article · 2021
Online Super-Resolution Imaging for Airborne Scanning Radar Based on Sliding Window RLS Algorithm
Jiawei Luo, Yongchao Zhang, Yongwei Zhang, Yin Zhang, Yulin Huang, Haiguang Yang, Jianyu Yang
Cited by 2Abstract and details only
Abstract
Airborne radar high-squint looking imaging is an important research for remote sensing. The traditional Doppler beam sharpening based on fast Fourier transform (FFT) has good real-time performance but low cross-range resolution. Many super-resolution methods have been proposed to enhance the cross-range resolution for airborne radar. However, these methods generally adopt the batch processing mode with high computational complexity and high memory usage, which lead to poor real-time performance. This paper proposes an online super-resolution imaging approach for airborne scanning radar based on sliding window recursive least square (SWRLS) algorithm. The current scattering estimation can be derived recursively through downdating and updating. The proposed method effectively improves the cross-range resolution as well as the real-time performance and memory occupancy, which is beneficial to high-quint continuous realtime imaging for airborne radar. Simulation results are given to demonstrate the effectiveness of the proposed method.
Cite this paper
Luo, J., Zhang, Y., Zhang, Y., Zhang, Y., Huang, Y., Yang, H., & Yang, J. (2021). Online Super-Resolution Imaging for Airborne Scanning Radar Based on Sliding Window RLS Algorithm. https://doi.org/10.1109/igarss47720.2021.9553500
Luo, Jiawei, et al. “Online Super-Resolution Imaging for Airborne Scanning Radar Based on Sliding Window RLS Algorithm.” 2021, pp. 5067–70, https://doi.org/10.1109/igarss47720.2021.9553500.
Luo, Jiawei, Yongchao Zhang, Yongwei Zhang, Yin Zhang, Yulin Huang, Haiguang Yang, and Jianyu Yang. 2021. “Online Super-Resolution Imaging for Airborne Scanning Radar Based on Sliding Window RLS Algorithm.” https://doi.org/10.1109/igarss47720.2021.9553500.
Luo, J. et al. (2021) ‘Online Super-Resolution Imaging for Airborne Scanning Radar Based on Sliding Window RLS Algorithm’. Available at: https://doi.org/10.1109/igarss47720.2021.9553500.
@article{luo2021online,
title = {{Online Super-Resolution Imaging for Airborne Scanning Radar Based on Sliding Window RLS Algorithm}},
author = {Luo, Jiawei and Zhang, Yongchao and Zhang, Yongwei and Zhang, Yin and Huang, Yulin and Yang, Haiguang and Yang, Jianyu},
pages = {5067--5070},
year = {2021},
doi = {10.1109/igarss47720.2021.9553500}
}Made from the index record. Check names, capitalisation and page numbers against the paper. Need another style? AI for Research has over 10,000.