Corner Reflector Research Articles

Drone SAR Imaging for Monitoring an Active Landslide Adjacent to the M25 at Flint Hall Farm

Flint Hall Farm in Godstone, Surrey, UK, is situated adjacent to the London Orbital Motorway, or M25, and contains several landslide systems which pose a significant geohazard risk to this critical infrastructure. The site has been routinely monitored by geotechnical engineers following a landslide that encroached onto the hard shoulder in December 2000; current in situ instrumentation includes inclinometers and piezoelectric sensors. Interferometric Synthetic Aperture Radar (InSAR) is an active remote sensing technique that can quantify millimetric rates of Earth surface and structural deformation, typically utilising satellite data, and is ideal for monitoring landslide movements. We have developed the hardware and software for an Unmanned Aerial Vehicle (UAV), or drone radar system, for improved operational flexibility and spatial–temporal resolutions in the InSAR data. The hardware payload includes an industrial-grade DJI drone, a high-performance Ettus Software Defined Radar (SDR), and custom Copper Clad Laminate (CCL) radar horn antennas. The software utilises Frequency Modulated Continuous Wave (FMCW) radar at 5.4 GHz for raw data collection and a Range Migration Algorithm (RMA) for focusing the data into a Single Look Complex (SLC) Synthetic Aperture Radar (SAR) image. We present the first SAR image acquired using the drone radar system at Flint Hall Farm, which provides an improved spatial resolution compared to satellite SAR. Discrete targets on the landslide slope, such as corner reflectors and the in situ instrumentation, are visible as bright pixels, with their size and positioning as expected; the surrounding grass and vegetation appear as natural speckles. Drone SAR imaging is an emerging field of research, given the necessary and recent technological advancements in drones and SDR processing power; as such, this is a novel achievement, with few authors demonstrating similar systems. Ongoing and future work includes repeat-pass SAR data collection and developing the InSAR processing chain for drone SAR data to provide meaningful deformation outputs for the landslides and other geotechnical hazards and infrastructure.

Neutronics design of shutdown and control systems for a Zero Power Experiments of chloride-based molten salt fast reactor.

Nuclear power's role as a reliable, baseload, low-carbon source and its importance in achieving clean energy goals are being increasingly recognized with growing urgency around decarbonization of the global energy systems. However, to deliver a long-term sustainable solution, it is essential to develop innovative nuclear technologies for improving the fuel utilization and reducing the nuclear waste disposal challenge. Zero Power Reactors (ZPR) are an essential initial step for developing new nuclear technologies because they allow for testing and refinement in a safe environment before large-scale deployment. This paper discusses the design of a ZPR experiments for the development of iMAGINE, a novel chloride-based molten salt reactor technology. The paper presents a detailed analysis of the neutronic design for the shutdown and control systems of an experimental ZPR based on the iMAGINE molten salt reactor technology. The study concludes that a split-core design with a lower corner reflector as an extension of the lower annular reflector offers the most robust ZPR configuration, offering optimum operational margins and maneuverability. This design ensures safety, regulatory compliance, and sufficient control and shutdown performance for the successful development of the iMAGINE technology.

Implementation of Wide Angle FoV Radar Module for ADAS Systems

In this study, we propose the wide field of view (FoV) radar module for autonomous vehicles. The proposed wide FoV radar (WFR) module was constructed using of an RF module comprising wide beamwidth microstrip patch antennas, an AWR1642 radar sensor chip, and a control module. To achieve a wide FoV of 150° using the fabricated radar module, the 3-dB beamwidth characteristic of the applied microstrip patch antenna had to wider than 150°. The patch antenna was designed using a comb-line structure along 10-by-1 array structure, each radiator characterized by a shorted patch structure, such as a planar inverted-F antenna. The designed antenna was then fabricated on the same board surface as the sensor chip. To identify the characteristics of the implemented radar module, a trihedral corner reflector with a radar-cross-section of 180 m2 was used as the reflector target, and the CA-CFAR (cell averaging constant false alarm rate) target detection algorithm was applied. The measurement results, showed good detection performance of the radar in the view angle of 150°, from -75° to +75°, and a broad bandwidth of 4 GHz in the 77–81 GHz millimeter band. Therefore, the proposed WFR is applicable for used in blind spot detection sensors in autonomous vehicles.

