relative performance by using real images. The findings of this study indicate that the motion blur present in strapdown celestial imagery yields an a posteriori mean absolute attitude error of less than 0.13 degrees in the yaw axis, and 0.06 degrees in the pitch and roll axes (3 σ) for a calibrated wide-angle camera lens. These findings demonstrate the viability of low-cost, wide-angle, strapdown celestial attitude sensors on lightweight UAV hardware.