Bistatic three-dimensional interferometric ISAR image reconstruction

Zhao, Lizhi; Gao, Meiguo; Stagliano, Daniele

doi:10.1109/taes.2014.130702

Cited by 37 publications

(16 citation statements)

References 24 publications

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“…The greatest strength of the proposed method is to prove a method for the radar network to reconstruct the 3D image of the spinning target, and the anisotropy problem which is caused when the radars in the network observe the target from the different perspectives is overcome in the proposed method. At present, interferometric technique is regarded as an effective method to reconstruct the 3D image with high precision, and there are several novel and cutting-edge papers [10,11,14,20,30] which study the interferometric technique to reconstruct the 3D target image. In the interferometric 3D imaging method, L-shaped three-antenna configuration or the Bistatic radar configuration is necessary to generate the interferometric signal and calculate the interferometric phase.…”

Section: Discussionmentioning

confidence: 99%

“…As mentioned above, the radar network can observe the air target from the different perspectives, thus at least one radar in the radar network could produce the 2D imaging result of the target, regardless of the fight direction of the target. Moreover, 3D imaging method must extract the multidimensional characteristics about the target to produce the 3D image [30]. The monostatic radar can only extract the limited target characteristics, while the radar network can extract more characteristics about the target by observing from the different perspectives [31,32].…”

Section: Introductionmentioning

confidence: 99%

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Reconstruction of Three-Dimensional Images Based on Estimation of Spinning Target Parameters in Radar Network

et al. 2018

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A high-resolution three-dimensional (3D) image reconstruction method for a spinning target is proposed in this paper and the anisotropy is overcome by fusing different observation information acquired from the radar network. The proposed method will reconstruct the 3D scattering distribution, and the mapping of the reconstructed 3D image onto the imaging plane is identical to the two-dimensional (2D) imaging result. At first, the range compression and inverse radon transform is employed to produce the 2D image of the spinning target. In addition, the process of mapping the spinning target onto the imaging plane is analyzed and the mapping formulas which are to map the point onto the 2D image plane are derived. After the micro-Doppler signature about which every reconstructed point in 2D imaging result is extracted by the Radon transform, the extended Hough transform is adopted to calculate an important parameter about the micro-Doppler signature, and the 3D image reconstruction model for the spinning target is constructed based on the radar network. Finally, the algorithm for solving the reconstruction model is proposed and the 3D image of the spinning target is obtained. Some simulation results are given to illustrate the effectiveness of the proposed method, and results show that the mean square error (MSE) relatively holds a steady trend when the signal-to-noise ratio (SNR) is higher than −10 dB and the MSE of the reconstructed 3D target image is less than 0.15 when SNR is at the level of −10 dB.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Reconstruction of Three-Dimensional Images Based on Estimation of Spinning Target Parameters in Radar Network

et al. 2018

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“…Currently, aiming at two features of the Bi-ISAR in terms of scaled image resolution and image shearing distortion, bistatic distortion correction methods and a crossrange scaling technique are studied [9][10][11]. With the continuous development of signal processing technology, bistatic three-dimensional (3-D) interferometric ISAR based on interference processing has gradually become a research hotspot [12][13][14]. Also, this kind of method can provide more abundant information.…”

Section: Introductionmentioning

confidence: 99%

Bistatic Radar Coincidence Imaging Based on Multiple Measurement Vectors for Rotating Cone-Shaped Targets

Luo

Zhang

et al. 2020

Journal of Sensors

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Bistatic radar imaging can overcome limitations of monostatic radar imaging and obtain abundant target feature information; thus, it is followed with interest. Different from bistatic inverse synthetic aperture radar (Bi-ISAR) imaging, bistatic radar coincidence imaging (Bi-RCI) provides a new tack on the bistatic radar imaging technique. In this paper, a Bi-RCI based on multiple measurement vectors (MMV) for rotating cone-shaped targets is proposed to realize Bi-RCI coherent processing and improve imaging performance. Based on the mixed mode signals, a MMV parametric model is established and measurement number coarse selection is proposed. Finally, a modified sparse Bayesian learning (MSBL) algorithm is introduced to reconstruct the target image. Simulation results demonstrate the validity and the superiority of the proposed method.

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“…Hence, the bistatic-ISAR system has been an effective solution for space targets surveillance [7][8][9][10][11][12]. The bistatic-ISAR research, with respect to application and algorithm, has been studied in recent years [6,[13][14][15][16][17][18][19].…”

Section: Introductionmentioning

confidence: 99%

Bistatic-ISAR Linear Geometry Distortion Alleviation of Space Targets

et al. 2019

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The linear geometry distortion caused by time variant bistatic angles induces the sheared shape of the bistatic inverse synthetic aperture radar (bistatic-ISAR) image. A linear geometry distortion alleviation algorithm for space targets in bistatic-ISAR systems is presented by exploiting prior information. First, we analyze formation mathematics of linear geometry distortions in the Range Doppler (RD) domain. Second, we estimate coefficients of first-order polynomial of bistatic angles by least square error (LSE) method through exploiting the imaging geometry and orbital information of space targets. Third, we compensate the linear spatial-variant terms to restore the linear geometry distortions. Consequently, the restored bistatic-ISAR image with real shape is obtained. Simulated results of the ideal point scatterers dataset and electromagnetic numerical dataset verify the performance of the proposed algorithm.

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Bistatic three-dimensional interferometric ISAR image reconstruction

Cited by 37 publications

References 24 publications

Reconstruction of Three-Dimensional Images Based on Estimation of Spinning Target Parameters in Radar Network

Reconstruction of Three-Dimensional Images Based on Estimation of Spinning Target Parameters in Radar Network

Bistatic Radar Coincidence Imaging Based on Multiple Measurement Vectors for Rotating Cone-Shaped Targets

Bistatic-ISAR Linear Geometry Distortion Alleviation of Space Targets

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