Inverse Synthetic Aperture Radar Imaging: A Historical Perspective and State-of-the-Art Survey

Vehmas, Risto; Neuberger, Nadav

doi:10.1109/access.2021.3104799

Cited by 24 publications

(8 citation statements)

References 368 publications

(243 reference statements)

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“…The entropy formula is shown in Eq. (15). Due to the randomness of complex Gaussian white noise, here we conduct 100 rounds of Monte Carlo experiments and nd the average entropy values of all experimental results.…”

Section: B Image-focusing Effectmentioning

confidence: 99%

“…The current phase autofocus algorithms are divided into two categories [15] : phase autofocus algorithms based on image sharpness functions and phase autofocus algorithms based on scatters.…”

Section: Introductionmentioning

confidence: 99%

“…However, these methods still require many iterations. In addition, this kind of method is suitable for images with high contrast [15] , so the usage of these methods is somewhat limited.…”

Section: Introductionmentioning

confidence: 99%

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An Improved Phase Gradient Autofocus Algorithm For ISAR Phase Autofocus Problem

Fu¹,

Li²

2023

Preprint

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The Phase Gradient Autofocus Algorithm (PGA) is widely used in radar imaging due to its ability to achieve high accuracy estimation of phase error of arbitrary orders. However, in inverse synthetic aperture radar (ISAR) imaging, the target usually occupies continuous range bins and there may be multiple stronger scatters in a range bin. In this case, the range bins selection method of the conventional algorithm tends to miss a part of the useful data contained in the target, and its windowing method also tends to cause the loss of useful high-frequency components in the range bins. Aiming at the above problems, an improved PGA algorithm is proposed in this paper. It uses an amplitude-based traversal method and Kaiser window to retain the valid echo data in the target and range bins, and eventually to achieve phase autofocus. Simulation results show that the improved method can obtain more stable and evident focusing results for ISAR target faster than the conventional method.

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Section: B Image-focusing Effectmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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An Improved Phase Gradient Autofocus Algorithm For ISAR Phase Autofocus Problem

Fu¹,

Li²

2023

Preprint

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“…This translational motion dr 0 / dt is the same for every point target and gives each scatterer the same Doppler shift. Hence this phase offset is not useful for the ISAR imaging process and has to be corrected later in the image processing procedure [25].…”

Section: Measurement Modelmentioning

confidence: 99%

High‐resolution inverse synthetic aperture radar imaging of satellites in space

Anger,

Jirousek,

Dill

et al. 2023

IET Radar Sonar & Navi

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In view of the increasing number of space objects, comprehensive high‐quality space surveillance becomes ever more important. Radar is a powerful tool that, in addition to detection and tracking of objects, also enables spatially high‐resolution imaging independent of daylight and most weather conditions. Together with the technique of Inverse Synthetic Aperture Radar (ISAR), very high‐resolution and distance‐independent two‐dimensional images can be obtained. However, advanced high‐performance radar imaging of space objects is a complex and demanding task, touching many technological and signal processing issues. Therefore, besides theoretical work, the Microwaves and Radar Institute of German Aerospace Center (DLR) has developed and constructed an experimental radar system called IoSiS (Imaging of Satellites in Space) for basic research on new concepts for the acquisition of advanced high‐resolution radar image products of objects in a low earth orbit. Based on pulse radar technology, which enables precise calibration and error correction, IoSiS has imaged space objects with a spatial resolution in the centimetre range, being novel in public perception and accessible literature. The goal of this paper is therefore to communicate and illustrate comprehensively the technological steps for the construction and successful operation of advanced radar‐based space surveillance. Besides the basic description of the IoSiS system design this paper outlines primarily useful theory for ISAR imaging of objects in space, together with relevant imaging parameters and main formulae. All relevant processing steps, necessary for very high‐resolution imaging of satellites in practice, are introduced and verified by simulation results. Finally, a unique measurement result demonstrates the practicability of the introduced processing steps and error correction strategies.

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“…The use of multistatic, or even Multiple Input Multiple Output (MIMO), ISAR systems with multiple sensors observing the same target with different acquisitions geometries and the joint exploitation of the acquired data allow much richer information to be garnered, overcoming limitations (ii) and (iii) imposed by conventional systems due to their single perspective. Over the last decade, researchers investigated the potentialities of multistatic/MIMO ISAR configurations for different tasks, see [5] and references therein.…”

Section: Introductionmentioning

confidence: 99%

Decentralized Approach for Translational Motion Estimation with Multistatic Inverse Synthetic Aperture Radar Systems

Testa,

Pastina,

Santi

2023

Remote Sensing

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This paper addresses the estimation of the target translational motion by using a multistatic Inverse Synthetic Aperture Radar (ISAR) system composed of an active radar sensor and multiple receiving-only devices. Particularly, a two-step decentralized technique is derived: the first step estimates specific signal parameters (i.e., Doppler frequency and Doppler rate) at the single-sensor level, while the second step exploits these estimated parameters to derive the target velocity and acceleration components. Specifically, the second step is organized in two stages: the former is for velocity estimation, while the latter is devoted to velocity estimation refinement if a constant velocity model motion can be regarded as acceptable, or to acceleration estimation if a constant velocity assumption does not apply. A proper decision criterion to select between the two motion models is also provided. A closed-form theoretical performance analysis is provided for the overall technique, which is then used to assess the achievable performance under different distributions of the radar sensors. Additionally, a comparison with a state-of-the-art centralized approach has been carried out considering computational burden and robustness. Finally, results obtained against experimental multisensory data are shown confirming the effectiveness of the proposed technique and supporting its practical application.

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Inverse Synthetic Aperture Radar Imaging: A Historical Perspective and State-of-the-Art Survey

Cited by 24 publications

References 368 publications

An Improved Phase Gradient Autofocus Algorithm For ISAR Phase Autofocus Problem

An Improved Phase Gradient Autofocus Algorithm For ISAR Phase Autofocus Problem

High‐resolution inverse synthetic aperture radar imaging of satellites in space

Decentralized Approach for Translational Motion Estimation with Multistatic Inverse Synthetic Aperture Radar Systems

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