Performance Boundaries and Tradeoffs in Super-Resolution Imaging Technologies for Space Targets
XiaoLe He, Ping Liu, JunLing Wang

TL;DR
This paper explores the fundamental performance limits of super-resolution imaging algorithms for space targets using ISAR technology, deriving mathematical bounds and analyzing tradeoffs among key factors like rotation angle and energy.
Contribution
It introduces a mathematical framework based on CRL theory to determine resolution bounds and resource requirements for space target imaging, highlighting practical tradeoffs.
Findings
Derived explicit bounds for super-resolution in ISAR imaging.
Identified key factors influencing resolution limits, such as SNR and scatterer count.
Demonstrated tradeoffs through simulations across different scenarios.
Abstract
Inverse synthetic aperture radar (ISAR) super-resolution imaging technology is widely applied in space target imaging. However, the performance limits of super-resolution imaging algorithms remain a rarely explored issue. This paper investigates these limits by analyzing the boundaries of super-resolution algorithms for space targets and examines the relationships between key contributing factors. In particular, drawing on the established mathematical theory of computational resolution limits (CRL) for line spectrum reconstruction, we derive mathematical expressions for the upper and lower bounds of cross-range super-resolution imaging, based on ISAR imaging model transformations. Leveraging the explicit expressions, we first explore influencing factors of these bounds, such as the traditional Rayleigh limit, the number of scatterers, and the peak signal-to-noise ratio (PSNR) of…
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Taxonomy
TopicsCCD and CMOS Imaging Sensors · Advanced Semiconductor Detectors and Materials · Infrared Target Detection Methodologies
