Statistical Analysis of Performance of Optimisation‐Based SAR Autofocus

ABSTRACT Transionospheric SAR autofocus is a variational algorithm designed to circumvent the deficiencies of conventional autofocus techniques in correcting the distortions of spaceborne SAR images due to ionospheric turbulence. It has demonstrated superior performance in a variety of computer‐simulated imaging scenarios. In the current work, we conduct a systematic statistical analysis of transionospheric SAR autofocus aimed at corroborating its robustness and identifying limitations and sensitivities across a broad range of factors that affect the autofocus performance. We employ the range‐compressed domain representation where the target reflectivity, antenna signal, and the phase screen depend only on the azimuthal coordinate. The three main factors included in the study are the levels of turbulent perturbations, clutter, and noise. We use the normalised cross correlation (NCC), integrated sidelobe ratio (ISLR), and peak desynchronisation (PD) as a‐posteriori performance metrics. A key objective of the current analysis, beyond assessing the autofocus performance, is to identify the directions of how to further improve the algorithm, in terms of both the quality of focusing and associated computational cost.

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Publication Details

Journal
IET Radar Sonar & Navigation
Published
2025-01-01
DOI
https://doi.org/10.1049/rsn2.70030
Primary Topic
Advanced SAR Imaging Techniques
Type
article
Field-Weighted Citation Impact
0.00

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article

Statistical Analysis of Performance of Optimisation‐Based SAR Autofocus

Mikhail Gilman, Semyon Tsynkov, Patrick Haughey
IET Radar Sonar & Navigation
Advanced SAR Imaging Techniques
article

Statistical Analysis of Performance of Optimisation‐Based SAR Autofocus

Mikhail Gilman, Semyon Tsynkov, Patrick Haughey
article en

Abstract

ABSTRACT Transionospheric SAR autofocus is a variational algorithm designed to circumvent the deficiencies of conventional autofocus techniques in correcting the distortions of spaceborne SAR images due to ionospheric turbulence. It has demonstrated superior performance in a variety of computer‐simulated imaging scenarios. In the current work, we conduct a systematic statistical analysis of transionospheric SAR autofocus aimed at corroborating its robustness and identifying limitations and sensitivities across a broad range of factors that affect the autofocus performance. We employ the range‐compressed domain representation where the target reflectivity, antenna signal, and the phase screen depend only on the azimuthal coordinate. The three main factors included in the study are the levels of turbulent perturbations, clutter, and noise. We use the normalised cross correlation (NCC), integrated sidelobe ratio (ISLR), and peak desynchronisation (PD) as a‐posteriori performance metrics. A key objective of the current analysis, beyond assessing the autofocus performance, is to identify the directions of how to further improve the algorithm, in terms of both the quality of focusing and associated computational cost.

IET Radar Sonar & NavigationVol. 19(1)
North Carolina State University (US)
North Carolina Space Grant, Air Force Office of Scientific Research
Openalex Percentile: Top 87%
Advanced SAR Imaging Techniques
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Statistical Analysis of Performance of Optimisation‐Based SAR Autofocus — Mikhail Gilman, Semyon Tsynkov, et al. · IET Radar Sonar & Navigation (2025) | TGRS Research Map | TGRS