一种改进的全息SAR相位梯度自聚焦算法

doi:10.12305/j.issn.1001-506X.2025.06.07

摘要/Abstract

摘要：

全息合成孔径雷达(holographic synthetic aperture radar, HoloSAR)成像是一种SAR三维成像模式, 通过不同空间维度的观测提供丰富的目标散射信息。相位梯度自聚焦(phase gradient autofocus, PGA)是一种高效的相位误差补偿方法, 其缺陷在于无法估计相位误差中的线性分量, 会造成HoloSAR子孔径成像结果高度偏移。因此, 提出一种改进的PGA方法, 将图像偏置算法拓展至三维成像, 用于估计PGA中的残余线性相位误差, 从而解决HoloSAR子孔径图像之间的高度偏移问题。所提方法能够在回波域和图像域联合校正相位误差, 相比于现有方法更加简便、高效。仿真目标和GOTCHA实测数据的处理结果证实了所提方法的有效性和实用性。

关键词: 三维成像, 全息合成孔径雷达, 相位误差校正, 相位梯度自聚焦

Abstract:

Holographic synthetic aperture radar (HoloSAR) imaging is a SAR three-dimensional (3D) imaging mode that provides rich target scattering information through observations from different spatial dimensions. The phase gradient autofocus (PGA) is an efficient method for phase error compensation. However, its limitation lies in the inability to estimate the linear component of the phase error, causing vertical shift among HoloSAR sub-aperture imaging results. Therefore, an improved PGA method is proposed which extends the map drift (MD) algorithm to 3D imaging. The proposed method estimates the residual linear phase error within PGA, addressing the vertical shift issue among HoloSAR sub-apertures imaging. The proposed method can jointly correct phase errors in both the echo domain and the image domain, and is simpler and more efficient compared to existing methods. The processing results of simulated targets and GOTCHA measured data confirm the effectiveness and practicality of the proposed method.

Key words: three-dimensional (3D) imaging, holographic synthetic aperture radar (HoloSAR), phase error correction, phase gradient autofocus (PGA)

中图分类号:

TN95

黄丰卓, 冯东, 华洋晟, 黄晓涛. 一种改进的全息SAR相位梯度自聚焦算法[J]. 系统工程与电子技术, 2025, 47(6): 1786-1795.

Fengzhuo HUANG, Dong FENG, Yangsheng HUA, Xiaotao HUANG. An improved holographic SAR phase gradient autofocus algorithm[J]. Systems Engineering and Electronics, 2025, 47(6): 1786-1795.

