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

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

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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

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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.