Noise-robust range alignment method for inverse synthetic aperture radar based on aperture segmentation and average range profile correlation

EURASIP journal on advances in signal processing

article

Lu, Yue¹  Yang, Jian²  Zhang, Yue¹  Xu, Shiyou³ 

[1] National Key Laboratory of Science and Technology on Automatic Target Recognition, National University of Defense Technology;Rocket Force University of Engineering;School of Electronics and Communication Engineering, Sun Yat-sen University

关键词: Aperture segmentation;    Entropy minimization;    Inverse synthetic aperture radar;    Range alignment;   

DOI  :  10.1186/s13634-020-00709-z

来源: SpringerOpen

【 摘 要 】

Range alignment is an essential procedure in the translation motion compensation of inverse synthetic aperture radar imaging. Global optimization or maximum-correlation-based algorithms have been used to realize range alignment. However, it is still challenging to achieve range alignment in low signal-to-noise ratio scenarios, which are common in inverse synthetic aperture radar imaging. In this paper, a novel anti-noise range alignment approach is proposed. In this new method, the target motion is modeled as a uniformly accelerated motion during a short sub-aperture time. Minimum entropy optimization is implemented to estimate the motion parameters in each sub-aperture. These estimated parameters can be used to align the profiles of the current sub-aperture. Once the range profiles of each sub-aperture are aligned, the non-coherent accumulation gain is obtained by averaging all profiles in each sub-aperture, which can be used as valuable information. The accumulation and correlation method is applied to align the average range profiles of each sub-aperture because the former step focuses mainly on alignment within the sub-apertures. Experimental results based on simulated and real measured data demonstrate the effectiveness of the proposed algorithm in low signal-to-noise ratio scenarios.

【 授权许可】

CC BY