Platform Vibration Fine Modeling and Adaptive Motion Compensation Algorithm for Terahertz SAR Imaging

CHEN Si-yu; WANG Yong

doi:10.12263/DZXB.20241174

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Platform Vibration Fine Modeling and Adaptive Motion Compensation Algorithm for Terahertz SAR Imaging

PAPERS | 更新时间：2025-08-18

- Platform Vibration Fine Modeling and Adaptive Motion Compensation Algorithm for Terahertz SAR Imaging
- ACTA ELECTRONICA SINICA Vol. 53, Issue 5, Pages: 1500-1519(2025)
- 作者机构：
  
  哈尔滨工业大学电子与信息工程学院，黑龙江哈尔滨 150001
- 作者简介：
- 基金信息：
  
  National Science Fund for Distinguished Young Scholars under grant(62325104)
- DOI：10.12263/DZXB.20241174
  CLC： TN957.52;
- Received：30 December 2024，
  
  Revised：2025-04-25，
  
  Published：25 May 2025
- 稿件说明：
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陈思雨, 王勇. 太赫兹SAR平台振动精细化建模与自适应运动补偿算法研究[J]. 电子学报, 2025, 53(05): 1500-1519.

CHEN Si-yu, WANG Yong. Platform Vibration Fine Modeling and Adaptive Motion Compensation Algorithm for Terahertz SAR Imaging[J]. Acta Electronica Sinica, 2025, 53(05): 1500-1519.
陈思雨, 王勇. 太赫兹SAR平台振动精细化建模与自适应运动补偿算法研究[J]. 电子学报, 2025, 53(05): 1500-1519. DOI：10.12263/DZXB.20241174

CHEN Si-yu, WANG Yong. Platform Vibration Fine Modeling and Adaptive Motion Compensation Algorithm for Terahertz SAR Imaging[J]. Acta Electronica Sinica, 2025, 53(05): 1500-1519. DOI：10.12263/DZXB.20241174

摘要

太赫兹合成孔径雷达（Synthetic Aperture Radar，SAR）凭借其高分辨率成像和精细目标细节提取能力，展现出广阔的应用前景.由于信号波长较短，太赫兹SAR极易受到平台振动的影响，导致其成像过程中存在虚假成像点、沿方位向模糊、SAR图像散焦等诸多问题.为解决这一挑战，本文对复杂太赫兹SAR平台振动进行精细化建模，并对应地提出了太赫兹SAR自适应运动补偿算法，基于数理模型分析平台振动对成像过程影响机理，灵活精确地补偿实际场景中复杂的太赫兹SAR平台振动.首先，本文提出了基于时变幅度调制振动模型（Temporal Amplitude Modulation Vibration Model，TAMVM）的太赫兹SAR平台振动的精细化建模方法.通过集成余弦时变幅度和随机时变幅度调制模型，TAMVM模型克服了传统简谐振动模型的局限性，提升了对复杂多变的太赫兹SAR平台振动的适配性.其次，针对传统依赖简谐模型的运动补偿算法在处理复杂平台振动时的性能损失，提出了最小Tsallis熵准则下基于列文伯格-马夸尔特（Levenberg-Marquardt，LM）算法的太赫兹SAR自适应运动补偿方法.本文提出的图像质量驱动的运动补偿算法无需依赖特显点，能够在非线性最小二乘框架下精确估计复杂多变的回波振动相位，且无需额外的补偿步骤.同时，本文在最小Tsallis熵准则下精确推导了LM算法的迭代运算过程.该算法通过自适应调整搜索位移实现反馈更新和迭代优化，能够精确估计回波振动相位并抑制图像模糊，从而获得高质量的聚焦太赫兹SAR图像.仿真与实测数据的对比结果验证了本文所提的TAMVM振动模型的合理性和可行性，以及所提自适应运动补偿方法在精准聚焦太赫兹SAR图像与抑制虚假成像点方面的优越性.

Abstract

Terahertz synthetic aperture radar (SAR) exhibits broad application prospects due to its capability for high-resolution imaging and detailed target extraction. However

its short wavelength makes terahertz SAR extremely susceptible to the platform vibration

leading to many issues during the imaging process such as false imaging points

azimuthal blurring

and defocused SAR images. Therefore

this paper establishes a fine platform vibration model of terahertz SAR

and proposes an adaptive terahertz SAR motion compensation algorithm. Based on the impact mechanism analysis of the platform vibration on imaging using the mathematical model

the complex platform vibration in terahertz SAR imaging scenes can be compensated flexibly and accurately. Firstly

a fine terahertz SAR vibration model is established based on the temporal amplitude modulation vibration model (TAMVM). By integrating the cosine time-varying amplitude and the random time-varying amplitude modulation vibration model

the TAMVM model reduces the limitation of the traditional harmonic model

and improves the adaptability to the complex and variable terahertz SAR platform vibration. Secondly

to address the performance loss of traditional harmonic model-based motion compensation algorithms when handling the complex platform vibration

this paper proposes an adaptive motion compensation method based on the Levenberg-Marquardt (LM) algorithm under the minimum Tsallis entropy criterion. The image quality-driven motion compensation algorithm proposed in this paper does not rely on the dominant target points

and it can precisely estimate the complex and varying vibration phase under the nonlinear least squares framework without the additional compensation steps. Moreover

the iterative process of the LM algorithm is derived under the minimum Tsallis entropy criterion in this paper. This algorithm adaptively adjusts the search displacement to achieve the feedback update and the iterative optimization

enabling precise estimation of the vibration phase and suppression of image blur

thereby obtaining high-quality focused terahertz SAR images. Furthermore

the comparison results of the simulated and real-measured data verify the rationality and feasibility of the proposed TAMVM model

and demonstrate the superiority of the proposed adaptive motion compensation method in achieving the precise terahertz SAR image focusing and suppressing false imaging points.

关键词

Keywords

references

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