Abstract
This paper presents a new Range-Doppler Algorithm based on Fractional Fourier Transform (RDA-FrFT) to obtain High-Resolution (HR) images for targets in radar imaging. The performance of the proposed RDA-FrFT is compared with the classical RDA algorithm, which is based on the Fast Fourier Transform (FFT). A closed-form expression for the range and azimuth compression of the proposed RDA-FrFT is mathematically derived and analyzed from the HR Synthetic Aperture Radar (SAR) imaging point of view. The proposed RDA-FrFT takes its advantage of the property of the FrFT to resolve chirp signals with high precision. Results show that the proposed RDA-FrFT gives low Peak Side-Lobe (PSL) and Integrated Side-Lobe (ISL) levels in range and azimuth directions for detected targets. HR images are obtained using the proposed RDA-FrFT algorithm.
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Appendices
Appendix 1
1.1 Range FrFT
where
The derivative of ϕ 1(t, η, f t ) with respect to t is given by
To use the PSP, we should find the range time t* when \( \frac{d\phi_{1} (t)}{dt} = 0 \)
The solution of the integral of S 1(f t , η) can be written as
where
The last term in Eq. 32 is the Residual Video Phase (RVP), which is a consequence of the range FrFT of the received chirp signal that should be removed to avoid defocusing of the constructed SAR image, hence
1.2 Range reference FrFT
where
To use the PSP, we should find the range time t* when \( \frac{d\phi_R (t)}{dt} = 0 \)
The solution of the integral of S R (f t ) can be written as
1.3 Range-IFrFT
To find the range frequency \( f_{t}^{*} \), the derivative \( \frac{{d\phi_3 (f_{t} )}}{{df_{t} }} \) must be equal zero,
Hence,
where \( M_{1} = {{K_{r} } \mathord{\left/ {\vphantom {{K_{r} } {\left[ {\left( {K_{r} + u_{o}^{2} \cot \alpha } \right) \cdot \left( {{{u_{o}^{\prime 2} \cos \alpha - 4\csc \alpha } \mathord{\left/ {\vphantom {{u_{o}^{\prime 2} \cos \alpha - 4\csc \alpha } {\left( {K_{r} + u_{o}^{2} \cot \alpha } \right)}}} \right. \kern-\nulldelimiterspace} {\left( {K_{r} + u_{o}^{2} \cot \alpha } \right)}}} \right)} \right]}}} \right. \kern-\nulldelimiterspace} {\left[ {\left( {K_{r} + u_{o}^{2} \cot \alpha } \right) \cdot \left( {{{u_{o}^{\prime 2} \cos \alpha - 4\csc \alpha } \mathord{\left/ {\vphantom {{u_{o}^{\prime 2} \cos \alpha - 4\csc \alpha } {\left( {K_{r} + u_{o}^{2} \cot \alpha } \right)}}} \right. \kern-\nulldelimiterspace} {\left( {K_{r} + u_{o}^{2} \cot \alpha } \right)}}} \right)} \right]}} \), is constant. \( M_{2} (t) = t_{d} - t - tu_{o}^{2} \cot \alpha /K_{r} \), which is constant for azimuth FrFT.
The solution of the integral of \( S_{3} (t,\eta ) \)can be written as
where
The above expression contains the RVP. We can remove it from our derivation, since it only adds additional complexity to the mathematical calculations.
where
Appendix 2
2.1 Azimuth FrFT
where
After applying the PSP, the final expression is
where
2.2 Azimuth Reference FrFT
The azimuth reference function used for the RDA is given by:
Its FrFT is given by:
then,
The next step is multiplying \( S_{4} (t,\,f_{\eta } )\,{\text {by}}\,S_{a} (f_{\eta } )\,{\text {to}\,{get}} \):
where
2.3 Azimuth IFrFT
where
After applying the PSP, the azimuth frequency is
and
The solution to the integral of \( S_{6} (t,\eta ) \) can be written as
where \( \phi_{6} \left( {t,\,f_{\eta }^{*} ,\eta^{*} } \right) \) is given in equation (56) replacing f η by \( f_{\eta }^{*} \) in equation (57).
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El-Mashed, M.G., Dessouky, M.I., El-Kordy, M. et al. Target Image Enhancement in Radar Imaging Using Fractional Fourier Transform. Sens Imaging 13, 37–53 (2012). https://doi.org/10.1007/s11220-011-0069-y
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DOI: https://doi.org/10.1007/s11220-011-0069-y