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参考文献 22

1	WILEY C A . Synthetic aperture radars[J]. IEEE Trans.on Aerospace and Electronic Systems, 1985 (3): 440- 443.
2	SONG S Q , DAI Y P . An effective image reconstruction enhancement method with convolutional reweighting for near-field SAR[J]. IEEE Antennas and Wireless Propagation Letters, 2024, 23 (8): 2486- 2490. doi: 10.1109/LAWP.2024.3397881
3	GE S D , FENG D , SONG S Q , et al. Sparse logistic regression based one-bit SAR imaging[J]. IEEE Trans.on Geoscience and Remote Sensing, 2023, 61, 5217915.
4	XIE Z , XU Z , FAN C Y , et al. Robust radar waveform optimization under target interpulse fluctuation and practical constraints via sequential Lagrange dual approximation[J]. IEEE Trans.on Aerospace and Electronic Systems, 2023, 59 (6): 9711- 9721. doi: 10.1109/TAES.2023.3260814
5	XIE Z , WU L L , ZHU J H , et al. RIS-aided radar for target detection: clutter region analysis and joint active-passive design[J]. IEEE Trans.on Signal Processing, 2024, 72, 1706- 1723. doi: 10.1109/TSP.2024.3371292
6	GE S D , SONG S Q , FENG D , et al. Efficient near-field millimeter-wave sparse imaging technique utilizing one-bit measurements[J]. IEEE Trans.on Microwave Theory and Techniques, 2024, 72 (10): 6049- 6061. doi: 10.1109/TMTT.2024.3379978
7	SONG S Q , DAI Y P , SUN S L , et al. Efficient image reconstruction methods based on structured sparsity for short-range radar[J]. IEEE Trans.on Geoscience and Remote Sensing, 2024, 62, 5212615.
8	FERRETTI A , PRATI C , ROCCA F . Permanent scatterers in SAR interferometry[J]. IEEE Trans.on Geoscience and Remote Sensing, 2001, 39 (1): 8- 20. doi: 10.1109/36.898661
9	GATTI G , TEBALDINI S . ALGAE: a fast algebraic estimation of interferogram phase offsets in space-varying geometries[J]. IEEE Trans.on Geoscience and Remote Sensing, 2010, 49 (6): 2343- 2353.
10	TEBALDINI S , ROCCA F . Phase calibration of airborne tomographic SAR data via phase center double localization[J]. IEEE Trans.on Geoscience and Remote Sensing, 2015, 54 (3): 1775- 1792.
11	WANG D W , ZHANG F B , CHEN L Y , et al. The calibration method of multi-channel spatially varying amplitude-phase inconsistency errors in airborne array TomoSAR[J]. Remote Sensing, 2023, 15 (12): 3032. doi: 10.3390/rs15123032
12	PARDINI M, PAPATHANASSIOU K, BIANCO V, et al. Phase calibration of multibaseline SAR data based on a minimum entropy criterion[C]//Proc. of the IEEE International Geo- science and Remote Sensing Symposium, 2012: 5198-5201.
13	AGHABABAEE H , FORNARO G , SCHIRINZI G . Phase cali- bration based on phase derivative constrained optimization in multibaseline SAR tomography[J]. IEEE Trans.on Geoscience and Remote Sensing, 2018, 56 (11): 6779- 6791. doi: 10.1109/TGRS.2018.2843447
14	冯东. 多基线SAR三维成像技术研究[D]. 长沙: 国防科技大学, 2020.
	FENG D. Research on technologies of multibaseline SAR three- dimensional imaging[D]. Changsha: National University of Defense Technology, 2020.
15	WAHL D E , EICHEL P H , GHIGLIA D C , et al. Phase gradient autofocus-a robust tool for high resolution SAR phase correction[J]. IEEE Trans.on Aerospace and Electronic Systems, 1994, 30 (3): 827- 835. doi: 10.1109/7.303752
16	孙希龙. SAR层析与差分层析成像技术研究[D]. 长沙: 国防科技大学, 2012.
	SUN X L. Research on SAR tomography and differential SAR tomography imaging technology[D]. Changsha: National University of Defense Technology, 2012.
17	FENG D , AN D X , HUANG X T , et al. A phase calibration method based on phase gradient autofocus for airborne holographic SAR imaging[J]. IEEE Geoscience and Remote Sensing Letters, 2019, 16 (12): 1864- 1868. doi: 10.1109/LGRS.2019.2911932
18	LU H L , ZHANG H , FAN H T , et al. Forest height retrieval using P-band airborne multi-baseline SAR data: a novel phase compensation method[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2021, 175, 99- 118. doi: 10.1016/j.isprsjprs.2021.02.022
19	LU H L , SUN J L , WANG J L , et al. A novel phase compensation method for urban 3D reconstruction using SAR tomography[J]. Remote Sensing, 2022, 14 (16): 4071. doi: 10.3390/rs14164071
20	HUANG Y , LIU F Y , CHEN Z Y , et al. An improved map-drift algorithm for unmanned aerial vehicle SAR imaging[J]. IEEE Geoscience and Remote Sensing Letters, 2020, 18 (11): 1- 5.
21	AUSTIN C D, ERTIN E, MOSES R L. Sparse multipass 3D SAR imaging: applications to the GOTCHA data set[C]//Proc. of the Algorithms for Synthetic Aperture Radar Imagery XVI, 2009: 19-30.
22	DUNGAN K E , POTTER L C . 3D imaging of vehicles using wide aperture radar[J]. IEEE Trans.on Aerospace and Electronic Systems, 2011, 47 (1): 187- 200. doi: 10.1109/TAES.2011.5705669

参数名称	参数值
中心频率/GHz	9.6
信号带宽/MHz	640
入射角/(°)	45
中心斜距/m	4 242.6
层析向分辨率/m	0.474
不模糊高度范围/m	3.315

方法	x-z平面		y-z平面		x-y平面		三维图像
方法	IE	IC	IE	IC	IE	IC	IE	IC
COA	8.310	2.810	7.983	2.577	7.514	2.594	11.262	1.339
NC-PGA	8.325	2.358	7.941	2.340	7.540	2.179	11.111	1.608
PGA-MD	8.149	2.716	7.816	2.555	7.443	2.350	10.874	1.757

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