Multi-targets ISAR Imaging Technology based on Robust Principal Component Analysis
Fan YE, Zelong WANG, Jubo ZHU
Available Online July 2017.
- 10.2991/eia-17.2017.36How to use a DOI?
- multi-targets; inverse synthetic aperture radar; low-rank; robust principal component analysis
In multi-targets inverse synthetic aperture radar imaging, range profiles of multi-targets with different motion are coupled, so traditional Range-Doppler imaging algorithm is failure. A new imaging technology based on low-rank decomposition is proposed in this paper. After translational compensation and range compression, multi-targets signal can be decomposed into a low-rank part and a sparse part by Robust Principal Component Analysis. Then imaging processing is applied in multiple signals respectively. Simulation results verify the validity of the proposed method.
- © 2017, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Fan YE AU - Zelong WANG AU - Jubo ZHU PY - 2017/07 DA - 2017/07 TI - Multi-targets ISAR Imaging Technology based on Robust Principal Component Analysis BT - Proceedings of the 2017 International Conference on Electronic Industry and Automation (EIA 2017) PB - Atlantis Press SP - 168 EP - 171 SN - 1951-6851 UR - https://doi.org/10.2991/eia-17.2017.36 DO - 10.2991/eia-17.2017.36 ID - YE2017/07 ER -