Refocusing of Ground Moving Targets with Doppler Ambiguity Using Keystone Transform and Modified Second-Order Keystone Transform for Synthetic Aperture Radar

Wan, Jun; Tan, Xiaoheng; Chen, Zhanye; Li, Dong; Liu, Qinghua; Zhou, Yu; Zhang, Linrang

doi:10.3390/rs13020177

Cited by 18 publications

(9 citation statements)

References 34 publications

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“…(1) Then, R s (t n ) can be expanded according to the Taylor series expansion, and a quadratic term model is utilized, as follows [8,9,[13][14][15][22][23][24][25][26][27]:…”

Section: Signal Modelmentioning

confidence: 99%

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Fast Approach for SAR Imaging of Ground-Based Moving Targets Based on Range Azimuth Joint Processing

et al. 2022

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The synthetic aperture radar (SAR) images of a moving target may be out of focus, given the motions of a non-cooperative target. Doppler ambiguities, including the Doppler center blur and spectrum ambiguity, will easily appear due to the limitations of pulse repetition frequency, which causes difficulty in moving-target imaging. Therefore, a robust fast Doppler ambiguity approach for SAR imaging of a ground-based moving target using range azimuth joint processing (RAJP) is presented. Firstly, the use of RAJP, based on a two-dimensional cross-correlation function and linear range cell migration (LRCM) compensation function, is proposed to simultaneously obtain the first- and second-order phase parameters in the fast-time and azimuth-frequency domains. Then, a corresponding azimuth reference function is constructed to image the moving target. Additionally, a principal component analysis-based operation is introduced to solve the mismatch with the LRCM compensation function. The couplings between the range and azimuth and between the first- and second-order parameters can be simultaneously decoupled by the proposed RAJP operation, which simplifies the processing steps. The developed approach can simultaneously obtain the first- and second-order parameters in the fast-time and azimuth-frequency domains, which avoids the propagation error of parameter estimation caused by the stepwise processing operation. The proposed method is relatively fast, given the need for fewer processing steps. The presented approach is robust in terms of Doppler ambiguity and handles the blind speed sidelobe well. In this study, simulated and real data are processed to verify the proposed approach.

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“…(1) Then, R s (t n ) can be expanded according to the Taylor series expansion, and a quadratic term model is utilized, as follows [8,9,[13][14][15][22][23][24][25][26][27]:…”

Section: Signal Modelmentioning

confidence: 99%

“…Generally, because of the limitations of the pulse repetition frequency (PRF) of an SAR system, the moving target signal quickly demonstrates a Doppler ambiguity [13][14][15]25]. If the Doppler center shift (DCS) induced by the cross-track velocity of a moving target is larger than PRF/2, a Doppler center blur will be generated.…”

Section: Introductionmentioning

confidence: 99%

Fast Approach for SAR Imaging of Ground-Based Moving Targets Based on Range Azimuth Joint Processing

et al. 2022

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“…Feng et al [28] used mean shift algorithm to track high-speed targets. Wan et al [29] used Keystone Transform and Modified Second-Order Keystone Transform to achieve moving target tracking. Lin et al [30] used multiple drones to achieve multi-target tracking.…”

Section: Introductionmentioning

confidence: 99%

A Multi Moving Target Recognition Algorithm Based on Remote Sensing Video

Zheng¹,

Bai²,

Tian³

2023

Computer Modeling in Engineering &Amp; Sciences

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The Earth observation remote sensing images can display ground activities and status intuitively, which plays an important role in civil and military fields. However, the information obtained from the research only from the perspective of images is limited, so in this paper we conduct research from the perspective of video. At present, the main problems faced when using a computer to identify remote sensing images are: They are difficult to build a fixed regular model of the target due to their weak moving regularity. Additionally, the number of pixels occupied by the target is not enough for accurate detection. However, the number of moving targets is large at the same time. In this case, the main targets cannot be recognized completely. This paper studies from the perspective of Gestalt vision, transforms the problem of moving target detection into the problem of salient region probability, and forms a Saliency map algorithm to extract moving targets. On this basis, a convolutional neural network with global information is constructed to identify and label the target. And the experimental results show that the algorithm can extract moving targets and realize moving target recognition under many complex conditions such as target's long-term stay and small-amplitude movement.

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“…First, the residual phase caused by the moving transmitter is corrected in range frequency-domain. Based on this, keystone transform (KT) [15][16][17][18] is used to eliminate the coupling between the range and azimuth, since the imaging capability is greatly affected by the coupling between the range and azimuth. Finally, the focused image is obtained through matched filtering.…”

Section: Introductionmentioning

confidence: 99%

An Adjusted Frequency-Domain Algorithm for Arc Array Bistatic SAR Data with One-Moving Transmitter

Huang

Hao

Tan

et al. 2022

Sensors

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Arc array synthetic aperture radar (AA-SAR), which can observe the scene in all directions, breaks through the single view of traditional SAR. However, the concealment of AA-SAR is poor. To mitigate this, arc array bistatic SAR (AA-BiSAR) with the moving transmitter is proposed, it has the advantages of good concealment and can expand the imaging scene, and improve the flexibility of the system. The imaging geometry including the signal model is established, and a range frequency-domain algorithm based on keystone transform (KT) is proposed in this paper. In the first step, the slant range equation is approximated by Taylor series expansion to compensate for the residual phase caused by the transmitter motion. In the second step, the range cell migration between the range and azimuth is eliminated through the KT method in the range frequency-domain. In the third step, using the data after range cell migration correction in step 2, an azimuth pulse compression is performed to obtain the focused image. In addition, the spatial resolution of the AA-BiSAR system is analyzed in detail. Finally, three simulation results verify the effectiveness of the proposed algorithm and the change in the spatial resolution.

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Refocusing of Ground Moving Targets with Doppler Ambiguity Using Keystone Transform and Modified Second-Order Keystone Transform for Synthetic Aperture Radar

Cited by 18 publications

References 34 publications

Fast Approach for SAR Imaging of Ground-Based Moving Targets Based on Range Azimuth Joint Processing

Fast Approach for SAR Imaging of Ground-Based Moving Targets Based on Range Azimuth Joint Processing

A Multi Moving Target Recognition Algorithm Based on Remote Sensing Video

An Adjusted Frequency-Domain Algorithm for Arc Array Bistatic SAR Data with One-Moving Transmitter

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