A Small Ship Target Detection Method Based on Polarimetric SAR

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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An Improved Method of Land Masking for Synthetic Aperture Radar-based Ship Detection

Journal of Navigation ◽

10.1017/s037346331800005x ◽

2018 ◽

Vol 71 (4) ◽

pp. 788-804 ◽

Cited By ~ 3

Author(s):

Chan-Su Yang ◽

Ju-Han Park ◽

Ahmed Harun-Al Rashid

Keyword(s):

Synthetic Aperture Radar ◽

Coastal Waters ◽

Detection Algorithm ◽

Synthetic Aperture ◽

False Alarms ◽

Sar Images ◽

Ship Detection ◽

X Band ◽

Merging Process ◽

Aperture Radar

Land masking of Synthetic Aperture Radar (SAR) images is generally accomplished by applying either archived shoreline databases or image segmentation. However, those methods cannot be solely applied to geographical areas complicated with many small islands and exposed rocks. Therefore, we have proposed a new procedure where Sobel edge extraction is applied to detect the edges of all objects from KOMPSAT-5 X-band SAR images, followed by a merging process with the edges from the land objects based on Electronic Navigational Chart (ENC) coastlines. Using the land mask data, geometrically corrected SAR images were masked before applying a ship detection algorithm. This land masking procedure was applied to several images covering different areas of the Korean Peninsula. The results show that land targets such as newly constructed and natural objects were also masked, and thus did not create false alarms during ship detection. Therefore, this method can be used to assist precise ship detection using SAR images in coastal waters.

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Realizing Target Detection in SAR Images Based on Multiscale Superpixel Fusion

Sensors ◽

10.3390/s21051643 ◽

2021 ◽

Vol 21 (5) ◽

pp. 1643

Author(s):

Ming Liu ◽

Shichao Chen ◽

Fugang Lu ◽

Mengdao Xing ◽

Jingbiao Wei

Keyword(s):

Synthetic Aperture Radar ◽

False Alarm ◽

False Alarm Rate ◽

Target Detection ◽

Synthetic Aperture ◽

False Alarms ◽

Sar Image ◽

Constant False Alarm Rate ◽

Sar Images ◽

Complex Scenes

For target detection in complex scenes of synthetic aperture radar (SAR) images, the false alarms in the land areas are hard to eliminate, especially for the ones near the coastline. Focusing on the problem, an algorithm based on the fusion of multiscale superpixel segmentations is proposed in this paper. Firstly, the SAR images are partitioned by using different scales of superpixel segmentation. For the superpixels in each scale, the land-sea segmentation is achieved by judging their statistical properties. Then, the land-sea segmentation results obtained in each scale are combined with the result of the constant false alarm rate (CFAR) detector to eliminate the false alarms located on the land areas of the SAR image. In the end, to enhance the robustness of the proposed algorithm, the detection results obtained in different scales are fused together to realize the final target detection. Experimental results on real SAR images have verified the effectiveness of the proposed algorithm.

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Comparison of Target Detectors to Identify Icebergs in Quad-Polarimetric L-Band Synthetic Aperture Radar Data

Remote Sensing ◽

10.3390/rs13091753 ◽

2021 ◽

Vol 13 (9) ◽

pp. 1753

Author(s):

Johnson Bailey ◽

Armando Marino ◽

Vahid Akbari

Keyword(s):