ISAR Imaging Analysis of Complex Aerial Targets Based on Deep Learning

Traditional range–instantaneous Doppler (RID) methods for maneuvering target imaging are hindered by issues related to low resolution and inadequate noise suppression. To address this, we propose a novel ISAR imaging method enhanced by deep learning, which incorporates the fundamental architecture of CapsNet along with two additional convolutional layers. Pre-training is conducted through the deep learning network to establish the mapping function for reference. Subsequently, the trained network is integrated into the electromagnetic simulation software, Feko 2019, utilizing a combination of geometric forms such as corner reflectors and Luneberg spheres for analysis. The results indicate that the derived ISAR imaging effectively identifies the ISAR program associated with complex aerial targets. A thorough analysis of the imaging results further corroborates the effectiveness and superiority of this approach. Both simulation and empirical data demonstrate that this method significantly enhances imaging resolution and noise suppression.

Радиолокационный метод оценивания углового положения летательного аппарата на основе использования векторных свойств зондирующих сигналов

The radar monopulse method of determining the bearing and roll angles of an aircraft using a passive radio beacon with specified polarization scattering characteristics is considered, in which the reflected radio pulse contains complete information about the navigation elements of the aircraft flight. The passive beacon is two spatially separated in the horizontal plane radar polarization-anisotropic trihedral corner reflectors with horizontal and vertical natural polarizations, respectively. To determine the bearing and roll angles of an aircraft, probing pulse signals are used, the linear plane of polarization of which makes an angle π/4 with the horizontal plane. The bearing of the aircraft is estimated in this plane by a single reflected radio pulse at the output of a two-channel receiving device according to the measured phase difference between the horizontal and vertical polarized components of the received signal. The roll angle is estimated from the measured ratio of the amplitudes of the orthogonally linearly polarized components. Analytical expressions for determining the bearing and roll angles of the aircraft are obtained.

Geometric calibration of large-scale SAR images using wind turbines as ground control points

ABSTRACT The geometric positioning accuracy of synthetic aperture radar images is a key factor impacting their application, necessitating geometric calibration for improved accuracy. Traditional geometric calibration methods rely on ground calibration fields and supportive equipment such as corner reflectors, which often fall short in meeting both domestic and international geometric calibration demands. To enable convenient, swift, and large-scale or even global SAR calibration, we proposed a method that employs wind turbines as ground control points for SAR geometric calibration, and have constructed a wind turbine database for China. This database allows for precise positioning of wind turbine targets in SAR images. In this study, we applied the wind turbine geometric calibration model for the first time to four imaging modes of Gaofen-3 images. The results indicate that the positioning accuracy post-calibration ranges from 2.70 m to 8.72 m. The mean square error of positioning for the multi-scene calibration of 12 images spanning six provinces is less than 9 m, validating the method's applicability for large-scale calibration. Our proposed method presents a cost-effective solution for large-scale geometric calibration and can notably enhance the positioning accuracy of Gaofen-3 images, thereby increasing their application potential in remote sensing mapping, environmental monitoring, and resource management.

Target-based georeferencing of terrestrial radar images using TLS point clouds and multi-modal corner reflectors in geomonitoring applications

Terrestrial Radar Interferometry (TRI) is widely adopted in geomonitoring applications due to its capability to precisely observe surface displacements along the line of sight, among other key characteristics. As its deployment grows, TRI is also increasingly used to monitor smaller and more dispersed geological phenomena, where the challenge is their precise localization in 3d space if the pose of the radar interferometer is not known beforehand. To tackle this challenge, we introduce a semi-automatic target-based georeferencing method for precisely aligning TRI data with 3d point clouds obtained using long-range Terrestrial Laser Scanning (TLS). To facilitate this, we developed a multi-modal corner reflector (mmCR) that serves as a common reference point recognizable by both technologies, and we accompanied it with a semi-automatic data-processing pipeline, including the algorithms for precise center estimation. Experimental validation demonstrated that the corner reflector can be localized within the TLS data with a precision of 3–5 cm and within the TRI data with 1–2 dm. The targets were deployed in a realistic geomonitoring scenario to evaluate the implemented workflow and the achievable quality of georeferencing. The post-georeferencing mapping uncertainty was found to be on a decimeter level, matching the state-of-the-art results using dedicated targets and achieving more than an order of magnitude lower uncertainty than the existing data-driven approaches. In contrast to the existing target-based approaches, our results were achieved without laborious visual data inspection and manual target detection and on significantly larger distances, surpassing 2 km. The use of the developed mmCR and its associated data-processing pipeline extends beyond precise georeferencing of TRI imagery to TLS point clouds, allowing for alternatively georeferencing using total stations, mapping quality evaluation as well as on-site testing and calibrating TRI systems within the application environment.

