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Implementation of a fast method for reconstruction of ISAR images
Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, The Institute of Technology.
2003 (English)Independent thesis Basic level (professional degree), 20 credits / 30 HE creditsStudent thesisAlternative title
Implementation av en snabb metod för rekonstruktion av ISAR-bilder (Swedish)
Abstract [en]

By analyzing ISAR images, the characteristics of military platforms with respect to radar visibility can be evaluated. The method, which is based on the Discrete-Time Fourier Transform (DTFT), that is currently used to calculate the ISAR images requires large computations efforts. This thesis investigates the possibility to replace the DTFT with the Fast Fourier Transform (FFT). Such a replacement is not trivial since the DTFT is able to compute a contribution anywhere along the spatial axis while the FFT delivers output data at fixed sampling, which requires subsequent interpolation. The interpolation leads to a difference in the ISAR image compared to the ISAR image obtained by DTFT. On the other hand, the FFT is much faster. In this quality-and-time trade-off, the objective is to minimize the error while keeping high computational efficiency.

The FFT-approach is evaluated by studying execution time and image error when generating ISAR images for an aircraft model in a controlled environment. The FFT method shows good results. The execution speed is increased significantly without any visible differences in the ISAR images. The speed-up- factor depends on different parameters: image size, degree of zero-padding when calculating the FFT and the number of frequencies in the input data.

Place, publisher, year, edition, pages
Institutionen för systemteknik , 2003. , 67 p.
LiTH-ISY-Ex, 3437
Keyword [en]
Technology, radar, RCS, radar cross section, ISAR, image reconstruction, algorithm, FFT
Keyword [sv]
National Category
Engineering and Technology
URN: urn:nbn:se:liu:diva-2073OAI: diva2:19402
Subject / course
Computer Vision Laboratory
Available from: 2003-12-16 Created: 2003-12-16 Last updated: 2012-07-02

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