Sea Ice ◽

Synthetic Aperture Radar ◽

Roc Curves ◽

Radar Data ◽

Open Ocean ◽

Synthetic Aperture ◽

False Alarms ◽

Synthetic Aperture Radar Data ◽

Whitening Filter ◽

Aperture Radar

Icebergs represent hazards to ships and maritime activities and therefore their detection is essential. Synthetic Aperture Radar (SAR) satellites are very useful for this, due to their capability to acquire data under cloud cover and during day and night passes. In this work, we compared six state-of-the-art polarimetric target detectors to test their performance and ability to detect small-sized icebergs <120 m in four locations in Greenland. We used four single-look complex (SLC) ALOS-2 quad-polarimetric images from JAXA for quad-polarimetric detection and we compared with dual-polarimetric detectors using only the channels HH and HV. We also compared these detectors with single-polarimetric intensity channels and we tested using two scenarios: open ocean and sea ice. Our results show that the multi-look polarimetric whitening filter (MPWF) and the optimal polarimetric detector (OPD) provide the most optimal performance in quad- and dual-polarimetric mode detection. The analysis shows that, overall, quad-polarimetric detectors provide the best detection performance. When the false alarm rate (PF) is fixed to 10-5, the probabilities of detection (PD) are 0.99 in open ocean and 0.90 in sea ice. Dual-polarimetric or single-polarimetric detectors show an overall reduction in performance (the ROC curves show a decrease), but this degradation is not very large (<0.1) when the value of false alarms is relatively high (i.e., we are interested in bigger icebergs with a brighter backscattering >120 m, as they are easier to detect). However, the differences between quad- and dual- or single-polarimetric detectors became much more evident when the PF value was fixed to low detection probabilities 10-6 (i.e., smaller icebergs). In the single-polarimetric mode, the HV channel showed PD values of 0.62 for open ocean and 0.26 for sea ice, compared to values of 0.81 (open ocean) and 0.77 (sea ice) obtained with quad-polarimetric detectors.

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Constant false alarm rate detection of slow targets in polarimetric along‐track interferometric synthetic aperture radar imagery

IET Radar Sonar & Navigation ◽

10.1049/iet-rsn.2018.5082 ◽

2019 ◽

Vol 13 (1) ◽

pp. 31-44 ◽

Cited By ~ 1

Author(s):

Zhang Peng ◽

Zhang Jia‐Feng ◽

Liu Tao

Keyword(s):

Synthetic Aperture Radar ◽

False Alarm ◽

False Alarm Rate ◽

Synthetic Aperture ◽

Interferometric Synthetic Aperture Radar ◽

Constant False Alarm Rate ◽

Radar Imagery ◽

Synthetic Aperture Radar Imagery ◽

Along Track ◽

Aperture Radar

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FISHING-VESSEL DETECTION USING SYNTHETIC APERTURE RADAR (SAR) SENTINEL-1 (CASE STUDY: JAVA SEA)

International Journal of Remote Sensing and Earth Sciences (IJReSES) ◽

10.30536/j.ijreses.2019.v16.a3235 ◽

2020 ◽

Vol 16 (2) ◽

pp. 131

Author(s):

Sarah Putri Fitriani ◽

Jonson Lumban Gaol ◽

Dony Kushardono

Keyword(s):

Synthetic Aperture Radar ◽

Object Identification ◽

Synthetic Aperture ◽

Overlay Analysis ◽

Constant False Alarm Rate ◽

Fishing Vessel ◽

Fishing Vessels ◽

Sensing Technology ◽

Vessel Detection ◽

Aperture Radar

The synthetic aperture radar (SAR) instrument of Sentinel-1 is a remote sensing technology being developed to enable the detection of vessel distribution. The purpose of this research is to study fishing-vessel detection using SAR Sentinel-1 data. In this study, the constant false alarm rate method (CFAR) for Sentinel-1 data is used for the detection of fishing vessels in Indramayu sea waters. The data used to detect ships includes SAR Sentinel-1A images and vessel monitoring system (VMS) data acquired on 8 March and 20 March 2018. SAR Sentinel-1 imagery data is obtained through pre-processing and object identification using Sentinel Application Platform (SNAP) software. Overlay analysis is then used to enable discrimination of immovable and movable objects and validation of ships detected from SAR Sentinel-1 imagery is performed using VMS data. From overlay analysis, 46 ships were detected on 8 March 2018 and 39 ships on 20 March 2018. Of all the ship points detected using SAR Sentinel-1, 7.06% could be detected by VMS data while 92.94% could not. The number of ships detected by SAR Sentinel-1 is greater than those detected by VMS because not all ships use VMS devices.

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