TY - GEN
T1 - Detecting and Mitigating Radio Frequency Interference Artifacts via Tensor Decomposition of Multi-Temporal SAR Images
AU - Lai, Siqi
AU - Liu, Yanyang
AU - Tao, Mingliang
AU - Su, Jia
AU - Wang, Ling
N1 - Publisher Copyright:
© 2023 International Union of Radio Science.
PY - 2023
Y1 - 2023
N2 - Radio frequency interference (RFI) in space-based radar echo signals may affect the coherent focus imaging process, resulting in blurred scattered images or occlusion artifacts. Conventional echo domain RFI mitigation methods do not work well with image domain data. Therefore, a novel RFI mitigation method based on tensor low-rank sparse decomposition in the image domain is proposed in this paper. The tensor low-rank sparse decomposition problem can fully preserve the spatial correlation between images. A joint mathematical model of low-rank sparse tensor decomposition is established and solved to achieve the extraction and mitigation of remote sensing image interference. The results of Sentinel-lA data show that the method can extract interference artifacts and recover clear background images. The interference mitigation performance of this method is better compared with the previously proposed matrix decomposition method.
AB - Radio frequency interference (RFI) in space-based radar echo signals may affect the coherent focus imaging process, resulting in blurred scattered images or occlusion artifacts. Conventional echo domain RFI mitigation methods do not work well with image domain data. Therefore, a novel RFI mitigation method based on tensor low-rank sparse decomposition in the image domain is proposed in this paper. The tensor low-rank sparse decomposition problem can fully preserve the spatial correlation between images. A joint mathematical model of low-rank sparse tensor decomposition is established and solved to achieve the extraction and mitigation of remote sensing image interference. The results of Sentinel-lA data show that the method can extract interference artifacts and recover clear background images. The interference mitigation performance of this method is better compared with the previously proposed matrix decomposition method.
UR - http://www.scopus.com/inward/record.url?scp=85175148638&partnerID=8YFLogxK
U2 - 10.23919/URSIGASS57860.2023.10265485
DO - 10.23919/URSIGASS57860.2023.10265485
M3 - 会议稿件
AN - SCOPUS:85175148638
T3 - 2023 35th General Assembly and Scientific Symposium of the International Union of Radio Science, URSI GASS 2023
BT - 2023 35th General Assembly and Scientific Symposium of the International Union of Radio Science, URSI GASS 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 35th General Assembly and Scientific Symposium of the International Union of Radio Science, URSI GASS 2023
Y2 - 19 August 2023 through 26 August 2023
ER -