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22 pages, 4009 KiB

Open AccessArticle

Estimation of High-Frequency Vibration Parameters for Airborne Terahertz SAR Using Chirplet Decomposition and LS Sequential Estimators

by Zhaoxin Hao, Jinping Sun, Qing Li and Tao Shan

Remote Sens. 2022, 14(14), 3416; https://doi.org/10.3390/rs14143416 - 16 Jul 2022

Cited by 1 | Viewed by 1070

Abstract

Due to the short wavelength of the terahertz wave, airborne terahertz synthetic aperture radar (THz-SAR) suffers from echo phase errors caused by the high-frequency vibration of the platform. These errors will result in defocusing and the emergence of ghost targets, which will degrade [...] Read more.

Due to the short wavelength of the terahertz wave, airborne terahertz synthetic aperture radar (THz-SAR) suffers from echo phase errors caused by the high-frequency vibration of the platform. These errors will result in defocusing and the emergence of ghost targets, which will degrade the quality of the image. Therefore, it is necessary to compensate for phase errors in order to bring the image into focus. This paper proposes a multi-component high-frequency vibration parameter estimation method based on chirplet decomposition and least squares (LS) sequential estimators, which differs from other methods that can only be applied to simple harmonic vibrations. In particular, we first obtain the instantaneous chirp rate (ICR) of the signal by chirplet decomposition. Then, we employ the LS sequential estimators in conjunction with separable regression technique (SRT) to estimate vibration parameters. The estimated parameters are subsequently used to re-establish the ICR components for each vibration component and these parameters are further re-estimated to improve their accuracy. Based on the estimated parameters, phase compensation functions can be constructed to suppress the defocusing and ghost targets in airborne THz-SAR imaging. Simulated results on point targets and distributed imaging scenes demonstrate that the proposed method is accurate and reliable even at low signal-to-noise ratios (SNRs). Full article

(This article belongs to the Special Issue Advances in Synthetic Aperture Radar Remote Sensing)

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18 pages, 9558 KiB

Open AccessArticle

Beijing Land Subsidence Revealed Using PS-InSAR with Long Time Series TerraSAR-X SAR Data

by Zechao Bai, Yanping Wang and Timo Balz

Remote Sens. 2022, 14(11), 2529; https://doi.org/10.3390/rs14112529 - 25 May 2022

Cited by 12 | Viewed by 3002

Abstract

Beijing is a major city suffering from land subsidence due to long-term over-exploitation of groundwater. The South-to-North Water Diversion Project (SNWDP), however, has had a significant impact on the structure of water consumption since the end of 2014, and it is changing the [...] Read more.

Beijing is a major city suffering from land subsidence due to long-term over-exploitation of groundwater. The South-to-North Water Diversion Project (SNWDP), however, has had a significant impact on the structure of water consumption since the end of 2014, and it is changing the status of land subsidence in Beijing. In this study, we employed Persistent Scatterers Synthetic Aperture Radar Interferometric (PS-InSAR) to investigate the decadal evolution of land subsidence in Beijing with 100 TerraSAR-X stripmap images collected from April 2010 to December 2019. The water resources, historic climate and urban construction data were compiled for the years of 2010 to 2019 to analyze changes in groundwater level, human activity, surface geology, active faults and land subsidence patterns. The results show that the changes in the water supply structure are correlated to a rise in groundwater level after 2015. These changes include an increase in the water supply from the SNWDP, a reduction in groundwater exploitation, the optimization of water consumption, replacing recycled water for environmental water and a reduction in the use of water for agriculture. Land subsidence in the study area was concentrated in the eastern regions, trending towards a decreasing velocity starting about two years after the commencement of SNWDP in 2015. Uneven subsidence in the land subsidence area was related to excavations of underground soil, and the construction of Line 6 and Line 7 led to rapid nonlinear subsidence. Our results have scientific significance for reducing subsidence hazards in the context of SNWDP and urban expansion. Full article

(This article belongs to the Special Issue Advances in Synthetic Aperture Radar Remote Sensing)

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15 pages, 12047 KiB

Open AccessCommunication

Multi-Frequency Interferometric Coherence Characteristics Analysis of Typical Objects for Coherent Change Detection

by Zhongbin Wang, Yachao Wang, Bingnan Wang, Maosheng Xiang, Rongrong Wang, Weidi Xu and Chong Song

Remote Sens. 2022, 14(7), 1689; https://doi.org/10.3390/rs14071689 - 31 Mar 2022

Cited by 5 | Viewed by 1778

Abstract

This paper focuses on the study of a multi-frequency interferometric coherence characteristics analysis of typical objects for coherent change detection. Coherent change detection utilizes the phase difference between two or more SAR images to detect potential changes in the scene. It makes a [...] Read more.

