Search Results (7)

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. Full article

The target simulation of airplanes is an important research topic. It is particularly important to find the right balance between high performance and low cost. In order to balance the contradictions between realistic target simulations and controllable costs, the scientific formulation of the performance parameters of target simulation is the key to achieving high performance. This paper proposes an intelligent simulation technology based on RCS imaging simulation through the combination of 60° variation corner reflector and a Luneberg lens reflector. It is designed to simulate several important RCS characteristics of the aircraft. At the same time, the different RCS images are automatically shifted to the corresponding gear position to achieve the purpose of simulation, and the price is low and the performance is good. It can be used for the training of radar target searching. Full article

This article deals with the analysis of backscattering at automatic target recognition (ATR) by ground-based radar located on rough terrain surfaces, using the properties of wave polarization. The purpose of the study is to examine and compare linear and circular polarized reflected waves, which can be described by decomposition theorems. Coherent decompositions (Pauli, Krogager, Cameron decomposition) are considered in the case of a rough terrain, for which the advantage of the Pauli decomposition has been shown. The article demonstrates an approach to the extraction of polarization signal backscattering data for two types of vehicles with different profiles. It is shown that the measurement results can be calibrated by a corner reflector that takes into account the properties of the ground surface, and further used for ATR based on supervised learning algorithms. The accuracy of object classification was 68.1% and 54.2% for the signal generated by linearly and elliptically polarized waves, respectively. Based on these results, we recommend using a linearly polarized wave as an object recognition mechanism. At the same time, any reflected depolarized wave significantly reshapes the structure due to the rotation of the object profile and the influence of a rough surface (vegetation fluctuations). This explains the low recognition accuracy in general. Full article

C-SAR/01, the successor of China’s Gaofen-3 Satellite, which launched on 23 November 2021, is the first synthetic aperture radar (SAR) satellite to be launched in China’s civil space infrastructure plan and has served as an invaluable data resource. Radiometric calibration and validation are prerequisites for the quantitative application of SAR data. In this study, the radiometric calibration experiments of C-SAR/01 data of the ultra-fine strip (UFS) and fine strip I (FSI) modes were conducted applying flexible automatic triangular trihedral corner reflectors deployed in Xilinhot SAR satellite calibration and validation site. Accordingly, the image quality and radiometric calibration accuracy were evaluated. The results show that the spatial resolution, peak sidelobe ratio, and integrated sidelobe ratio of UFS and FSI mode data of C-SAR/01 are better than those of the design indexes, and the calibration results from the integral method are more stable than those from the peak method. Furthermore, the standard deviation of the calibration constant for UFS mode data is 0.234 dB, with the relative and absolute calibration accuracies obtained as 0.233 and 0.532 dB, respectively, whereas the standard deviation calibration constant for FSI mode data is 0.198 dB, with its relative and absolute calibration accuracies evaluated as 0.199 and 0.333 dB, respectively. Full article

The intensive development of both interferometric technology and sensors in recent years allows Interferometric Synthetic Aperture Radar (InSAR)-based applications to be accessible to a growing number of users. InSAR-based services now cover entire countries and soon even the whole of Europe. These InSAR systems require massive amounts of computer processing power and significant time to generate a final product. Most, if not all, of these projects have a limited “monitoring component”, aimed at historical analysis but are rarely, if ever, updated. Consequently, the results do not necessarily meet every purpose or specific user requirement. It is now clear that the increasing computing capacity and big data provided by the sensors have initiated the development of new InSAR services. However, these systems are only useful when linked to specific real-world operational problems. Continuous monitoring of a country’s ageing water management infrastructure has become an increasingly critical issue in recent years, in addition to the threats posed by climate change. Our article provides a comprehensive overview of a nationwide, dedicated, operational InSAR application, which was developed to support the operational work of the Hungarian Disaster Management Service (HDMS). The objective was to provide monthly monitoring of 63 water facilities, including 83 individual objects, distributed throughout Hungary, in combination with the development of a near real-time warning system. Our work involved the compilation of a completely new InSAR System as a Service (SaaS) which incorporates user requirements, preparatory work, the compilation of the Sentinel-1 automatic processing pipeline, the installation of corner reflectors, a special early warning system, and a dedicated user interface. The developed system can automatically start to evaluate the S1 measurements within 24 h of downloading the data into the system storage forward the results toward the warning system before the next image arrives. Users are provided with detailed information on the stability of 70% of the 83 water facility objects monitored through the dedicated user interface. The additional early warning system currently operates as a preliminary “spatial decision support system”, but the HDMS is willing to make it fully operational over the next few years. Full article

Over the past few decades, the global population and the built environment’s vulnerability to natural hazards have risen dramatically. As a result, decisive actions, such as the SENDAI framework, have emerged to foster a global culture of successful disaster risk reduction policies, including actions to mitigate the social and economic impact of geohazards. The effective study of natural disasters requires meticulous and precise monitoring of their triggering factors, with ground- and space-based techniques. The integration of GNSS and SAR observations through the establishment of permanent infrastructures, i.e., Continuously Operating Reference Stations (CORS) networks and arrays of Corner Reflectors (CRs), may form a seamless ground displacement monitoring system. The current research literature provides fragmented guidelines, regarding the co-location of SAR and GNSS permanent infrastructures. Furthermore, there exist no guidelines for the determination of the most suitable locations using a holistic approach, in terms of criteria and required data. The purpose of this paper is to present a semi-automatic multicriteria site suitability analysis and evaluation of candidate sites for the installation of a permanent CORS and two CRs; one for each pass, taking into account various parameters and criteria. The first results demonstrate that the collocation of SAR and GNSS permanent infrastructures, utilizing a holistic criteria-based approach, is successful and complies with all the literature’s requirements. Full article

Artificial radar reflectors, such as corner reflectors or transponders, are commonly used for radiometric and geometric Synthetic Aperture Radar (SAR) sensor calibration, SAR interferometry (InSAR) applications over areas with few natural coherent scatterers, and InSAR datum connection and geodetic integration. Despite the current abundance of regular SAR time series, no free and open-source software (FOSS) dedicated to analyzing SAR time series of artificial radar reflectors exists. In this paper, we present a FOSS Python toolbox for efficient and automatic estimation of: (i) the clutter level of a particular site before a corner reflector installation, (ii) the Radar Cross Section (RCS) to track a corner reflector’s performance and detect outliers, for example, due to damage or debris accumulation, (iii) the Signal-to-Clutter Ratio (SCR) to predict the positioning precision and the InSAR phase variance, (iv) the InSAR displacement time series of a corner reflector network. We use the toolbox to analyze Sentinel-1 SAR time series of the network of 23 corner reflectors for InSAR monitoring of landslides in Slovakia. Full article