Fractional Chirp Scaling Algorithm: Mathematical Model

• Published in: IEEE transactions on signal processing Vol. 55; no. 8; pp. 4162 - 4172
• Main Authors: Amein, A.S., Soraghan, J.J.
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.08.2007; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithm design and analysis; Algorithms; Applied sciences; Brain modeling; Chirp; Computer simulation; Exact sciences and technology; Fast Fourier transforms; Focusing; Fourier transforms; fractional Fourier; High resolution; Image analysis; Information, signal and communications theory; Lobes; Mathematical model; Miscellaneous; Radar polarimetry; SAR imaging; Signal processing; Signal to noise ratio; Synthetic aperture radar; Telecommunications and information theory; Lateral lobe; High resolution; Chirp; Fractional Fourier transformation; Fast Fourier transformation; Algorithm; SAR imaging; Algorithm performance; Simulation; fractional Fourier; Airborne radar; Radar imaging; Signal processing; Mathematical model; Synthetic aperture radar; Signal to noise ratio
• ISSN: 1053-587X; 1941-0476
• DOI: 10.1109/TSP.2007.895994

In this paper, the new fractional chirp scaling algorithm (FrCSA) is mathematically derived and analyzed from high-resolution SAR imaging point of view. The FrCSA is based on the use of the fractional Fourier transform within the chirp scaling algorithm (CSA). The performance of the FrCSA is compared to that of the classical CSA that is based on the fast Fourier transform (FFT). Simulation results for airborne SAR systems show that the FrCSA offers enhanced signal-to-noise ratio (SNR), better focusing capabilities, sharpened main lobe with extra power concentration, and greater side-lobe reduction ratio (SLRR) and all of these, without the need for any additional focusing or enhancement techniques that are required in the classical FFT-based CSA.