Region Based Target Detection Approach for Synthetic Aperture Radar Images and Its Parallel Implementation

Date

2012-04-26

Author

Nar, Fatih
Demirkesen, Can
Okman, O. Erman
ÇETİN, MÜJDAT

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

182
views

0
downloads

Automatic target detection (ATD) methods for synthetic aperture radar (SAR) imagery are sensitive to image resolution, target size, clutter complexity, and speckle noise level. However, a robust ATD method needs to be less sensitive to the above factors. In this study, a constant false alarm rate (CFAR) based method is proposed which can perform target detection independent of image resolution and target size even in heterogeneous background clutter. The proposed method is computationally efficient since clutter statistics are calculated only for candidate target regions and a single execution of the method is sufficient for different types of targets having different shapes and sizes. Computational efficiency is further increased by parallelizing the algorithm using OpenMP and NVidia CUDA implementations.

Subject Keywords

Automatic target detection, CFAR, SAR, GPU implementation

URI

https://hdl.handle.net/11511/67349

DOI

https://doi.org/10.1117/12.921083

Collections

Department of Electrical and Electronics Engineering, Conference / Seminar

Suggestions

OpenMETU
Core

Radar target detection in non-gaussian clutter Doyuran, Ülkü; Tanık, Yalçın; Department of Electrical and Electronics Engineering (2007) In this study, novel methods for high-resolution radar target detection in non-Gaussian clutter environment are proposed. In solution of the problem, two approaches are used: Non-coherent detection that operates on the envelope-detected signal for thresholding and coherent detection that performs clutter suppression, Doppler processing and thresholding at the same time. The proposed non-coherent detectors, which are designed to operate in non-Gaussian and range-heterogeneous clutter, yield higher performanc...
Ship detection in synthetic aperture radar (SAR) images by deep learning Ayhan, Oner; Sen, Nigar (2019-01-01) In this paper, we propose a Convolutional Neural Network (CNN) based method to detect ships in Synthetic Aperture Radar (SAR) images. The architecture of proposed CNN has customized parts to detect small targets. In order to train, validate and test the CNN, TerraSAR-X Spot mode images are used. In the phase of data preparation, a GIS (Geographic Information System) specialist labels ships manually in all images. Later, image patches that contain ships are cropped and ground truths are also obtained from pr...
Expectation Maximization-Based Detection in Range-Heterogeneous Weibull Clutter Doyuran, Ulku Cilek; Tanık, Yalçın (2014-10-01) The problem of radar target detection in Weibull and range-heterogeneous clutter is considered. The clutter component in each range cell is modeled as an instance of a random variable belonging to one of several Weibull distributions. We use the expectation-maximization algorithm to estimate parameters of the distribution and set the threshold accordingly. The performance of the proposed receiver is investigated through computer simulations and observed to be superior compared with numerous well-known methods.
Information Theoretic SAR Boundary Detection with User Interaction Demirkesen, Can; Leloğlu, Uğur Murat (2015-09-24) Detection of region boundaries is a very challenging task especially in the presence of noise or speckle as in synthetic aperture radar images. In this work, we propose a user interaction based boundary detection technique which makes use of B-splines and well-known powerful tools of information theory such as the Kullback-Leibler divergence (KLD) and Bhattacharyya distance. The proposed architecture consists of the following four main steps: (1) The user selects points inside and outside of a region. (2) P...
Airport runway detection in satellite images by Adaboost Learning ZÖNGÜR, Ugur; Halıcı, Uğur; AYTEKİN, Orsan; Ulusoy, İlkay (2009-09-03) Advances in hardware and pattern recognition techniques, along with the widespread utilization of remote sensing satellites, have urged the development of automatic target detection systems in satellite images. Automatic detection of airports is particularly essential, due to the strategic importance of these targets. In this paper, a runway detection method using a segmentation process based on textural properties is proposed for the detection of airport runways, which is the most distinguishing element of...

Citation Formats

F. Nar, C. Demirkesen, O. E. Okman, and M. ÇETİN, “Region Based Target Detection Approach for Synthetic Aperture Radar Images and Its Parallel Implementation,” 2012, vol. 8394, p. 0, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/67349.