Abstract
For inverse synthetic aperture radar (ISAR) imaging of targets with nonsevere maneuverability, the Doppler frequencies of scatterers are actually time-varying and azimuth echoes of a range cell have to be modeled as multicomponent linear frequency modulation (LFM) signals after the range alignment and the phase adjustment. In ISAR imaging with the LFM signal model, the chirp rate deteriorates the target image and an effective parameter estimation algorithm is required. By employing a symmetric instantaneous self-correlation function and the modified scaled Fourier transform, an effective parameter estimation algorithm, known as the centroid frequency chirp rate distribution (CFCRD), is proposed and applied to ISAR imaging. Compared to two representative parameter estimation algorithms, the modified Wigner-Ville distribution and the Lv’s distribution, the proposed CFCRD can acquire a higher antinoise performance without spectrum aliasing and brute-force searching. Through simulations and analyses of the synthetic radar data and the real radar data, we verify the effectiveness of CFCRD and the corresponding ISAR imaging algorithm.
Highlights
Inverse synthetic aperture radar (ISAR) imaging has attracted the attention of radar researchers in the past three decades due to its all-weather suitability and day and night availability.[1,2,3,4] The primary steps for ISAR imaging are the range alignment[5,6,7,8] and the phase adjustment.[9,10] the traditional range-Doppler (RD) method can be used to obtain the well-focused ISAR image for targets with smooth motions
For targets with nonsevere maneuverability, the traditional RD algorithm cannot work due to the time-varying Doppler frequencies of the scatterers. This ISAR imaging problem has motivated the research on the range-instantaneous Doppler (RID) technique[11,12] and the range instantaneous chirp rate (RIC) technique.[13,14]
Based on the RID technique or RIC technique, azimuth echoes of targets with nonsevere maneuverability can be modeled as multicomponent linear frequency modulation (LFM) signals
Summary
Inverse synthetic aperture radar (ISAR) imaging has attracted the attention of radar researchers in the past three decades due to its all-weather suitability and day and night availability.[1,2,3,4] The primary steps for ISAR imaging are the range alignment (compensating the translational and rotational range migrations)[5,6,7,8] and the phase adjustment (removing the Doppler phase induced by the translation).[9,10] the traditional range-Doppler (RD) method can be used to obtain the well-focused ISAR image for targets with smooth motions. To resolve problems of the aforementioned bilinear algorithms, the integrated cubic phase function,[20] the Radon-ambiguity transform,[21] the keystone-Wigner transform,[12,22] the fractional Fourier transform,[23,24] and the modified discrete chirp Fourier transform[25,26] are proposed They employ the brute-force searching of the unknown chirp rate to accumulate the signal energy, which benefits the cross-term suppression and the antinoise performance. An effective parameter estimation algorithm, known as the centroid frequency chirp rate distribution (CFCRD), is proposed by employing a novel symmetric instantaneous self-correlation function and the modified scaled Fourier transform (MSFT). In the two sections, the crossterm and the selection criterion of the zoom factor will be analyzed for CFCRD
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