@inproceedings{8e5dc7658de9467d84514c5d600fd6f2,
title = "An improved unscented Kalman filter for satellite tracking",
abstract = "In order to detect satellite under sky background, we propose an optimized satellite object detection extraction and tracking algorithm under the sky background. The proposed satellite tracking processing consists of two stages. In the first stage of object detection and extraction, the background template based on the mixture Gaussian model is used to establish background frame, and then the background is removed by inter-frame difference method to obtain the object. In the subsequent object tracking stage, this paper proposes an improved untracked Kalman filter algorithm for object tracking. Firstly, it tracks multiple suspected objects in the background, and then introduces a path coherence function to eliminate the false objects. Compared with other methods, the experimental results show that our method can better meet the real-Time requirement, eliminate false objects appeared in the sequence of images more efficiently and make the tracking trajectory smoother.",
keywords = "Mixed Gaussian model, Path coherence, Satellite tracking, Unscented Kalman filter",
author = "Zhenyu Zhu and Qiong Wu and Kun Gao and Youwen Zhuang and Jing Wang and Guangping Wang",
note = "Publisher Copyright: {\textcopyright} COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.; International Symposium on Optoelectronic Technology and Application 2018: Optical Sensing and Imaging Technologies and Applications 2018, OTA 2018 ; Conference date: 22-05-2018 Through 24-05-2018",
year = "2018",
doi = "10.1117/12.2503798",
language = "English",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "Dong Liu and Jin Lu and HaiMei Gong and Mircea Guina",
booktitle = "Optical Sensing and Imaging Technologies and Applications",
address = "United States",
}