A new PolSAR ship detection metric fused by polarimetric similarity and the third eigenvalue of the coherency matrix

Xi, Yuyang; Zhang, Xi; Lai, Quan; Li, Wei; Lang, Haitao

doi:10.1109/igarss.2016.7729019

Cited by 6 publications

(3 citation statements)

References 10 publications

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“…Several similar metrics were also proposed for ship detection [ 23 , 24 , 25 ]. However, they are based on the same reasonable assumption that the ship is dominated by even-bounce scattering and line bounce scattering in fully polarimetric (FP) SAR images, while the sea is dominated by odd-bounce scattering [ 23 , 24 ].…”

Section: Resultsmentioning

confidence: 99%

“…However, they are based on the same reasonable assumption that the ship is dominated by even-bounce scattering and line bounce scattering in fully polarimetric (FP) SAR images, while the sea is dominated by odd-bounce scattering [ 23 , 24 ]. Thus, those metrics select some certain decomposed polarimetric parameters to achieve excellent performance [ 25 ]. However, intensity oscillating with the change of aspect angle is the main characteristic of vehicle backscattering.…”

Section: Resultsmentioning

confidence: 99%

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Detectability Analysis of Road Vehicles in Radarsat-2 Fully Polarimetric SAR Images for Traffic Monitoring

Zhang

Wang

Zhang

et al. 2017

Sensors

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By acquiring information over a wide area regardless of weather conditions and solar illumination, space-borne Synthetic Aperture Radar (SAR) has the potential to be a promising application for traffic monitoring. However, the backscatter character of a vehicle in a SAR image is unstable and varies with image parameters, such as aspect and incidence angle. To investigate vehicle detectability in SAR images for traffic monitoring applications, images of four common types of vehicles in China were acquired using the fully polarimetric (FP) SAR of Radarsat-2 in our experiments. Methods for measuring a vehicle's aspect angle and backscatter intensity are introduced. The experimental FP SAR images are used to analyze the detectability, which is affected by factors such as vehicle size, vehicle shape, and aspect angle. Moreover, a new metric to improve vehicle detectability in FP SAR images is proposed and compared with the well-known intensity metric. The experimental results show that shape is a crucial factor in affecting the backscatter intensity of vehicles, which also oscillates with varying aspect angle. If the size of a vehicle is smaller than the SAR image resolution, using the intensity metric would result in low detectability. However, it could be improved in an FP SAR image by using the proposed metric. Compared with the intensity metric, the overall detectability is improved from 72% to 90% in our experiments. Therefore, this study indicates that FP SAR images have the ability to detect stationary vehicles on the road and are meaningful for traffic monitoring.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Detectability Analysis of Road Vehicles in Radarsat-2 Fully Polarimetric SAR Images for Traffic Monitoring

Zhang

Wang

Zhang

et al. 2017

Sensors

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“…In the literature [14], Robust Principal Component Analysis (RPCA) was used for the first time to transform the ship target detection problem into a low-rank and sparse matrix decomposition problem. (3) Ship detection methods based on polarization characteristics [15][16][17]. The difference in scattering mechanism between the ship target and sea clutter is utilized to distinguish the target from the background [18,19].…”

Section: Introductionmentioning

confidence: 99%

A Novel Method for SAR Ship Detection Based on Eigensubspace Projection

Shu

Chang

et al. 2022

Remote Sensing

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Synthetic Aperture Radar (SAR) is a high-resolution radar that operates all day and in all weather conditions, so it has been widely used in various fields of science and technology. Ship detection using SAR images has become important research in marine applications. However, in complex scenes, ships are easily submerged in sea clutter, which cause missed detection. Due to this, strong sidelobes in SAR images generate false targets and reduce the detection accuracy. To solve these problems, a ship detection method based on eigensubspace projection (ESSP) in SAR images is proposed. First, the image is reconstructed into a new observation matrix along the azimuth direction, and the phase space matrix of the reconstructed image is constructed by using the Hankel characteristic, which preliminarily determines the approximate position of the ship. Then, the autocorrelation matrix of the reconstructed image is decomposed by eigenvalue decomposition (EVD). According to the size of the eigenvalues, the corresponding eigenvectors are divided into two parts, which constitute the basis of the ship subspace and the clutter subspace. Finally, the original image is projected into the ship subspace, and the ship data in the ship subspace are rearranged to obtain the precise position of the ship with significantly suppressed clutter. To verify the effectiveness of the proposed method, the ESSP method is compared with other detection methods on four images at different sea conditions. The results show that the detection accuracy of the ESSP method reaches 89.87% in complex scenes. Compared with other methods, the proposed method can extract ship targets from sea clutter more accurately and reduce the number of false alarms, which has obvious advantages in terms of detection accuracy and timeliness.

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Saliency detection of targets in polarimetric SAR images based on globally weighted perturbation filters

Yang

Cao

Cui

et al. 2019

ISPRS Journal of Photogrammetry and Remote Sensing

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A new PolSAR ship detection metric fused by polarimetric similarity and the third eigenvalue of the coherency matrix

Cited by 6 publications

References 10 publications

Detectability Analysis of Road Vehicles in Radarsat-2 Fully Polarimetric SAR Images for Traffic Monitoring

Detectability Analysis of Road Vehicles in Radarsat-2 Fully Polarimetric SAR Images for Traffic Monitoring

A Novel Method for SAR Ship Detection Based on Eigensubspace Projection

Saliency detection of targets in polarimetric SAR images based on globally weighted perturbation filters

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