Sparse sampling‐based microwave 3D imaging using interferometry and frequency‐domain principal component analysis

He, Tao; Li, Daojing

doi:10.1049/iet-rsn.2017.0087

Cited by 5 publications

(3 citation statements)

References 25 publications

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“…3 shows a MURA code and its auto-correlation function (ACF). We can see that it has a space occupancy of 50% and a sharp ACF, therefore it has an ideal auto-correlation property within limited geometry size [26]. Reference [27] demonstrated the applicability of MURA code for SAR 3D imaging with efficient performance.…”

Section: Mura-based Echo Extractionmentioning

confidence: 91%

Airborne sparse flight array SAR 3D imaging based on compressed sensing in frequency domain

He¹,

Dong²,

Yin³

et al. 2023

J. of Syst. Eng. Electron.

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In airborne array synthetic aperture radar (SAR), the three-dimensional (3D) imaging performance and cross-track resolution depends on the length of the equivalent array. In this paper, Barker sequence criterion is used for sparse flight sampling of airborne array SAR, in order to obtain high cross-track resolution in as few times of flights as possible. Under each flight, the imaging algorithm of back projection (BP) and the data extraction method based on modified uniformly redundant arrays (MURAs) are utilized to obtain complex 3D image pairs. To solve the side-lobe noise in images, the interferometry between each image pair is implemented, and compressed sensing (CS) reconstruction is adopted in the frequency domain. Furthermore, to restore the geometrical relationship between each flight, the phase information corresponding to negative MURA is compensated on each single-pass image reconstructed by CS. Finally, by coherent accumulation of each complex image, the high resolution in cross-track direction is obtained. Simulations and experiments in X-band verify the availability.

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Section: Mura-based Echo Extractionmentioning

confidence: 91%

Airborne sparse flight array SAR 3D imaging based on compressed sensing in frequency domain

He¹,

Dong²,

Yin³

et al. 2023

J. of Syst. Eng. Electron.

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“…Firstly, the algorithm is utilized to complete the large range migra-tion correction in the cross-track direction and the 3-D imaging result of a 4.84 km equivalent cross-track aperture under sparse sampling is realized. Secondly, referring to the method of literature [17] to [21], interferometry is exploited to obtain a sparse frequency spectrum. In addition, principal component analysis (PCA) [22,23] is utilized to extract the main features in the image spectrum, and the 3-D image reconstruction result of the observation scenario can be obtained by inverse transformation of the reconstructed spectrum.…”

Section: Introductionmentioning

confidence: 99%

Sparse flight spotlight mode 3-D imaging of spaceborne SAR based on sparse spectrum and principal component analysis

Zhou¹,

cui³

et al. 2021

J. of Syst. Eng. Electron.

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The spaceborne synthetic aperture radar (SAR) sparse flight 3-D imaging technology through multiple observations of the cross-track direction is designed to form the crosstrack equivalent aperture, and achieve the third dimensionality recognition. In this paper, combined with the actual triple star orbits, a sparse flight spaceborne SAR 3-D imaging method based on the sparse spectrum of interferometry and the principal component analysis (PCA) is presented. Firstly, interferometric processing is utilized to reach an effective sparse representation of radar images in the frequency domain. Secondly, as a method with simple principle and fast calculation, the PCA is introduced to extract the main features of the image spectrum according to its principal characteristics. Finally, the 3-D image can be obtained by inverse transformation of the reconstructed spectrum by the PCA. The simulation results of 4.84 km equivalent crosstrack aperture and corresponding 1.78 m cross-track resolution verify the effective suppression of this method on high-frequency sidelobe noise introduced by sparse flight with a sparsity of 49% and random noise introduced by the receiver. Meanwhile, due to the influence of orbit distribution of the actual triple star orbits, the simulation results of the sparse flight with the 7-bit Barker code orbits are given as a comparison and reference to illuminate the significance of orbit distribution for this reconstruction results. This method has prospects for sparse flight 3-D imaging in high latitude areas for its short revisit period.

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“…The PCA technique has been frequently applied in data reduction [7][8][9][10], and it will be compared in this work with a statistical analysis used to perform the same task. The PCA compression reduction on near-field data compression was tested before for a half-wavelength dipole and an array of dipoles [11], and in this work, it will be also evaluated to a scattered field by a dielectric sphere.…”

Section: Introductionmentioning

confidence: 99%

Comparison between statistical and principal component analysis in reduction of near‐field FDTD data

Ramos¹,

Rodrigues

Camilo

et al. 2019

IET Microwaves, Antennas & Propagation

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We present a comparison of statistical and principal component analyses (PCA) for reducing the amount of near‐field data required as an input to a time‐domain spherical‐multipole near‐to‐far‐field transformation. Such transformations are necessary for finite‐difference time‐domain (FDTD) simulations that typically only model the near‐field. The authors demonstrate their approach for the case of far‐fields scattered by a dielectric sphere. For a threshold value of 106, the PCA technique reduced the data required by 32%, using 12 components. A similar compression was achieved with statistical analysis, when the threshold is set at 10−7σ. Their work shows that the proposed statistical compression is preferable because it has simpler implementation and low‐cost processing, when implemented together with the NFF transformation code.

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Sparse sampling‐based microwave 3D imaging using interferometry and frequency‐domain principal component analysis

Cited by 5 publications

References 25 publications

Airborne sparse flight array SAR 3D imaging based on compressed sensing in frequency domain

Airborne sparse flight array SAR 3D imaging based on compressed sensing in frequency domain

Sparse flight spotlight mode 3-D imaging of spaceborne SAR based on sparse spectrum and principal component analysis

Comparison between statistical and principal component analysis in reduction of near‐field FDTD data

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