Abstract
The inverse synthetic aperture radar (ISAR) imaging for targets with complex motions has always been a challenging task due to the time-varying Doppler parameter, especially at the low signal-to-noise ratio (SNR) condition. In this paper, an efficient ISAR imaging algorithm for maneuvering targets based on a noise-resistance bilinear coherent integration is developed without the parameter estimation. First, the received signals of the ISAR in a range bin are modelled as a multicomponent quadratic frequency-modulated (QFM) signal after the translational motion compensation. Second, a novel quasi-time-frequency representation noise-resistance bilinear Radon-cubic phase function (CPF)-Fourier transform (RCFT) is proposed, which is based on the coherent integration of the energy of auto-terms along the slope line trajectory. In doing so, the RCFT also effectively suppresses the cross-terms and spurious peaks interference at no expense of the time-frequency resolution loss. Third, the cross-range positions of target’s scatters in ISAR image are obtained via a simple maximization projection from the RCFT result to the Doppler centroid axis, and the final high-resolution ISAR image is thus produced by regrouping all the range-Doppler frequency centroids. Compared with the existing time-frequency analysis-based and parameter estimation-based ISAR imaging algorithms, the proposed method presents the following features: (1) Better cross-term interference suppression at no time-frequency resolution loss; (2) computationally efficient without estimating the parameters of each scatters; (3) higher signal processing gain because of 2-D coherent integration realization and its bilinear function feature. The simulation results are provided to demonstrate the performance of the proposed method.
Highlights
Thanks to the ability to produce high-resolution microwave imagery for the non-cooperative target nearly regardless of weather condition, the inverse synthetic aperture radar (ISAR) presents a range of applications in the field of national defense surveillance [1,2,3,4]
The Radon-cubic phase function (CPF)-Fourier transform (RCFT) method is first proposed for the analysis of multiple quadratic frequency-modulated (QFM) signals
Because of 2-D coherent integration realization and the bilinear function feature, the better cross-term interference suppression is achieved at no loss of time-frequency resolution, and higher signal processing gain is obtained
Summary
Thanks to the ability to produce high-resolution microwave imagery for the non-cooperative target nearly regardless of weather condition, the inverse synthetic aperture radar (ISAR) presents a range of applications in the field of national defense surveillance [1,2,3,4]. The first group is the parametric approach, where the received signal in a range bin is modeled by a special signal [7,8,9], and based on that, the instantaneous Doppler frequency is estimated and the corresponding ISAR image is obtained by using the estimated Doppler frequency. ISAR imaging algorithm based a new quasi-time-frequency transform named Lv’s distribution was proposed, where the cross-terms suppression is better achieved with no time-frequency resolution loss. This method is only valid for linear frequency modulated (LFM) signals, and its performance degrades dramatically in the case of quadratic frequency-modulated (QFM) signal that often is utilized to model the maneuvering targets.
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