Spiral SAR Imaging with Fast Factorized Back-Projection: A Phase Error Analysis

This paper presents a fast factorized back-projection (FFBP) algorithm that can satisfactorily process real P-band synthetic aperture radar (SAR) data collected from a spiral flight pattern performed by a drone-borne SAR system. Choosing the best setup when processing SAR data with an FFBP algorithm is not so straightforward, so predicting how this choice will affect the quality of the output image is valuable information. This paper provides a statistical phase error analysis to validate the hypothesis that the phase error standard deviation can be predicted by geometric parameters specified at the start of processing. In particular, for a phase error standard deviation of ~12°, the FFBP is up to 21 times faster than the direct back-projection algorithm for 3D images and up to 13 times faster for 2D images.

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A modified back-projection algorithm for imaging Geo-referenced SAR data

2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS) ◽

10.1109/igarss.2015.7326825 ◽

2015 ◽

Author(s):

Songtao Zhao ◽

Jie Chen ◽

Bing Sun ◽

Wei Yang ◽

Pengbo Wang

Keyword(s):

Projection Algorithm ◽

Back Projection ◽

Sar Data

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Multiple Local Autofocus Back-Projection Algorithm for Space-Variant Phase-Error Correction in Synthetic Aperture Radar

IEEE Geoscience and Remote Sensing Letters ◽

10.1109/lgrs.2016.2578719 ◽

2016 ◽

Vol 13 (9) ◽

pp. 1241-1245 ◽

Cited By ~ 9

Author(s):

Lei Ran ◽

Zheng Liu ◽

Lei Zhang ◽

Rong Xie ◽

Tao Li

Keyword(s):

Synthetic Aperture Radar ◽

Error Correction ◽

Phase Error ◽

Projection Algorithm ◽

Synthetic Aperture ◽

Back Projection ◽

Space Variant ◽

Aperture Radar

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Focusing High-Resolution Airborne SAR with Topography Variations Using an Extended BPA Based on a Time/Frequency Rotation Principle

Remote Sensing ◽

10.3390/rs10081275 ◽

2018 ◽

Vol 10 (8) ◽

pp. 1275 ◽

Cited By ~ 6

Author(s):

Chunhui Lin ◽

Shiyang Tang ◽

Linrang Zhang ◽

Ping Guo

Keyword(s):

High Resolution ◽

Time Domain ◽

Phase Error ◽

Projection Algorithm ◽

Geometric Distortion ◽

Back Projection ◽

Time Frequency ◽

Phase Errors ◽

Airborne Sar ◽

The Time Domain

With the increasing requirement for resolution, the negligence of topography variations causes serious phase errors, which leads to the degradation of the focusing quality of the synthetic aperture (SAR) imagery, and geometric distortion. Hence, a precise and fast algorithm is necessary for high-resolution airborne SAR. In this paper, an extended back-projection (EBP) algorithm is proposed to compensate the phase errors caused by topography variations. Three-dimensional (3D) variation will be processed in the time-domain for high-resolution airborne SAR. Firstly, the quadratic phase error (QPE) brought by topography variations is analyzed in detail for high-resolution airborne SAR. Then, the key operation, a time-frequency rotation operation, is applied to decrease the samplings in the azimuth time-domain. Just like the time-frequency rotation of the conventional two-step approach, this key operation can compress data in an azimuth time-domain and it reduces the computational burden of the conventional back-projection algorithm, which is applied lastly in the time-domain processing. The results of the simulations validate that the proposed algorithm, including frequency-domain processing and time-domain processing can obtain good focusing performance. At the same time, it has strong practicability with a small amount of computation, compared with the conventional algorithm.

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Processing Missile-Borne SAR Data by Using Cartesian Factorized Back Projection Algorithm Integrated with Data-Driven Motion Compensation

Remote Sensing ◽

10.3390/rs13081462 ◽

2021 ◽

Vol 13 (8) ◽

pp. 1462

Author(s):

Min Bao ◽

Song Zhou ◽

Mengdao Xing

Keyword(s):

Time Domain ◽

Motion Compensation ◽

Phase Error ◽

Data Driven ◽

Projection Algorithm ◽

Compressed Domain ◽

Fast Time ◽

Back Projection ◽

Motion Error ◽

Efficient Data

Due to the independence of azimuth-invariant assumption of an echo signal, time-domain algorithms have significant performance advantages for missile-borne synthetic aperture radar (SAR) focusing with curve moving trajectory. The Cartesian factorized back projection (CFBP) algorithm is a newly proposed fast time-domain implementation which can avoid massive interpolations to improve the computational efficiency. However, it is difficult to combine effective and efficient data-driven motion compensation (MOCO) for achieving high focusing performance. In this paper, a new data-driven MOCO algorithm is developed under the CFBP framework to deal with the motion error problem for missile-borne SAR application. In the algorithm, spectrum compression is implemented after a CFBP process, and the SAR images are transformed into the spectrum-compressed domain. Then, the analytical image spectrum is obtained by utilizing wavenumber decomposition based on which the property of motion induced error is carefully investigated. With the analytical image spectrum, it is revealed that the echoes from different scattering points are aligned in the same spectrum range and the phase error becomes a spatial invariant component after spectrum compression. Based on the spectrum-compressed domain, an effective and efficient data-driven MOCO algorithm is accordingly developed for accurate error estimation and compensation. Both simulations of missile-borne SAR and raw data experiment from maneuvering highly-squint airborne SAR are provided and analyzed, which show high focusing performance of the proposed algorithm.

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