Fast recognition algorithm for faint targets in complex space background

Abstract

<p indent="0mm">Imaging characteristics of stars and artificial targets in space are very similar in long-distance space-based observation as they are both light spots described by point spread function with a Gaussian distribution. In the condition of low signal-to-noise ratio, the signal of space artificial targets is faint on the image, which is covered with background and noise signals; thus, it is more difficult to recognize the faint space artificial targets from complex backgrounds. To solve this problem, this paper proposes a fast recognition algorithm for faint targets on the basis of matched filters. First, the imaging model of space artificial targets is built in the star tracking observation mode, wherein space artificial targets and stars appear as streaks and points, respectively. Therefore, the faint point target recognition problem is transferred to faint streak pattern recognition from light spot background. Second, the signal-to-noise ratio is used to define the faint degree of targets to evaluate the recognition limit of the algorithm. Then, a streak element pattern is designed. It is a part of the whole streak pattern; thus, the generation of streak patterns with varying lengths in the progress of matched filter can be avoided, so the calculation is decreased and the recognition speed is increased. Finally, to verify the fast recognition algorithm of faint targets, several images with stars and faint space artificial targets under different signal-to-noise ratios are simulated. The fast recognition algorithm of faint targets is tested using these simulation images; the results reveal that faint targets can be recognized from simulation images using this algorithm when the signal-to-noise ratio is above 0.5.