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10.3390/rs15092368
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Article

ISAR Imaging of Non-Stationary Moving Target Based on Parameter Estimation and Sparse Decomposition

by
Can Liu
1,2,
Yunhua Luo
1,2,
Zhongjun Yu
1,2 and
Jie Feng
1,2,*
1
Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100080, China
2
School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 101400, China
*
Author to whom correspondence should be addressed.
Remote Sens. 2023, 15(9), 2368; https://doi.org/10.3390/rs15092368
Submission received: 6 March 2023 / Revised: 23 April 2023 / Accepted: 29 April 2023 / Published: 30 April 2023
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Abstract

This paper studies the inverse synthetic aperture radar imaging problem for a non-stationary moving target and proposes a non-search imaging method based on parameter estimation and sparse decomposition. The echoes received by radar can be thought of as consisting of chirp signals with varying chirp rates and center frequencies. Lv’s distribution (LVD) is introduced to accurately estimate these parameters. Considering their inherent sparsity, the signals are reconstructed via sparse representation using a redundant chirp dictionary. An efficient algorithm is developed to tackle the optimization problem for sparse decompositions. Then, by using the reconstructed data, adaptive joint time–frequency imaging techniques are employed to create high-quality images of the non-stationary moving target. Finally, the simulated experiments and measured data processing results confirm the proposed method’s validity.
Keywords: inverse synthetic aperture radar (ISAR) imaging; time–frequency analysis; Lv’s distribution; sparse recovery; non-stationary moving target inverse synthetic aperture radar (ISAR) imaging; time–frequency analysis; Lv’s distribution; sparse recovery; non-stationary moving target

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MDPI and ACS Style

Liu, C.; Luo, Y.; Yu, Z.; Feng, J. ISAR Imaging of Non-Stationary Moving Target Based on Parameter Estimation and Sparse Decomposition. Remote Sens. 2023, 15, 2368. https://doi.org/10.3390/rs15092368

AMA Style

Liu C, Luo Y, Yu Z, Feng J. ISAR Imaging of Non-Stationary Moving Target Based on Parameter Estimation and Sparse Decomposition. Remote Sensing. 2023; 15(9):2368. https://doi.org/10.3390/rs15092368

Chicago/Turabian Style

Liu, Can, Yunhua Luo, Zhongjun Yu, and Jie Feng. 2023. "ISAR Imaging of Non-Stationary Moving Target Based on Parameter Estimation and Sparse Decomposition" Remote Sensing 15, no. 9: 2368. https://doi.org/10.3390/rs15092368

APA Style

Liu, C., Luo, Y., Yu, Z., & Feng, J. (2023). ISAR Imaging of Non-Stationary Moving Target Based on Parameter Estimation and Sparse Decomposition. Remote Sensing, 15(9), 2368. https://doi.org/10.3390/rs15092368

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