Brightness temperature calculation of corner reflector on the sea surface and analysis of its jamming on ship recognition in passive millimetre-wave

Corner reflector, as a passive jammer, can generate a large radar cross section (RCS) to interfere with radar for target recognition. However, the impact of corner reflectors on passive millimetre-wave (PMMW) recognition is unclear. In this paper, based on ray tracing, the brightness temperature (TB) of corner reflectors is calculated. Ray tracing paths are used to analyze the impact of the sky, sea surface, and sun on the TB of corner reflectors. The antenna temperature of corner reflectors and their array at different distances is simulated and compared with that of a metal ship to evaluate their jamming performance. Four series of experiments measuring the antenna temperature of corner reflectors and the ship are conducted to verify the jamming performance. The results indicate that the contrast of corner reflectors is much smaller than that of ship target, causing little jamming for PMMW recognition.

High-gain H-plane SIW horn antenna loaded with dielectric slab for ku band low RCS applications

This article presents the design, simulation and experimental measurements of an H-Plane substrate-integrated waveguide (SIW) Horn Antenna Loaded with FR-4 Slab for Low RCS (radar cross section) applications like defence sector at Ku band (12-16 GHz). The design facilitates high gain and good impedance bandwidth (IBW). Also, the proposed structure has simple feed, planar structure with low-cost FR-4 substrate as dielectric material and decomposed into two parts. The former part of the antenna is the feeding part, which consists of two metallic plates filled with air substrate and a 90-degree corner reflector designed by shortening the metallic plates. The later part of the antenna is loaded with the FR-4 substrate that enhance the peak gain of the structure significantly. A simple coaxial probe is employed for the excitation of the corner reflector antenna. After the design is conferred by simulations, the same is fabricated and the performance measured experimentally. The experimental results are in close agreement with the simulated results. The design has yielded a 10 dB bandwidth of 30% (11.6–16 GHz), and a stable endfire radiation pattern over the entire bandwidth with a peak gain of 18.5 dBi at 14 GHz. Also, the design has F/B ratio > 20 dB over entire 10 dB bandwidth. Moreover, the antenna produced low RCS < 20 dB(m2) from −30° to +180° of elevation angle. Therefore antenna can’t easily detected from the radar system and suitable for defence applications.

Calibration of SAR Polarimetric Images by Covariance Matching Estimation Technique with Initial Search

To date, various methods have been proposed for calibrating polarimetric synthetic aperture radar (SAR) using distributed targets. Some studies have utilized the covariance matching estimation technique (Comet) for SAR data calibration. However, practical applications have revealed issues stemming from ill-conditioned problems due to the analytical solution in the iterative process. To tackle this challenge, an improved method called Comet IS is introduced. Firstly, we introduce an outlier detection mechanism which is based on the Quegan algorithm’s results. Next, we incorporate an initial search approach which is based on the interior point method for recalibration. With the outlier detection mechanism in place, the algorithm can recalibrate iteratively until the results are correct. Simulation experiments reveal that the improved algorithm outperforms the original one. Furthermore, we compare the improved method with Quegan and Ainsworth algorithms, demonstrating its superior performance in calibration. Furthermore, we validate our method’s advancement using real data and corner reflectors. Compared with the other two algorithms, the improved performance in crosstalk isolation and channel imbalance is significant. This research provides a more reliable and effective approach for polarimetric SAR calibration, which is significant for enhancing SAR imaging quality.

Polarimetric calibration of linear dual-pol SAR when corner reflectors are unavailable

Dual-pol synthetic aperture radar (SAR) has a higher resolution and broader swath than the quad-pol system. However, calibration of dual-pol SAR is challenging because only two-channel observations exist: HH&VH and HV&VV. In external calibration, the timely and periodic deployment of corner reflectors (CRs) increases costs when calibration factors vary over time. The effectiveness of such calibration can be increased when the target scattering in the scene is known. This study proposes a novel method that considers a distortion-free image as a benchmark to calibrate the receiving distortion of other products even within several years. The high-correlation targets in the time-series images present stable scattering mechanisms and provide a robust reference to estimate the radiometric calibration factor and channel imbalance (CI). The vegetation with azimuth symmetry is proposed to evaluate the crosstalk (XT) further. The novel technique is tested on dual-pol data of Gaofen-3 and Sentinel-1A. Results confirm that the residual XT is lower than − 35 dB, and the CI error is better than 0.25 dB with a 5° phase error after calibration. Our novel method can calibrate dual-pol data without using CR and reduce the workload in external calibration. The source codes are provided on the website for benchmarking and reproducibility purposes (http://jszy.whu.edu.cn/sl/zh_CN/jxzy/428540/list/index.htm).

