Statistical Multisource-Multitarget Information Fusion
Statistical Multisource-Multitarget Information Fusion
A New Starry Images Matching Method in Dim and Small Space Target Detection
ICIG '09 Proceedings of the 2009 Fifth International Conference on Image and Graphics
Relative entropy rate based multiple hidden Markov model approximation
IEEE Transactions on Signal Processing
The Gaussian Mixture Probability Hypothesis Density Filter
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
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In this paper, a real time method for detecting and tracking multiple dim targets in deep space background is presented. We matched the stars in tow continuous images to get their speed at first and found moving targets through speed in both images. Using the targets in the common frame data association is achieved. The Gaussian Mixture Probability Hypothesis Density (GM-PHD) filter is used to track targets to solve the problem of targets disappearance. To initialize of the birth random finite sets (RFSs) the targets sequences are built to find new targets. Extensive experiments on real images sequences show that the proposed approach could effectively meet the requirements of the real-time detection with a low false alarm rate and a high detection probability.