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Conventional radar imaging systems use Fourier transform for image formation, but due to the target's complicated motion the Doppler spectrum is time-varying and thus the reconstructed image becomes blurred even after applying standard motion compensation algorithms. Therefore, sophisticated algorithms such as polar reformatting are usually employed to produce clear images. Alternatively, Joint Time-Frequency (JTF) analysis can be used for image formation which produces clear image without using polar reformatting algorithm. In this paper, a new JTF-based method is proposed for image formation in inverse synthetic aperture radars (ISAR). This method uses minimum entropy criterion for optimum parameter adjustment of JTF algorithms. Short Time Fourier Transform (STFT) and Fractional Fourier Transform (FrFT) are applied as JTF for time-varying Doppler spectrum analysis. Both the width of Gaussian window of STFT and the order of FrFT, α, are adjusted using minimum entropy as local and total measures. Furthermore, a new statistical parameter, called normalized correlation, is defined for comparison of images reconstructed by different methods. Simulation results show that α-order FrFT with local adjustment has much better performance than the other methods in this category even in low SNR.

- Publication
- IEICE TRANSACTIONS on Communications Vol.E92-B No.8 pp.2714-2722

- Publication Date
- 2009/08/01

- Publicized

- Online ISSN
- 1745-1345

- DOI
- 10.1587/transcom.E92.B.2714

- Type of Manuscript
- PAPER

- Category
- Sensing

The copyright of the original papers published on this site belongs to IEICE. Unauthorized use of the original or translated papers is prohibited. See IEICE Provisions on Copyright for details.

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Mohammad Mahdi NAGHSH, Mahmood MODARRES-HASHEMI, "ISAR Image Formation Based on Minimum Entropy Criterion and Fractional Fourier Transform" in IEICE TRANSACTIONS on Communications,
vol. E92-B, no. 8, pp. 2714-2722, August 2009, doi: 10.1587/transcom.E92.B.2714.

Abstract: Conventional radar imaging systems use Fourier transform for image formation, but due to the target's complicated motion the Doppler spectrum is time-varying and thus the reconstructed image becomes blurred even after applying standard motion compensation algorithms. Therefore, sophisticated algorithms such as polar reformatting are usually employed to produce clear images. Alternatively, Joint Time-Frequency (JTF) analysis can be used for image formation which produces clear image without using polar reformatting algorithm. In this paper, a new JTF-based method is proposed for image formation in inverse synthetic aperture radars (ISAR). This method uses minimum entropy criterion for optimum parameter adjustment of JTF algorithms. Short Time Fourier Transform (STFT) and Fractional Fourier Transform (FrFT) are applied as JTF for time-varying Doppler spectrum analysis. Both the width of Gaussian window of STFT and the order of FrFT, α, are adjusted using minimum entropy as local and total measures. Furthermore, a new statistical parameter, called normalized correlation, is defined for comparison of images reconstructed by different methods. Simulation results show that α-order FrFT with local adjustment has much better performance than the other methods in this category even in low SNR.

URL: https://global.ieice.org/en_transactions/communications/10.1587/transcom.E92.B.2714/_p

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@ARTICLE{e92-b_8_2714,

author={Mohammad Mahdi NAGHSH, Mahmood MODARRES-HASHEMI, },

journal={IEICE TRANSACTIONS on Communications},

title={ISAR Image Formation Based on Minimum Entropy Criterion and Fractional Fourier Transform},

year={2009},

volume={E92-B},

number={8},

pages={2714-2722},

abstract={Conventional radar imaging systems use Fourier transform for image formation, but due to the target's complicated motion the Doppler spectrum is time-varying and thus the reconstructed image becomes blurred even after applying standard motion compensation algorithms. Therefore, sophisticated algorithms such as polar reformatting are usually employed to produce clear images. Alternatively, Joint Time-Frequency (JTF) analysis can be used for image formation which produces clear image without using polar reformatting algorithm. In this paper, a new JTF-based method is proposed for image formation in inverse synthetic aperture radars (ISAR). This method uses minimum entropy criterion for optimum parameter adjustment of JTF algorithms. Short Time Fourier Transform (STFT) and Fractional Fourier Transform (FrFT) are applied as JTF for time-varying Doppler spectrum analysis. Both the width of Gaussian window of STFT and the order of FrFT, α, are adjusted using minimum entropy as local and total measures. Furthermore, a new statistical parameter, called normalized correlation, is defined for comparison of images reconstructed by different methods. Simulation results show that α-order FrFT with local adjustment has much better performance than the other methods in this category even in low SNR.},

keywords={},

doi={10.1587/transcom.E92.B.2714},

ISSN={1745-1345},

month={August},}

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TY - JOUR

TI - ISAR Image Formation Based on Minimum Entropy Criterion and Fractional Fourier Transform

T2 - IEICE TRANSACTIONS on Communications

SP - 2714

EP - 2722

AU - Mohammad Mahdi NAGHSH

AU - Mahmood MODARRES-HASHEMI

PY - 2009

DO - 10.1587/transcom.E92.B.2714

JO - IEICE TRANSACTIONS on Communications

SN - 1745-1345

VL - E92-B

IS - 8

JA - IEICE TRANSACTIONS on Communications

Y1 - August 2009

AB - Conventional radar imaging systems use Fourier transform for image formation, but due to the target's complicated motion the Doppler spectrum is time-varying and thus the reconstructed image becomes blurred even after applying standard motion compensation algorithms. Therefore, sophisticated algorithms such as polar reformatting are usually employed to produce clear images. Alternatively, Joint Time-Frequency (JTF) analysis can be used for image formation which produces clear image without using polar reformatting algorithm. In this paper, a new JTF-based method is proposed for image formation in inverse synthetic aperture radars (ISAR). This method uses minimum entropy criterion for optimum parameter adjustment of JTF algorithms. Short Time Fourier Transform (STFT) and Fractional Fourier Transform (FrFT) are applied as JTF for time-varying Doppler spectrum analysis. Both the width of Gaussian window of STFT and the order of FrFT, α, are adjusted using minimum entropy as local and total measures. Furthermore, a new statistical parameter, called normalized correlation, is defined for comparison of images reconstructed by different methods. Simulation results show that α-order FrFT with local adjustment has much better performance than the other methods in this category even in low SNR.

ER -