Novel Method of ISAR Cross-Range Scaling for Slowly Rotating Targets Based on the Iterative Adaptive Approach and Discrete Polynomial-Phase Transform

Wang, Yong; Huang, Xin; Cao, Rui

doi:10.1109/jsen.2019.2902618

Cited by 18 publications

(10 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…According to the experience, eight to ten range bins are always selected to acquire a good result of the RV estimation. If too few range bins are selected, the fitting result will not be accurate enough to reveal the linear relationship in (17). If too many range bins are selected, the computational burden will increase, and some unqualified range bins with several dominant scatterers may be chosen.…”

Section: Novel Cross-range Scaling Methodsmentioning

confidence: 99%

“…The FFT is not precise enough for a precise estimation of the RV of the desired target, especially for the slow rotation targets with small RVs. The algorithm in [17] can estimate small RVs, however, its involved iterative adaptive approach (IAA) is of high computational complexity. Thus, our paper focuses on proposing a highly accurate RV estimation method for the slow rotation target with a low computational burden.…”

Section: Introductionmentioning

confidence: 99%

“…However, many other cross-range scaling methods need to process all the range bins to obtain the estimation, which is quite computational expensive. Another reason is that the MUSIC technique has a lower computational complexity compared to other super-resolution methods, like the relax algorithm [20,23] and the IAA algorithm [17]. Those methods always include time-consuming iteration procedures.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

ISAR cross-range scaling based on the MUSIC technique

Liu

Wang

Zhang

2020

J. of Syst. Eng. Electron.

View full text Add to dashboard Cite

Cross-range scaling plays an important role in the inverse synthetic aperture radar (ISAR) imaging. Many of the published cross-range scaling algorithms are based on the fast Fourier transformation (FFT). However, the FFT technique is resolution limited, so that the FFT-based algorithms will fail in the rotation velocity (RV) estimation of the slow rotation target. In this paper, we propose an accurate cross-range scaling algorithm based on the multiple signal classification (MUSIC) method. We first select some range bins with the mono-component linear frequency modulated (LFM) signal model. Then, we dechirp the signal of each selected range bin into the form of sinusoidal signal, and utilize the super-resolution MUSIC technique to accurately estimate the frequency. After processing all the range bins, a linear relationship related to the RV can be obtained. Eventually, the ISAR image can be scaled. The proposal can precisely estimate the small RV of the slow rotation target with low computational complexity. Furthermore, the proposal can also be used in the case of cross-range scaling for the sparse aperture data. Experimental results with the simulated and raw data validate the superiority of the novel method.

show abstract

Section: Novel Cross-range Scaling Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

ISAR cross-range scaling based on the MUSIC technique

Liu

Wang

Zhang

2020

J. of Syst. Eng. Electron.

View full text Add to dashboard Cite

show abstract

“…Figure 1 is the target's motion model and imaging geometry [10]. We suppose that a linearly frequency modulated (LFM) signal is transmitted [3]…”

Section: Isar Imaging Modelmentioning

confidence: 99%

Moving target inverse synthetic aperture radar image resolution enhancement based on two‐dimensional block sparse signal reconstruction

Tong

Liu

2021

IET Image Processing

View full text Add to dashboard Cite

To achieve the high-resolution inverse synthetic aperture radar (ISAR) imaging of moving targets, the range Doppler method and compressed sensing technique can be used. However, those methods are generally faced with the problem of migration through range cells and basis mismatch problems, and the imaging results can be improved. To solve these problems and improve the image quality, the problem of ISAR imaging is termed as a block-sparse signal recovery problem by utilizing the block-sparse structure of the ISAR images. A localized low-rank promoting (LLP) method is introduced and extended to the complex case for the recovery of range compressed block-sparse signals. The sparse recovery problem is solved by minimizing another function, which is the surrogate function that can be solved more effectively. Based on the LLP method, the coefficients of the range compressed echo signal are reconstructed and some 2 × 2 matrices can be obtained. And then the log-determinant function is introduced to find the low rankness solutions for these matrices. Then the LLP method is also used in the cross-range domain to reconstruct the ISAR image. Experimental results show that the proposed method can recover better focused and higher quality ISAR images compared with the traditional methods.This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

show abstract

“…When the target has complex motions, the image plane is usually uncertain, and the real structure and size of the imaged target cannot be easily recognized and calculated [6]. These problems can be solved by interferometric inverse synthetic aperture radar (InISAR) because three-dimensional imaging of the target can be directly obtained without concerning the imaging plane as well as the cross-range scaling [6][7][8][9][10][11][12][13].…”

Section: Introductionmentioning

confidence: 99%

Squint Model InISAR Imaging Method Based on Reference Interferometric Phase Construction and Coordinate Transformation

2021

View full text Add to dashboard Cite

The imaging quality of InISAR under squint geometry can be greatly degraded due to the serious interferometric phase ambiguity (InPhaA) and thus result in image distortion problems. Aiming to solve these problems, a three-dimensional InISAR (3D ISAR) imaging method based on reference InPhas construction and coordinate transformation is presented in this paper. First, the target’s 3D coarse location is obtained by the cross-correlation algorithm, and a relatively stronger scatterer is taken as the reference scatterer to construct the reference interferometric phases (InPhas) so as to remove the InPhaA and restore the real InPhas. The selected scatterer needs not to be exactly in the center of the coarsely located target. Then, the image distortion is corrected by coordinate transformation, and finally the 3D coordinates of the target can be accurately estimated. Both simulation and practical experiment results validate the effectiveness of the method.

show abstract

Novel Method of ISAR Cross-Range Scaling for Slowly Rotating Targets Based on the Iterative Adaptive Approach and Discrete Polynomial-Phase Transform

Cited by 18 publications

References 25 publications

ISAR cross-range scaling based on the MUSIC technique

ISAR cross-range scaling based on the MUSIC technique

Moving target inverse synthetic aperture radar image resolution enhancement based on two‐dimensional block sparse signal reconstruction

Squint Model InISAR Imaging Method Based on Reference Interferometric Phase Construction and Coordinate Transformation

Contact Info

Product

Resources

About