Interferometric Calibration Model for the LuTan-1 Mission: Enhancing Digital Elevation Model Accuracy

The LuTan-1 (LT-1) mission, China’s first civilian bistatic spaceborne Synthetic Aperture Radar (SAR) mission, comprises two L-band SAR satellites. These satellites operate in bistatic InSAR strip map mode, maintaining a formation flight with an adjustable baseline to generate global digital elevation models (DEMs) with high accuracy and spatial resolution. This research introduces a dedicated interferometric calibration model for LT-1, tackling the unique challenges of the bistatic system, such as interferometric parameter coupling and the π-ambiguity problem caused by synchronization phase errors. This study validates the model using SAR images from LT-1 and Xinjiang corner reflector data, achieving interferometric phase accuracy better than 0.1 rad and baseline accuracy better than 2 mm, thereby producing high-precision DEMs with a height accuracy meeting the 5 m requirement.

An Identification Method of Corner Reflector Array Based on Mismatched Filter through Changing the Frequency Modulation Slope

The corner reflector is an effective means of interference for radar seekers due to its high jamming intensity, wide frequency band, and combat effectiveness ratio. Properly arranging multiple corner reflectors in an array can form dilution jamming that resembles ships, substantially enhancing the interference effect. This results in a significant decline in the precision attack efficiency of radar seekers. Hence, it is critical to accurately identify corner reflector array. The common recognition methods involve extracting features on the high-resolution range profile (HRRP) and polarization domain. However, the former is constrained by the number of corner reflectors, while the latter is affected by the accuracy of polarization measurement, both of which have limited performance on the identification of corner reflector array. In terms of the evident variations in physical structures, there must be differences in their scattering characteristics. To highlight the differences, this paper proposes a new method based on the concept of mismatched filtering, which involves changing the frequency modulation slope of the chirp signal in the filter. Then, the variance of width and intervals within a specific scope are extracted as features to characterize these differences, and an identification process is designed in combination with the support vector machine. The simulation experiments demonstrate that the proposed method exhibits stable discriminative performance and can effectively combat dilution jamming. Its accuracy rate exceeds 0.86 when the signal-to-noise ratio is greater than 0 dB. Compared to the HRRP methods, the recognition accuracy of the proposed algorithm improves 15% in relation to variations in the quantity of corner reflectors.

Analysis of the Dihedral Corner Reflector’s RCS Features in Multi-Resource SAR

Artificial corner reflectors are widely used in the vegetated landslide for time series InSAR monitoring due to their permanent scattering features. This paper investigated the RCS features of a novel dihedral CR under multi-resource SAR datasets. An RCS reduction model for the novel dihedral corner reflector has been proposed to evaluate the energy loss caused by the deviation between the SAR incident angle and the CR’s axis. On the Huangtupo slope, Badong county, Hubei province, tens of dihedral CRs had been installed and the TSX–spotlight and Sentinel-TOPS data had been collected. Based on the observation results of CRs with more than ten deviation angles, the proposed reduction model was tested with preferable consistency under a real dataset, while 2 dBsm of systematic bias was verified in those datasets. The maximum incident angle deviation in the Sentinel data overlapping area is over 12°, which leads to a 2.4 dBsm RCS decrease for horizontally placed dihedral CRs estimated by the proposed model, which has also been testified by the observed results. The testing results from the Sentinel data show that in high, vegetation-covered mountain areas like the Huangtupo slope, the dihedral CRs with a 0.4 m slide length can be achieve 1 mm precision accuracy, while a side length of 0.2 m can achieve the same accuracy under TSX–spotlight data.

Implementation of MIMO Radar-Based Point Cloud Images for Environmental Recognition of Unmanned Vehicles and Its Application

