ISAR Imaging for Maneuvering Targets with Complex Motion Based on Generalized Radon-Fourier Transform and Gradient-Based Descent under Low SNR
The existing inverse synthetic aperture radar (ISAR) imaging algorithms for ship targets with complex three-dimensional (3D) rotational motion are not applicable because of continuous change of image projection plane (IPP), especially under low signal-to-noise-ratio (SNR) condition. To overcome this...
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MDPI AG
2021-06-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/13/11/2198 |
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| author | Zhijun Yang Dong Li Xiaoheng Tan Hongqing Liu Yuchuan Liu Guisheng Liao |
| author_facet | Zhijun Yang Dong Li Xiaoheng Tan Hongqing Liu Yuchuan Liu Guisheng Liao |
| author_sort | Zhijun Yang |
| collection | DOAJ |
| description | The existing inverse synthetic aperture radar (ISAR) imaging algorithms for ship targets with complex three-dimensional (3D) rotational motion are not applicable because of continuous change of image projection plane (IPP), especially under low signal-to-noise-ratio (SNR) condition. To overcome this obstacle, an efficient approach based on generalized Radon Fourier transform (GRFT) and gradient-based descent optimal is proposed in this paper. First, the geometry and signal model for nonstationary IPP of ship targets with complex 3-D rotational motion is established. Furthermore, the two-dimensional (2D) spatial-variant phase errors caused by complex 3-D rotational motion which can seriously blur the imaging performance are derived. Second, to improve the computational efficiency for 2-D spatial-variant phase errors compensation, the coarse motion parameters of ship targets are estimated via the GRFT method. In addition, using the gradient-based descent optimal method, the global optimum solution is iteratively estimated. Meanwhile, to solve the local extremum for cost surface obtained via conventional image entropy, the image entropy combined with subarray averaging is applied to accelerate the global optimal convergence. The main contributions of the proposed method are: (1) the geometry and signal model for ship targets with a complex 3-D rotational motion under nonstationary IPP are established; (2) the image entropy conjunct with subarray averaging operation is proposed to accelerate the global optimal convergence; (3) the proposed method can ensure the imaging accuracy even with high imaging efficiency thanks to the sole optimal solution generated by using the subarray averaging and image entropy. Several experiments using simulated and electromagnetic data are performed to validate the effectiveness of the proposed approach. |
| first_indexed | 2024-03-10T10:41:55Z |
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| id | doaj.art-554ca279589d47e2a84fc7fe480b772a |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-10T10:41:55Z |
| publishDate | 2021-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-554ca279589d47e2a84fc7fe480b772a2023-11-21T22:51:20ZengMDPI AGRemote Sensing2072-42922021-06-011311219810.3390/rs13112198ISAR Imaging for Maneuvering Targets with Complex Motion Based on Generalized Radon-Fourier Transform and Gradient-Based Descent under Low SNRZhijun Yang0Dong Li1Xiaoheng Tan2Hongqing Liu3Yuchuan Liu4Guisheng Liao5Chongqing Key Laboratory of Space Information Network and Intelligent Information Fusion, Chongqing 400044, ChinaSchool of Microelectronics and Communication Engineering, Chongqing University, Chongqing 400044, ChinaChongqing Key Laboratory of Space Information Network and Intelligent Information Fusion, Chongqing 400044, ChinaChongqing Key Laboratory of Communications Technology, Chongqing University of Posts and Telecommunications, Chongqing 400065, ChinaChongqing Key Laboratory of Space Information Network and Intelligent Information Fusion, Chongqing 400044, ChinaNational Laboratory of Radar Signal Processing, Xidian University, Xi’an 710071, ChinaThe existing inverse synthetic aperture radar (ISAR) imaging algorithms for ship targets with complex three-dimensional (3D) rotational motion are not applicable because of continuous change of image projection plane (IPP), especially under low signal-to-noise-ratio (SNR) condition. To overcome this obstacle, an efficient approach based on generalized Radon Fourier transform (GRFT) and gradient-based descent optimal is proposed in this paper. First, the geometry and signal model for nonstationary IPP of ship targets with complex 3-D rotational motion is established. Furthermore, the two-dimensional (2D) spatial-variant phase errors caused by complex 3-D rotational motion which can seriously blur the imaging performance are derived. Second, to improve the computational efficiency for 2-D spatial-variant phase errors compensation, the coarse motion parameters of ship targets are estimated via the GRFT method. In addition, using the gradient-based descent optimal method, the global optimum solution is iteratively estimated. Meanwhile, to solve the local extremum for cost surface obtained via conventional image entropy, the image entropy combined with subarray averaging is applied to accelerate the global optimal convergence. The main contributions of the proposed method are: (1) the geometry and signal model for ship targets with a complex 3-D rotational motion under nonstationary IPP are established; (2) the image entropy conjunct with subarray averaging operation is proposed to accelerate the global optimal convergence; (3) the proposed method can ensure the imaging accuracy even with high imaging efficiency thanks to the sole optimal solution generated by using the subarray averaging and image entropy. Several experiments using simulated and electromagnetic data are performed to validate the effectiveness of the proposed approach.https://www.mdpi.com/2072-4292/13/11/2198nonstationary image projection plane (IPP)2-D spatial-variant phase errorGRFTgradient-based optimalimage entropy combined with subarray averaging operationinverse synthetic aperture radar (ISAR) imaging |
| spellingShingle | Zhijun Yang Dong Li Xiaoheng Tan Hongqing Liu Yuchuan Liu Guisheng Liao ISAR Imaging for Maneuvering Targets with Complex Motion Based on Generalized Radon-Fourier Transform and Gradient-Based Descent under Low SNR Remote Sensing nonstationary image projection plane (IPP) 2-D spatial-variant phase error GRFT gradient-based optimal image entropy combined with subarray averaging operation inverse synthetic aperture radar (ISAR) imaging |
| title | ISAR Imaging for Maneuvering Targets with Complex Motion Based on Generalized Radon-Fourier Transform and Gradient-Based Descent under Low SNR |
| title_full | ISAR Imaging for Maneuvering Targets with Complex Motion Based on Generalized Radon-Fourier Transform and Gradient-Based Descent under Low SNR |
| title_fullStr | ISAR Imaging for Maneuvering Targets with Complex Motion Based on Generalized Radon-Fourier Transform and Gradient-Based Descent under Low SNR |
| title_full_unstemmed | ISAR Imaging for Maneuvering Targets with Complex Motion Based on Generalized Radon-Fourier Transform and Gradient-Based Descent under Low SNR |
| title_short | ISAR Imaging for Maneuvering Targets with Complex Motion Based on Generalized Radon-Fourier Transform and Gradient-Based Descent under Low SNR |
| title_sort | isar imaging for maneuvering targets with complex motion based on generalized radon fourier transform and gradient based descent under low snr |
| topic | nonstationary image projection plane (IPP) 2-D spatial-variant phase error GRFT gradient-based optimal image entropy combined with subarray averaging operation inverse synthetic aperture radar (ISAR) imaging |
| url | https://www.mdpi.com/2072-4292/13/11/2198 |
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