Adaptive filtering method combined with quality map for InSAS interferogram

Huang, Pan; Teng, Xiaojie; Zhong, Heping

doi:10.1049/ell2.12472

Cited by 7 publications

(4 citation statements)

References 17 publications

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“…Some of the data points are not visible in the image, either because certain equipment was not adjusted on the day of the satellite transit or due to the image's coverage area. Similarly, since synthetic aperture sonar (SAS) [26,27] is similar in principle to SAR, the FFT interpolation and selection of the center of the point target with a sliding window used in this section are also applicable to SAS.…”

Section: Resultsmentioning

confidence: 99%

“…Similarly, since synthetic aperture sonar (SAS) [26,27] is similar in principle to SAR, the FFT interpolation and selection of the center of the point target with a sliding window used in this section are also applicable to SAS. Similarly, since synthetic aperture sonar (SAS) [26,27] is similar in principle to SA the FFT interpolation and selection of the center of the point target with a sliding windo used in this section are also applicable to SAS.…”

Section: Cr Location Extraction Based On Fft Interpolation and The Sl...mentioning

confidence: 99%

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Preliminary Evaluation of Geometric Positioning Accuracy of C-SAR Images Based on Automatic Corner Reflectors

Jiao,

Zhang,

Liu

et al. 2023

Remote Sensing

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C-SAR/01 and C-SAR/02 serve as successors to the GF-3 satellite. They are designed to operate in tandem with GF-3, collectively forming a C-band synthetic aperture radar (SAR) satellite constellation. This constellation aims to achieve 1 m resolution imaging with a revisit rate of one day. It can effectively cater to various applications such as marine disaster prevention, monitoring marine dynamic environments, and supporting marine scientific research, disaster mitigation, environmental protection, and agriculture. Geometric correction plays a pivotal role in acquiring highly precise geographic location data for ground targets. The geometric positioning accuracy without control points signifies the SAR satellite’s geometric performance. However, SAR images do not exhibit a straightforward image-point–object-point correspondence, unlike optical images. In this study, we introduce a novel approach employing high-precision automatic trihedral corner reflectors as ground control points (GCPs) to assess the geometric positioning accuracy of SAR images. A series of satellite-ground synchronization experiments was conducted at the Xilinhot SAR satellite calibration and validation site to evaluate the geometric positioning accuracy of different C-SAR image modes. Firstly, we calculated the azimuth and elevation angles of the corner reflectors based on satellite orbit parameters. During satellite transit, these corner reflectors were automatically adjusted to align with the radar-looking direction. We subsequently measured the exact longitude and latitude coordinates of the corner reflector vertex in situ using a high-precision real-time kinematics instrument. Next, we computed the theoretical image coordinates of the corner reflectors using the rational polynomial coefficients (RPC) model. After that, we determined the accurate position of the corner reflector in the Single Look Complex (SLC) SAR image using FFT interpolation and the sliding window method. Finally, we evaluated and validated the geometric positioning accuracy of C-SAR images by comparing the two coordinates. The preliminary results indicate that the positioning accuracy varies based on the satellite, imaging modes, and orbital directions. Nevertheless, for most sample points, the range positioning accuracy was better than 60 m, and the azimuth positioning accuracy was better than 80 m. These findings can serve as a valuable reference for subsequent applications of C-SAR satellites.

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Section: Resultsmentioning

confidence: 99%

Section: Cr Location Extraction Based On Fft Interpolation and The Sl...mentioning

confidence: 99%

Preliminary Evaluation of Geometric Positioning Accuracy of C-SAR Images Based on Automatic Corner Reflectors

Jiao,

Zhang,

Liu

et al. 2023

Remote Sensing

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“…Yang et al 50 proposed an interferogram filtering method with multilayer feature fusion neural networks. Huang et al 51 proposed an adaptive interferometric phase filtering method combined with quality maps, which adaptively determines the filter window size based on the correlation coefficient map, achieving good results and fast processing speeds. Among transform domain filter methods, Goldstein and Werner 52 proposed a method to filter interferometric phase noise in the frequency domain.…”

Section: Interferogram Filtering Methodsmentioning

confidence: 99%

Review of interferometric synthetic aperture sonar interferometric phase filtering methods

Huang,

Ding,

Wang

et al. 2023

Advances in Mechanical Engineering

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Interferometric synthetic aperture sonar (InSAS) is a novel three dimensional underwater mapping system, which is widely used in various fields. Interferometric phase filtering is a crucial process in InSAS signal processing. The study of interferogram filtering method has great significance to improve the signal-to-noise ratio (SNR) of interferogram, reduce the difficulty of phase unwrapping, and improve the accuracy of digital elevation maps. Firstly, this article introduces the sources of interferometric phase noise. Secondly, it illustrates the difference between real domain filter and complex domain filter by simulation experiment. Thirdly, the various methods of InSAS interferogram filtering are systematically studied, which can be classified into spatial domain filtering and transform domain filtering. The transform domain filtering can be further divided into frequency domain and wavelet transform filtering. Moreover, the advantages and disadvantages of various methods are analyzed theoretically. Finally, numerical simulation and real-data processing experiments are performed, and the advantages and shortcomings of several methods are compared using residue numbers, root mean square error (RMSE), and CPU time as evaluation criteria.

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“…With this tool, the users can easily find small objects such as pipeline and so on in seafloor. Besides, using a highresolution image [13][14][15][16], object recognition [17][18][19][20][21] can be performed quickly.…”

Section: Introductionmentioning

confidence: 99%

A Comparison of PCA and LBF Based Multireceiver SAS Imaging Algorithms

Wang,

Huang

2023

IEEE Access

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Multireceiver synthetic aperture sonar (SAS) is a useful tool to provide high-resolution images. The most important step lies in developments of multireceiver synthetic aperture image formation processors, which uses the sonar echoed signal as the input. The system transfer function is crucial in the development of signal processors. In order to use traditional imaging algorithms, the monostatic conversion transferring multireceiver SAS signal to monostatic SAS data is often conducted. A review and evaluation of imaging methods based on monostatic conversion is conducted in this article. The relationship of Phase center approximation (PCA) method and Loffeld's bistatic formula (LBF) is firstly reformulated in theory. Considering facts that PCA and LBF methods are the approximation of exact system transfer function, the approximation error of both methods are firstly compared and evaluated by using the numerical system transfer function, which is considered to be the precise system transfer function. Since more approximations of PCA and LBF should be carried out to develop fast imaging algorithms, the actual phase error of both methods is compared and evaluated based on numerical system transfer function. Then, the imaging performance of both methods based on range migration algorithm (RMA) is further evaluated. At last, the relationships of both patent methods are comprehensively described.

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Adaptive filtering method combined with quality map for InSAS interferogram

Cited by 7 publications

References 17 publications

Preliminary Evaluation of Geometric Positioning Accuracy of C-SAR Images Based on Automatic Corner Reflectors

Preliminary Evaluation of Geometric Positioning Accuracy of C-SAR Images Based on Automatic Corner Reflectors

Review of interferometric synthetic aperture sonar interferometric phase filtering methods

A Comparison of PCA and LBF Based Multireceiver SAS Imaging Algorithms

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