Minimum-Entropy Autofocusing Based on Re-PSO for Ionospheric Scintillation Mitigation in P-Band SAR Imaging

Yu, Lei; Zhang, Yongsheng; Zhang, Qilei; Ji, Yifei; Dong, Zhen

doi:10.1109/access.2019.2924802

Cited by 13 publications

(5 citation statements)

References 36 publications

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“…Based on the ACF of the simulated Moreover, as mentioned in [16] and [28], better focusing results in a smaller entropy and a larger correlation coefficient. So, the index of mean and deviation values of correlation coefficient [5] and image entropy [20], [28] are evaluated using the original scintillation-free image, distorted image and refocused images of those above experiment. Here, the definition of correlation coefficient γ between two SLC SAR images S1 and S2 is where S(i, j) denotes the element in the i-th row and j-th column of the image.…”

Section: A Results Using Simulated Point Targetsmentioning

confidence: 99%

“…The state-of-the-art method for estimating and compensating the SAR scintillation phase is the FR-based methodology, but fully polarized SAR data are required [5]. For single polarization SAR, autofocus techniques are proposed for refocusing the image distorted by scintillation, such as phase gradient autofocus (PGA) [16]- [18] and the minimum-entropy method [19], [20]. PGA is a nonparametric autofocus method, and mainly used in airborne SAR motion compensation.…”

Section: Introductionmentioning

confidence: 99%

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A Modified PGA for Spaceborne SAR Scintillation Compensation Based on the Weighted Maximum Likelihood Estimator and Data Division

Zeng

Yang

Wang

et al. 2022

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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The P-band spaceborne synthetic aperture radar (SAR) is significantly affected by ionospheric scintillation. Although the traditional phase gradient autofocus (PGA) can estimate and compensate the scintillation phase of the single polarization SAR data, the quality of the refocused image will degrade at the scene edge. In this paper, a modified PGA based on the weighted maximum likelihood (WML) estimator and data division is proposed for full-scene image refocusing. First, a data division strategy for scintillation corrupted image is introduced, which is based on the prior scintillation information including its power spectral density (PSD) and autocorrelation function (ACF). Then, some pre-processing steps including data selection, circular shifting and windowing are performed for suppressing the noise and clutter. Finally, the scintillation phase is estimated by the WML estimator with fewer iterations, and after the scintillation phase of all data blocks are obtained, the distorted full-scene image is refocused. Using the generated wide-band ionospheric scintillation model (WBMOD) phase screen, numerical simulations based on point targets and scenes derived from real spaceborne SAR data are carried out. The evaluation results about resolution, peak side-lobe ratio (PSLR), integral side-lobe ratio (ISLR), correlation coefficient and image entropy demonstrate the effectiveness of the proposed algorithm.

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Section: A Results Using Simulated Point Targetsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Modified PGA for Spaceborne SAR Scintillation Compensation Based on the Weighted Maximum Likelihood Estimator and Data Division

Zeng

Yang

Wang

et al. 2022

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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show abstract

“…Li et al [6][7][8][9] modify the particle swarm optimization method and achieved good results. Today, some existing methods spend a lot of time in threshold calculation [10,11] such as Otsu method [12][13][14] and iterative threshold method [15,16]. Although these methods are widely used, their results are unstable.…”

Section: Introductionmentioning

confidence: 99%

Fast Segmentation Method of Sonar Images for Jacket Installation Environment

Mao¹,

Yan²,

Liu³

et al. 2023

Intelligent Automation &Amp; Soft Computing

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It has remained a hard nut for years to segment sonar images of jacket installation environment, most of which are noisy images with inevitable blur after noise reduction. For the purpose of solutions to this problem, a fast segmentation algorithm is proposed on the basis of the gray value characteristics of sonar images. This algorithm is endowed with the advantage in no need of segmentation thresholds. To realize this goal, we follow the undermentioned steps: first, calculate the gray matrix of the fuzzy image background. After adjusting the gray value, the image is divided into three regions: background region, buffer region and target regions. After filtering, we reset the pixels with gray value lower than 255 to binarize images and eliminate most artifacts. Finally, the remaining noise is removed by morphological processing. The simulation results of several sonar images show that the algorithm can segment the fuzzy sonar images quickly and effectively. Thus, the stable and feasible method is testified.

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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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Minimum-Entropy Autofocusing Based on Re-PSO for Ionospheric Scintillation Mitigation in P-Band SAR Imaging

Cited by 13 publications

References 36 publications

A Modified PGA for Spaceborne SAR Scintillation Compensation Based on the Weighted Maximum Likelihood Estimator and Data Division

A Modified PGA for Spaceborne SAR Scintillation Compensation Based on the Weighted Maximum Likelihood Estimator and Data Division

Fast Segmentation Method of Sonar Images for Jacket Installation Environment

An Improved Phase Gradient Autofocus Algorithm For ISAR Phase Autofocus Problem

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