The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
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The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Os sistemas convencionais de imagem por radar usam a transformada de Fourier para a formação da imagem, mas devido ao movimento complicado do alvo, o espectro Doppler varia no tempo e, portanto, a imagem reconstruída fica borrada mesmo após a aplicação de algoritmos padrão de compensação de movimento. Portanto, algoritmos sofisticados, como a reformatação polar, são geralmente empregados para produzir imagens nítidas. Alternativamente, a análise Joint Time-Frequency (JTF) pode ser usada para formação de imagem que produz imagem nítida sem usar algoritmo de reformatação polar. Neste artigo, um novo método baseado em JTF é proposto para formação de imagens em radares de abertura sintética inversa (ISAR). Este método usa o critério de entropia mínima para ajuste ideal dos parâmetros dos algoritmos JTF. A Transformada de Fourier de Tempo Curto (STFT) e a Transformada de Fourier Fracionária (FrFT) são aplicadas como JTF para análise de espectro Doppler variável no tempo. Tanto a largura da janela gaussiana do STFT quanto a ordem do FrFT, α, são ajustadas usando a entropia mínima como medidas locais e totais. Além disso, um novo parâmetro estatístico, denominado correlação normalizada, é definido para comparação de imagens reconstruídas por diferentes métodos. Os resultados da simulação mostram que o FrFT de ordem α com ajuste local tem desempenho muito melhor do que os outros métodos nesta categoria, mesmo em SNR baixo.
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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 -