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Due to the large size of space targets, migration through resolution cells (MTRC) are induced by a rotational motion in high-resolution bistatic inverse synthetic aperture radar (Bi-ISAR) systems. The inaccurate correction of MTRC degrades the quality of Bi-ISAR images. However, it is challenging to correct the MTRC where sparse aperture data exists for Bi-ISAR systems. A joint approach of MTRC correction and sparse high-resolution imaging for Bi-ISAR systems is presented in this paper. First, a Bi-ISAR imaging sparse model-related to MTRC is established based on compress sensing (CS). Second, the target image elements and noise are modeled as the complex Laplace prior, and the Gaussian prior, respectively. Finally, the high-resolution, well-focused image is obtained by the full Bayesian inference method, without manual adjustments of unknown parameters. Simulated results verify the effectiveness and robustness of the proposed algorithm.

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In practical bistatic inverse synthetic aperture radar (ISAR) imaging systems, the echo signals are modulated by non-ideal amplitude and phase characteristics of the transmitting and receiving channels, which seriously distorts image quality. However, the conventional channel calibration method based on a transponder is not applicable to bistatic ISAR imaging systems, since the baseline of the system is up to hundreds of kilometers. A channel calibration method only using calibration satellite echo information is proposed for the system, with a linear frequency modulation (LFM) waveform. Firstly, echoes of the calibration satellite are collected by tracking the satellite and multi-period echoes are aligned in the time domain, according to the pulse compression result. Then, the signal to noise ratio (SNR) is improved by accumulating multi-period echoes coherently in the time domain and the calibration coefficient is constructed based on the accumulated signal. Finally, spectrum of the echo signal is multiplied with the calibration coefficient to compensate the influence of channel characteristics. The effectiveness of the proposed method is verified by the simulation experiment with real satellite echoes.