Bistatic ISAR distortion mitigation of a space target via exploiting the orbital prior information

Shi, Lin; Guo, Baofeng; Han, Ning; Ma, Jun; Zhao, Lizhi; Shang, Chaoxuan

doi:10.1049/iet-rsn.2018.5605

Cited by 3 publications

(15 citation statements)

References 32 publications

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“…The rectangular coordinate system xOy and uO m v are the target ontology coordinate systems with the target mass center O and O m as the origin at imaging time t 0 , and t m , respectively. More details are available in our previous paper [21].…”

Section: Bi-isar Cs-based Imaging Model With Mtrcmentioning

confidence: 99%

“…where σ P is the scattering coefficient, R Pm = R TPm + R RPm denotes the total instantaneous distance between P m and both the transmitter and the receiver. As we mentioned in [21], the R Pm can be written as,…”

Section: Bi-isar Cs-based Imaging Model With Mtrcmentioning

confidence: 99%

“…represents the rotational motion of the target. It can be further approximated by the second-order Taylor polynomial [21],…”

Section: Bi-isar Cs-based Imaging Model With Mtrcmentioning

confidence: 99%

“…where K 0 is the first-order coefficient of the time-variant bistatic angles and K 1 is the second-order coefficient [21], and ω 0 is the rotational velocity. Those two coefficients and rotational velocity can be estimated by exploiting the prior information [21,30]. The conventional range alignment methods [31,32] still work for sparse aperture data.…”

Section: Bi-isar Cs-based Imaging Model With Mtrcmentioning

confidence: 99%

“…In [17], we proposed a MTRC correction method for the Bi-ISAR systems in the presence of time-variant bistatic angles. Recently, based on [17], we proposed a distortions mitigation method that can correct the cross-range MTRC simultaneously by 2 of 17 exploiting prior information in [21]. However, the correction methods are all for full aperture data.…”

Section: Introductionmentioning

confidence: 99%

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High-Resolution Bistatic ISAR Imaging of a Space Target with Sparse Aperture

et al. 2019

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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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Section: Bi-isar Cs-based Imaging Model With Mtrcmentioning

confidence: 99%

Section: Bi-isar Cs-based Imaging Model With Mtrcmentioning

confidence: 99%

“…represents the rotational motion of the target. It can be further approximated by the second-order Taylor polynomial [21],…”

Section: Bi-isar Cs-based Imaging Model With Mtrcmentioning

confidence: 99%