Faint Ship Wake Detection in PolSAR Images

Zhou, Xu; Tang, Bo; Shuiying, Cheng

doi:10.1109/lgrs.2018.2823007

Cited by 12 publications

(6 citation statements)

References 21 publications

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“…With the development of the microwave and optical radar, several detection methods based on the image level have been proposed. Various methods such as Radon transform [1], [7], [8], Wavelet transform [9], the non-linear basis [10], the twostep approach [11], sparse regularisation [12], and the hybrid methods [13], [14] have been widely explored for ship wake detection in SAR image. However, some limitations, such as noisy echo and long revisit cycle for the SAR system, limit the ability to achieve high detection precision.…”

Section: Introductionmentioning

confidence: 99%

A Novel Data-Driven Scheme for the Ship Wake Identification on the 2-D Dynamic Sea Surface

Zhang

Jiang

2020

IEEE Access

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Because the ship wake spreads into an area much larger than that of the ship hull in the sea surface, it has been widely used in the ship detection. However, due to the complex sea wave motion and the high sea state, the ship wake detection is still a challenging task. In this paper, we propose a novel data-driven method based on dynamic mode decomposition (DMD) to detect, reconstruct, and locate the Kelvin wake on the two-dimensional dynamic sea surface. Through the proposed method, the sea's dynamic characteristics including the oscillation frequency and decay/growth rate of ship wakes and the time-varying sea surface can be obtained. Meanwhile, the spatial features of ship wakes can be derived by dynamic modes as well. The proposed method can distinguish the dynamic characteristics between the Kelvin wake and sea background. Then the corresponding modes of the Kelvin wake can be successfully identified. The proposed method is demonstrated by analyzing a 2D sea surface where the Kelvin ship wake is superposed. It is found that our new approach provides an effective and accurate ship detection, even in the case of high sea states. Meanwhile, the extracted mode of the wake shows the ship position clearly with very high resolution.

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Section: Introductionmentioning

confidence: 99%

A Novel Data-Driven Scheme for the Ship Wake Identification on the 2-D Dynamic Sea Surface

Zhang

Jiang

2020

IEEE Access

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“…Zhang et al used the space relation characteristics of ships to detection targets [6]. It has been shown that ship wakes can help detect ships and also provide useful information about heading and velocity [7]- [10]. However, ship wake detection is influenced by various factors, such as radar frequency, angle of view and angle of incidence and sea state.…”

Section: A Review Of Ship Detection In Polsar Imagerymentioning

confidence: 99%

“…where   tr  is the trace operator and L as the number of looks. When speckle is fully developed as mentioned in section A, z obeys a Gamma distribution after a series of mathematical deduction [33][34]: 1 ( , ) Ld z L  (7) where ( , )    denotes a Gamma distribution with shape parameter  and scale parameter  . ( , )    can be represented as follows [39]…”

Section: B Statistics Of the Mpwfmentioning

confidence: 99%

Robust CFAR Detector Based on Truncated Statistics for Polarimetric Synthetic Aperture Radar

Liu

Yang

Marino

et al. 2020

IEEE Trans. Geosci. Remote Sensing

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Constant false alarm rate (CFAR) algorithms using local training window are widely used for ship detection with synthetic aperture radar (SAR) imagery. However, when the density of targets is high, such as in busy shipping lines and crowded harbors, the background statistics may be contaminated by the presence of nearby targets in the training window. Recently a robust CFAR detector based on truncated statistics (TS) was proposed. However, the truncation of data in the format of polarimetric covariance matrices is much more complicated with respect to the truncation of intensity (single polarization) data. In this paper a polarimetric truncated statistic CFAR (PWF-TS-CFAR) is proposed to estimate the background parameters accurately in the contaminated sea clutter for Pol SAR imagery. The CFAR detector uses polarimetric whitening filter (PWF) to turn the multidimensional problem to a one dimensional case. It uses the truncation to exclude possible statistically interfering outliers and uses TS to model the remaining background samples. The algorithm does not require a prior knowledge of the interfering targets and it is performed iteratively and adaptively to derive better estimates of the polarimetric covariance matrix (although this is computationally expensive). The PWF-TS-CFAR detector provides accurate background clutter modeling, a stable false alarm property, and improves detection performance in high-target-density situations. RadarSat2 data are used to verify our derivations and the results are in line with the theory.

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“…P. Imbo et al [13] described two methods for wake-shape detection in PolSAR imagery: the first one reduced the dimension of the scattering matrix using the PWF filter, which can improve the contrast between ships and sea clutter in the background; the second one utilized the covariance matrix in the Radon domain. Z. Xu et al [14] introduced a novel two-step (coarse and fine processing) detector to detect the faint turbulent wake in PolSAR imagery. Based on the polarization decomposition theory, a new parameter called surface scattering randomness was proposed to enhance the contrast between wake and sea.…”

Section: Introductionmentioning

confidence: 99%

Pre-Processing of Simulated Synthetic Aperture Radar Image Scenes Using Polarimetric Enhancement for Improved Ship Wake Detection

Jiang,

Yang,

et al. 2024

Remote Sensing

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Ship wake detection using synthetic aperture radar (SAR) imagery provides a way to obtain small marine ship information, but it often becomes unavailable and unreliable during a high sea state. Polarimetric information provides a potential way to solve this problem, which can enhance the ship target as well as the ship wake features. However, three challenges still exist in ship wake detection in polarimetric SAR imagery: the unwanted influences of bright and singular points on ship wake detection, the lack of performance analysis of wake detection by new-type polarimetric enhancement methods, and the difficulty of using the assessment criteria for ship wake detection. In this paper, we try to solve the above problems. Firstly, fully polarized SAR imagery of both ship turbulent and Kelvin wake is simulated based on the two-scale composite model, and the Polarimetric Whitening Filter (PWF) and Polarimetric Detection Optimization Filter (PDOF) are applied to the simulated fully polarized SAR imagery to enhance the ship wake features. Secondly, since the bright and singular points resulting from the ship echoes and the polarimetric enhancement methods may lead to misdetections, a logarithm process and z-score normalization pre-processing has been applied to the images. Then, a new assessment criterion for wake detection performance has been formulated, and the probability of missing detections (PMDs) and the probability of false alarms (PFAs) have been defined for two different requirements. And a Radon transform-based ship wake detection method for both ship turbulence and Kelvin wake has been carried out in horizontal–horizontal (HH), vertical–vertical (VV), horizontal–vertical (HV), PWF and PDOF SAR imagery. Finally, an analysis of the wake detection performance has been carried out. The PWF and PDOF can improve the wake detection performance by an average of nearly 50 percent compared with the HH and VV.

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Faint Ship Wake Detection in PolSAR Images

Cited by 12 publications

References 21 publications

A Novel Data-Driven Scheme for the Ship Wake Identification on the 2-D Dynamic Sea Surface

A Novel Data-Driven Scheme for the Ship Wake Identification on the 2-D Dynamic Sea Surface

Robust CFAR Detector Based on Truncated Statistics for Polarimetric Synthetic Aperture Radar

Pre-Processing of Simulated Synthetic Aperture Radar Image Scenes Using Polarimetric Enhancement for Improved Ship Wake Detection

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