This paper focuses on the study of a multi-frequency interferometric coherence characteristics analysis of typical objects for coherent change detection. Coherent change detection utilizes the phase difference between two or more SAR images to detect potential changes in the scene. It makes a difference in civilian and military applications. However, the relationship between the coherence of typical objects and SAR frequency has not been fully studied, which restricts the quality of the detection results. To address this problem, this paper conducts research on the relationship between the coherence of typical objects and SAR frequency, and the coherence characteristics are obtained through statistical analysis. In order to illustrate the relationship more clearly, the actual experimental data obtained by the DVD-InSAR system developed by the Aerospace Information Research Institute, Chinese Academy of Sciences, are utilized. The experimental results show that the coherence characteristics of typical objects are different, and this finding can provide strong support for developing change-detection applications. Full article

(This article belongs to the Special Issue Advances in Synthetic Aperture Radar Remote Sensing)

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10 pages, 52982 KiB

Open AccessCommunication

SAR Target Detection Based on Domain Adaptive Faster R-CNN with Small Training Data Size

by Yuchen Guo, Lan Du and Guoxin Lyu

Remote Sens. 2021, 13(21), 4202; https://doi.org/10.3390/rs13214202 - 20 Oct 2021

Cited by 18 | Viewed by 2929

Abstract

It is expensive and time-consuming to obtain a large number of labeled synthetic aperture radar (SAR) images. In the task of small training data size, the results of target detection on SAR images using deep network approaches are usually not ideal. In this [...] Read more.

It is expensive and time-consuming to obtain a large number of labeled synthetic aperture radar (SAR) images. In the task of small training data size, the results of target detection on SAR images using deep network approaches are usually not ideal. In this study, considering that optical remote sensing images are much easier to be labeled than SAR images, we assume to have a large number of labeled optical remote sensing images and a small number of labeled SAR images with the similar scenes, propose to transfer knowledge from optical remote sensing images to SAR images, and develop a domain adaptive Faster R-CNN for SAR target detection with small training data size. In the proposed method, in order to make full use of the label information and realize more accurate domain adaptation knowledge transfer, an instance level domain adaptation constraint is used rather than feature level domain adaptation constraint. Specifically, generative adversarial network (GAN) constraint is applied as the domain adaptation constraint in the adaptation module after the proposals of Faster R-CNN to achieve instance level domain adaptation and learn the transferable features. The experimental results on the measured SAR image dataset show that the proposed method has higher detection accuracy in the task of SAR target detection with small training data size than the traditional Faster R-CNN. Full article

(This article belongs to the Special Issue Advances in Synthetic Aperture Radar Remote Sensing)

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13 pages, 2050 KiB

Open AccessCommunication

3D Point Cloud Reconstruction Using Inversely Mapping and Voting from Single Pass CSAR Images

by Shanshan Feng, Yun Lin, Yanping Wang, Fei Teng and Wen Hong

Remote Sens. 2021, 13(17), 3534; https://doi.org/10.3390/rs13173534 - 06 Sep 2021

Cited by 9 | Viewed by 2202

Abstract

3D reconstruction has raised much interest in the field of CSAR. However, three dimensional imaging results with single pass CSAR data reveals that the 3D resolution of the system is poor for anisotropic scatterers. According to the imaging mechanism of CSAR, different targets [...] Read more.

3D reconstruction has raised much interest in the field of CSAR. However, three dimensional imaging results with single pass CSAR data reveals that the 3D resolution of the system is poor for anisotropic scatterers. According to the imaging mechanism of CSAR, different targets located on the same iso-range line in the zero doppler plane fall into the same cell while for the same target point, imaging point will fall into the different positions at different aspect angles. In this paper, we proposed a method for 3D point cloud reconstruction using projections on 2D sub-aperture images. The target and background in the sub-aperture images are separated and binarized. For a projection point of target, given a series of offsets, the projection point will be mapped inversely to the 3D mesh along the iso-range line. We can obtain candidate points of the target. The intersection of iso-range lines can be regarded as voting process. For a candidate, the more times of intersection, the higher the number of votes, and the candidate point will be reserved. This fully excavates the information contained in the angle dimension of CSAR. The proposed approach is verified by the Gotcha Volumetric SAR Data Set. Full article

(This article belongs to the Special Issue Advances in Synthetic Aperture Radar Remote Sensing)

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14 pages, 6632 KiB

Open AccessTechnical Note

An Improved Multi-Baseline Phase Unwrapping Method for GB-InSAR

by Zihao Lin, Yan Duan, Yunkai Deng, Weiming Tian and Zheng Zhao

Remote Sens. 2022, 14(11), 2543; https://doi.org/10.3390/rs14112543 - 26 May 2022

Cited by 4 | Viewed by 1449

Abstract

Ground-based interferometric synthetic aperture radar (GB-InSAR) technology can be applied to generate a digital elevation model (DEM) with high spatial resolution and high accuracy. Phase unwrapping is a critical procedure, and unwrapping errors cannot be effectively avoided in the interferometric measurements of terrains [...] Read more.

