@inproceedings{ebd45a4bc554474c815b7ca0544ca92f,
title = "Multi-Source Image Fusion for GNSS-Based Passive Radar",
abstract = "Global Navigation Satellite System (GNSS)-based Passive Radar (GPR) is gaining increasing attentions recently due to its potential on moving target detection (MTD). The main problem of the GPR is the low power density of GNSS signals. With the upgrades of GNSS, the total transmit power for the new launched satellites has been greatly improved. However, the total transmit power is allocated to several independent signals, which cannot be directly integrated. This paper proposes a multi-source image fusion method for the GPR which aims at coherently integrating the power allocated to different signals for the same satellite, and improving the detection performance. Validation experiments using GPS signals as illumination source and an airplane as target are conducted. The target is successfully detected by exploiting GPS L1 and L5 signals for the same satellite as illumination sources. Two-image fusion is performed utilizing the proposed method. Significant SNR improvement is achieved, which validates the feasibility of the proposed method.",
keywords = "GNSS-based Passive Radar, MTD, SNR improvement, image fusion",
author = "Xinkai Zhou and Pengbo Wang and Jie Chen and Hongcheng Zeng",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 2022 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2022 ; Conference date: 17-07-2022 Through 22-07-2022",
year = "2022",
doi = "10.1109/IGARSS46834.2022.9883748",
language = "英语",
series = "International Geoscience and Remote Sensing Symposium (IGARSS)",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "3708--3711",
booktitle = "IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium",
address = "美国",
}