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Abstract
In an inverse synthetic aperture radar (ISAR) imaging system for targets with complex motion, the azimuth echo signals of the target are always modeled as multicomponent quadratic frequency modulation (QFM) signals. The chirp rate (CR) and quadratic chirp rate (QCR) estimation of QFM signals is very important to solve the ISAR image defocus problem. For multicomponent QFM (multi-QFM) signals, the conventional QR and QCR estimation algorithms suffer from the cross-term and poor anti-noise ability. This paper proposes a novel estimation algorithm called a two-dimensional product modified parameterized chirp rate-quadratic chirp rate distribution (2D-PMPCRD) for QFM signals parameter estimation. The 2D-PMPCRD employs a multi-scale parametric symmetric self-correlation function and modified nonuniform fast Fourier transform-Fast Fourier transform to transform the signals into the chirp rate-quadratic chirp rate (CR-QCR) domains. It can greatly suppress the cross-terms while strengthening the auto-terms by multiplying different CR-QCR domains with different scale factors. Compared with high order ambiguity function-integrated cubic phase function and modified Lv’s distribution, the simulation results verify that the 2D-PMPCRD acquires higher anti-noise performance and obtains better cross-terms suppression performance for multi-QFM signals with reasonable computation cost.
Highlights
The high-resolution inverse synthetic aperture radar (ISAR) imaging has been widely used in the field of civil and military in the past few decades
We propose two-dimensional product modified parameterized chirp rate-quadratic chirp rate distribution (2D-PMPCRD) to estimate the parameters of quadratic frequency modulation (QFM) signals
We propose the 2D-PMPCRD to estimate CR and quadratic chirp rate (QCR) of the QFM signals by introducing a novel multi-scale parametric symmetric self-correlation function (PSSAF) and the mNUFFT-fast-Fourier transform (FFT)
Summary
The high-resolution inverse synthetic aperture radar (ISAR) imaging has been widely used in the field of civil and military in the past few decades. Igor Djurovic proposed HAF-integrated CPF (HAF-ICPF) [15] by combining HAF with ICPF to estimate the parameters of the QFM signals It improves the anti-noise performance to some extent and its threshold SNR is −2 dB [15,20]. We propose two-dimensional product modified parameterized chirp rate-quadratic chirp rate distribution (2D-PMPCRD) to estimate the parameters of QFM signals. It combines a multi-scale parametric symmetric self-correlation function (PSSAF) with modified nonuniform fast Fourier transform-Fast Fourier transform (mNUFFT-FFT) to transform the signals into the chirp rate-quadratic chirp rate(CR-QCR) domains.
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