Ground-based interferometric synthetic aperture radar (GB-InSAR) technology can be applied to generate a digital elevation model (DEM) with high spatial resolution and high accuracy. Phase unwrapping is a critical procedure, and unwrapping errors cannot be effectively avoided in the interferometric measurements of terrains with discontinuous heights. In this paper, an improved multi-baseline phase unwrapping (MB PU) method for GB-InSAR is proposed. This method combines the advantages of the cluster-analysis-based MB PU algorithm and the minimum cost flow (MCF) method. A cluster-analysis-based MB PU algorithm (CA-based MB PU) is firstly utilized to unwrap the clustered pixels with high phase quality. Under the topological constraints of a triangulation network, the connectivity graph of any non-clustered pixel is established with its adjacent unwrapped cluster pixels. Then, the absolute phase of these non-clustered pixels can be identified using the MCF method. Additionally, a spatial-distribution-based denoising algorithm is utilized to denoise the data in order to further improve the accuracy of the phase unwrapping. The DEM generated by one GB-InSAR is compared with that generated by light detection and ranging (LiDAR). Both simulated and experimental datasets are utilized to verify the effectiveness and robustness of this improved method. Full article

(This article belongs to the Special Issue Advances in Synthetic Aperture Radar Remote Sensing)

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12 pages, 10817 KiB

Open AccessTechnical Note

Performance Evaluation of Different SAR-Based Techniques on the 2019 Ridgecrest Sequence

by Marco Polcari, Mimmo Palano and Marco Moro

Remote Sens. 2021, 13(4), 685; https://doi.org/10.3390/rs13040685 - 13 Feb 2021

Cited by 1 | Viewed by 1689

Abstract

We evaluated the performances of different SAR-based techniques by analyzing the surface coseismic displacement related to the 2019 Ridgecrest seismic sequence (an Mw 6.4 foreshock on July 4th and an Mw 7.1 mainshock on July 6th) in the tectonic framework of the eastern [...] Read more.

We evaluated the performances of different SAR-based techniques by analyzing the surface coseismic displacement related to the 2019 Ridgecrest seismic sequence (an Mw 6.4 foreshock on July 4th and an Mw 7.1 mainshock on July 6th) in the tectonic framework of the eastern California shear zone (Southern California, USA). To this end, we compared and validated the retrieved SAR-based coseismic displacement with the one estimated by a dense GNSS network, extensively covering the study area. All the SAR-based techniques constrained the surface fault rupture well; however, in comparison with the GNSS-based coseismic displacement, some significant differences were observed. InSAR data showed better performance than MAI and POT data by factors of about two and three, respectively, therefore confirming that InSAR is the most consolidated technique to map surface coseismic displacements. However, MAI and POT data made it possible to better constrain the azimuth displacement and to retrieve the surface rupture trace. Therefore, for cases of strike-slip earthquakes, all the techniques should be exploited to achieve a full synoptic view of the coseismic displacement field. Full article

(This article belongs to the Special Issue Advances in Synthetic Aperture Radar Remote Sensing)

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10 pages, 3170 KiB

Open AccessLetter

Analysis of a Bistatic Ground-Based Synthetic Aperture Radar System and Indoor Experiments

by Hoonyol Lee and Jihyun Moon

Remote Sens. 2021, 13(1), 63; https://doi.org/10.3390/rs13010063 - 26 Dec 2020

Cited by 4 | Viewed by 2860

Abstract

Recent advancement of satellite synthetic aperture radar (SAR) techniques require more sophisticated system configurations such as the use of bistatic antennas or multi-frequencies. A ground-based experiment is a cost-effective and efficient way to evaluate those new configurations especially in the early stage of [...] Read more.

Recent advancement of satellite synthetic aperture radar (SAR) techniques require more sophisticated system configurations such as the use of bistatic antennas or multi-frequencies. A ground-based experiment is a cost-effective and efficient way to evaluate those new configurations especially in the early stage of the system development. In this paper, a ground-based synthetic aperture radar (GB-SAR) system was constructed and operated in a bistatic mode at Ku-band where a receiving antenna (Rx) follows a transmitting antenna (Tx) separated by a baseline B. A new bistatic GB-SAR focusing algorithm was developed by modifying a conventional range-Doppler algorithm (RDA), and its performance has been evaluated by comparing the results with those from a back-projection algorithm (BPA). The results showed good performance of RDA at far range approaching nominal resolutions of 9.4 cm in range and 4.5 cm in azimuth, but limited quality at near range due to the approximation used in RDA. Signals from three trihedral corner reflectors (CR) reduced with increasing B, showing a typical bidirectional scattering behavior of CR. This GB-SAR system will be a testbed for new SAR imaging configurations with variations in antenna positions and target properties. Full article

(This article belongs to the Special Issue Advances in Synthetic Aperture Radar Remote Sensing)

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