General Polarimetric Model-Based Decomposition for Coherency Matrix

The detection of small fishing ships is very important for maritime fishery supervision. However, it is difficult to detect small ships using synthetic aperture radar (SAR), due to the weak target scattering and very small number of pixels. Polarimetric synthetic aperture radar (PolSAR) has been widely used in maritime ship detection due to its abundant target scattering information. In the present paper, a new ship detector, named ΛM, is developed based on the analysis of polarization scattering differences between ship and sea, then combined with the two-parameter constant false alarm rate method (TP-CFAR) algorithm to conduct ship detection. The goals of the detector construction are to fully consider the ship’s depolarization effect, and further amplify it through sliding window processing. First, the signal-to-clutter ratio (SCR) enhancement performance of ΛM for ships with different lengths ranging from 8 to 230 m under 90 different combinations of windows are analyzed in detail using three set of RADARSAT-2 quad-polarization data, then the appropriate window size is determined. In addition, the SCR enlargement between ΛM and some typical polarization features is compared. Among these, for ships of length greater than 35 m, the average contrast of ΛM is 33.7 dB, which is 20 dB greater than that of the HV channel. For small vessels of length less than 16 m, the average contrast of ΛM is 16 dB higher than that of HV channel on average. Finally, the RADARSAT-2 data including nonmetallic small vessels are used to perform ship detection tests, and the detection ability for conventional and small ships of some classic algorithms are compared and analyzed. For large vessels of length greater than 35 m, the method proposed in this paper is able to obtain a superior detection result, maintain the ship contour well, and suppress false alarms caused by the cross side lobe in the SAR image. For small vessels of length less than 16 m, the method proposed in this paper can reduce the number of missed targets, while also obtaining superior detection results, especially for small nonmetallic vessels.

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“…On the basis of the S matrix, its second-order statistical characteristics coherency matrix T is then further extracted [27,30]:…”

Section: Target Detection Methods Based On Scattering Difference For Pmentioning

confidence: 99%

A Small Ship Target Detection Method Based on Polarimetric SAR

2019

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“…Specifically, the maximum difference between the elements is only ±1/15 [21]. However, in real OOB landforms, cross-polarization power is found to be more intense than co-polarization power [4][5][6][7]. In this case, we incorporate the refined OOB descriptor C OOB and propose the scattering model of an OOB as follows…”

Section: Oob Scattering Modelmentioning

confidence: 99%

“…Despite all of this, outputs from the MBDs are sometimes confusing when discrimination between obliquely oriented buildings (OOBs) and natural areas is made. For an OOB whose main scattering center is at an oblique direction with respect to the radar illumination (its orientation angular domain approximately ranges between 22.5 • and 45 • (or between −45 • and −22.5 • ) [4]), intense cross-polarization powers instead of co-polarization powers will be induced [4][5][6][7]. Simultaneously, there also exist significant cross-polarization responses in natural areas.…”

Section: Introductionmentioning

confidence: 99%

Scattering Characterization of Obliquely Oriented Buildings from PolSAR Data Using Eigenvalue-Related Model

Quan

Xiong

Xiang³

et al. 2019

Remote Sensing

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Scattering characterization of obliquely oriented buildings (OOBs) from polarimetric synthetic aperture radar (PolSAR) data is challenging since the general double-bounce scattering does not support their dominant scattering mechanism. In this paper, a physical scattering model combining the eigenvalues of coherency matrix is proposed to characterize the scattering of OOBs. The coherency matrix is first operated by eigenvalue decomposition and a refined OOB descriptor is presented based on these eigenvalues. Considering the actual proportions of co-polarization and cross-polarization components, the descriptor is then adopted to modify the matrix elements of the well-known cross scattering model, thus introducing the OOB scattering model. Finally, strategies of model parameter solution are designed and the involved decomposition is complete accordingly. The proposed method is tested on spaceborne and airborne PolSAR data and the results confirm its effectiveness, which clearly call for further research and application.

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“…It is apparent that the quadratic discriminants in (16) are always positive; there are two roots for the quadratic equation. Accordingly, there are three possible solutions: (1) if the larger root is negative, f S (or f D ) is forced to zero; (2) if the larger root is positive and the smaller root is negative, f S (or f D ) is equal to the larger root; and (3) if the smaller root is positive, f S (or f D ) still equals the larger root.…”

Section: Model Solutionmentioning

confidence: 99%

“…In the past two decades, most of the MBD methods have been developed on the basis of the F3D and Y4D methods. Part of these methods adopted the mathematical operations, i.e., non-negative eigenvalue decomposition (NNED) [12][13][14] and orientation angle compensation (OAC) [15][16][17][18][19], for the input coherency matrix to estimate the scattering contributions in order to pursue an accurate scattering interpretation in a mathematical manner. Despite this, researches are more inclined to introduce sophisticated scattering models to develop and improve the MBD in a physical manner.…”

Section: Introductionmentioning

confidence: 99%

Seven-Component Model-Based Decomposition for PolSAR Data with Sophisticated Scattering Models

et al. 2019

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Due to incomprehensive and inaccurate scattering modeling, the state-of-the-art polarimetric synthetic aperture radar (PolSAR) model-based target decompositions are incapable of effectively depicting the scattering mechanism of obliquely oriented urban areas. In this paper, a seven-component model-based decomposition scheme is proposed by constructing several sophisticated scattering models. First, an eigenvalue-based obliquely-oriented dihedral scattering model is presented to reasonably distribute the co-polarization and cross-polarization scattering powers in obliquely oriented urban areas, thus accurately characterizing the urban scattering. Second, the ±45° oriented dipole and ±45° quarter-wave reflector scattering models are incorporated for the purpose of accounting for the real and imaginary components of the T 13 element in the coherency matrix so as to fully utilize polarimetric information. Finally, according to their mathematical forms, several strategies for model parameter solutions are designed, and the seven-component decomposition is fulfilled. Experimental results conducted on different PolSAR data demonstrate that the proposed method considerably improves the PolSAR scattering interpretation in a more physical manner compared to other existing model-based decomposition, which can be applied for urban area detection, classification, and other urban planning applications.

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General Polarimetric Model-Based Decomposition for Coherency Matrix

Cited by 163 publications

References 45 publications

A Small Ship Target Detection Method Based on Polarimetric SAR

A Small Ship Target Detection Method Based on Polarimetric SAR

Scattering Characterization of Obliquely Oriented Buildings from PolSAR Data Using Eigenvalue-Related Model

Seven-Component Model-Based Decomposition for PolSAR Data with Sophisticated Scattering Models

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