Improving the estimation accuracy and computational efficiency of ISAR range alignment

Vehmas, Risto; Jylhä, Juha

doi:10.23919/eurad.2017.8249135

Cited by 2 publications

(3 citation statements)

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“…The global range alignment method [69], [70] estimates the translation by minimizing a loss function, whose value quantitatively measure the quality of the range alignment for the entire CPI. Several different quality measures have been proposed [71], [72], such as the This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/ This article has been accepted for publication in a future issue of this journal, but has not been fully edited.…”

Section: Range Alignmentmentioning

confidence: 99%

“…The minimum entropy method is essentially non-parametric. Methods to speed up the computation of the global method have been proposed in [72], [73]. An efficient hybrid between the global and local pulse-to-pulse methods uses the average range profile (i. e., data from the entire CPI) in the loss function but does the estimation on a pulse-to-pulse basis [74]- [76].…”

Section: Range Alignmentmentioning

confidence: 99%

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

Vehmas¹,

Neuberger

2021

IEEE Access

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Radar can obtain high spatial resolution at large operating distances and its operation is largely independent from weather and lighting conditions. This makes it an important instrument in an ever-increasing number of applications requiring robust and reliable sensing of the environment. Due to the advancements in semiconductor technology and digital computation power, radar can obtain increasingly better position estimation accuracy, detection sensitivity, and target resolution. High-resolution imaging is an example of a rapidly advancing field of radar technology. Inverse synthetic aperture radar (ISAR) is an imaging technique that uses the motion of a target to obtain a high-resolution radar image of it. This paper presents a comprehensive review of past work and the state-of-the-art in ISAR imaging systems, algorithms, and applications. Starting from the early historical developments of simple monostatic range-Doppler imaging, we present the developments up to the current advanced spatially distributed imaging modalities and reconstruction algorithms. The list of references includes the most influential ISAR publications in the open literature up to early 2021.

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Section: Range Alignmentmentioning

confidence: 99%

Section: Range Alignmentmentioning

confidence: 99%

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

Vehmas¹,

Neuberger

2021

IEEE Access

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“…The phase autofocus algorithm based on the image sharpness functions [14] is a local optimization problem. The method rst selects an objective function, such as entropy [6] [7] [14][18] [19] , contrast [1][10] [11][13] [20] , and so on. Then, the optimization algorithm is used to nd the optimum solution of the objective function.…”

Section: Introductionmentioning

confidence: 99%

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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Improving the estimation accuracy and computational efficiency of ISAR range alignment

Cited by 2 publications

References 10 publications

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

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

An Improved Phase Gradient Autofocus Algorithm For ISAR Phase Autofocus Problem

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