A Method for Star Extraction of the Air-Borne Star Sensor During the Daytime

This paper proposes a new approach to star image denoising, recognizing and centroiding for the airborne application, especially during the daytime. To extend attitude determination of aircraft to daytime, one prerequisite is to precisely obtain the centroid of the target star. To date, there has not been an adequate analytical model and experimental method to solve this problem effectively. Generally, three main problems of degraded images lie in the low signal-to-noise ratio, high intensity of the background and distorted star shape. To clearly validate the given method on star recognition, we focused on the static environment, without the severe distortion and motion blur. To demonstrate the proposed approach, an experiment was conducted with a camera and host computer. Specifically, it consisted of the star image acquisition, image processing and star recognition. Due to the denoising process, the noise component was eliminated effectively. Besides, by the connected region analysis and minimal area screening, the star pattern can be completely isolated. On top of that, the percentage of recognition amounted to 86.7% and the centroid precision was within 1/10 pixel. The experimental results demonstrate the potential of the proposed approach to the star recognition and extraction, during the daytime for airborne application.