Spiky sea clutter and constant false alarm rate processing in high-resolution maritime radar systems

2012 ◽  
Author(s):  
Mohamed A. Abdel-Nabi ◽  
Karim G. Seddik ◽  
El-Sayed A. El-Badawy
Keyword(s):  
High Resolution ◽  
False Alarm ◽  
False Alarm Rate ◽  
Constant False Alarm Rate ◽  
Sea Clutter ◽  
Radar Systems

Erratum

1993 ◽  
Vol 46 (3) ◽  
pp. 447-447
Keyword(s):  
False Alarm ◽  
False Alarm Rate ◽  
Constant False Alarm Rate ◽  
Sea Clutter ◽  
Signal Differentiation ◽  
Signal Vidéo ◽  
Video Amplifier ◽  
Marine Navigation ◽  
Adaptive Signal

There was an error in Mr Richard Trim's paper, ‘Some causes of problems in the observation of standard racon marine beacons when observed by means of standard marine navigation radars’, which was published in the May 1993 issue of the Journal of Navigation. Section 3, paragraph 4 of page 276 should read:‘A third and very important cause of radar received-signal differentiation arises if a widely used form of automatic anti-sea-clutter processing is employed, since part of this processing is to differentiate the radar-received video so as to remove the d.c. term in the sea clutter echoes as part of the Constant False Alarm Rate (CFAR) processing. When such automatic sea clutter supression facilities are in operation, the gain level applied to the radar receiver video amplifier has an adaptive signal superimposed upon it which, while slow acting, generally follows the shape of the clutter returns on the received signal video, while being largely unaffected by the wanted echo returns such as those from ships, navigation marks, coastlines, etc. This effect may be reduced in the case of the very latest radar designs’.

scholarly journals AN ADAPTIVE SHIP DETECTION ALGORITHM FOR HRWS SAR IMAGES UNDER COMPLEX BACKGROUND: APPLICATION TO SENTINEL1A DATA

2018 ◽  
Vol XLII-3 ◽  
pp. 497-503
Author(s):  
G. He ◽  
Z. Xia ◽  
H. Chen ◽  
K. Li ◽  
Z. Zhao ◽  
...  
Keyword(s):  
High Resolution ◽  
False Alarm ◽  
False Alarm Rate ◽  
Texture Features ◽  
Detection Algorithm ◽  
Support Vector ◽  
Constant False Alarm Rate ◽  
Sar Images ◽  
Ship Detection ◽  
Wide Swath

Real-time ship detection using synthetic aperture radar (SAR) plays a vital role in disaster emergency and marine security. Especially the high resolution and wide swath (HRWS) SAR images, provides the advantages of high resolution and wide swath synchronously, significantly promotes the wide area ocean surveillance performance. In this study, a novel method is developed for ship target detection by using the HRWS SAR images. Firstly, an adaptive sliding window is developed to propose the suspected ship target areas, based upon the analysis of SAR backscattering intensity images. Then, backscattering intensity and texture features extracted from the training samples of manually selected ship and non-ship slice images, are used to train a support vector machine (SVM) to classify the proposed ship slice images. The approach is verified by using the Sentinl1A data working in interferometric wide swath mode. The results demonstrate the improvement performance of the proposed method over the constant false alarm rate (CFAR) method, where the classification accuracy improved from 88.5 % to 96.4 % and the false alarm rate mitigated from 11.5 % to 3.6 % compared with CFAR respectively.

A Constant False Alarm Rate-(CFAR) Based Change Detection Approach to Helicopter Diagnostics

2008 ◽  
Author(s):  
Kenneth Ranney ◽  
Hiralal Khatri ◽  
Jerry Silvious ◽  
Kwok Tom ◽  
Romeo del Rosario
Keyword(s):  
Change Detection ◽  
False Alarm ◽  
False Alarm Rate ◽  
Constant False Alarm Rate ◽  
Detection Approach

scholarly journals Realizing Target Detection in SAR Images Based on Multiscale Superpixel Fusion

Sensors ◽  
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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