High-performance radar systems are becoming increasingly popular for accurately detecting obstacles in front of unmanned vehicles in fog, snow, rain, night and other scenarios. The use of these systems is gradually expanding, such as indicating empty space and environment detection rather than just detecting and tracking the moving targets. In this paper, based on our high-resolution radar system, a three-dimensional point cloud image algorithm is developed and implemented. An axis translation and compensation algorithm is applied to minimize the point spreading caused by the different mounting positions and the alignment error of the Global Navigation Satellite System (GNSS) and radar. After applying the algorithm, a point cloud image for a corner reflector target and a parked vehicle is created to directly compare the improved results. A recently developed radar system is mounted on the vehicle and it collects data through actual road driving. Based on this, a three-dimensional point cloud image including an axis translation and compensation algorithm is created. As a results, not only the curbstones of the road but also street trees and walls are well represented. In addition, this point cloud image is made to overlap and align with an open source web browser (QtWeb)-based navigation map image to implement the imaging algorithm and thus determine the location of the vehicle. This application algorithm can be very useful for positioning unmanned vehicles in urban area where GNSS signals cannot be received due to a large number of buildings. Furthermore, sensor fusion, in which a three-dimensional point cloud radar image appears on the camera image, is also implemented. The position alignment of the sensors is realized through intrinsic and extrinsic parameter optimization. This high-performance radar application algorithm is expected to work well for unmanned ground or aerial vehicle route planning and avoidance maneuvers in emergencies regardless of weather conditions, as it can obtain detailed information on space and obstacles not only in the front but also around them.

An Advanced Quality Assessment and Monitoring of ESA Sentinel-1 SAR Products via the CyCLOPS Infrastructure in the Southeastern Mediterranean Region

The Cyprus Continuously Operating Natural Hazards Monitoring and Prevention System, abbreviated CyCLOPS, is a national strategic research infrastructure devoted to systematically studying geohazards in Cyprus and the Eastern Mediterranean, Middle East, and North Africa (EMMENA) region. Amongst others, CyCLOPS comprises six permanent sites, each housing a Tier-1 GNSS reference station co-located with two calibration-grade corner reflectors (CRs). The latter are strategically positioned to account for both the ascending and descending tracks of SAR satellite missions, including the ESA’s Sentinel-1. As of June 2021, CyCLOPS has reached full operational capacity and plays a crucial role in monitoring the geodynamic regime within the southeastern Mediterranean area. Additionally, it actively tracks landslides occurring in the western part of Cyprus. Although CyCLOPS primarily concentrates on geohazard monitoring, its infrastructure is also configured to facilitate the radiometric calibration and geometric validation of Synthetic Aperture Radar (SAR) imagery. Consequently, this study evaluates the performance of Sentinel-1A SAR by exploiting the CyCLOPS network to determine key parameters including spatial resolution, sidelobe levels, Radar Cross-Section (RCS), Signal-to-Clutter Ratio (SCR), phase stability, and localization accuracy, through Point Target Analysis (PTA). The findings reveal the effectiveness of the CyCLOPS infrastructure to maintain high-quality radiometric parameters in SAR imagery, with consistent spatial resolution, controlled sidelobe levels, and reliable RCS and SCR values that closely adhere to theoretical expectations. With over two years of operational data, these findings enhance the understanding of Sentinel-1 SAR product quality and affirm CyCLOPS infrastructure’s reliability.

Compact auto-aligning interferometers with picometer precision

This research introduces a compact, auto-aligning interferometer engineered for measuring translations with a wide angular working range and picometer precision above 1Hz. It presents a design ensuring automatic beam alignment during movement through secondary reflection from a corner reflector. The sensor head, a 20×10×10mm3 all-glass quasi-monolithic structure, exhibits a displacement sensitivity below 1pm/Hz1/2 above 1Hz and a wide angular working range of ±200mrad. This versatile optical design holds promise to improve the sensitivity in applications such as laser ranging, optical seismometers, precision manufacturing, and metrology.

Dynamic Doppler Characteristics of Maritime Airborne Corner Reflector

The maritime airborne corner reflector (ACR) is a radar reflector that can measure wind speed in an unknown sea area in real time over a long distance. To improve our understanding of how the ACR works, we investigated the Doppler characteristics of the ACR for the first time from a dynamic perspective. First, we constructed a radar echo signal model of the ACR. Then, we obtained the dynamic Doppler characteristics through pulse Doppler processing and discussed the special phenomenon of Doppler broadening. Finally, we proposed a rectangular window decomposition method to analyze the inner principle of the Doppler broadening phenomenon in more detail. In conclusion, this study provides valuable insights into the Doppler characterization of an ACR from a dynamic viewpoint, which contributes to enriching the basic theory of this equipment.

Combining 77–81 GHz MIMO FMCW radar with frequency-steered antennas: a case study for 3D target localization

Abstract In this paper, we introduce a compact 6 × 8 channel multiple-input multiple-output frequency-modulated continuous-wave radar system capable of determining the three-dimensional positions of targets despite utilizing a linear virtual array. The compact system, containing two cascaded radar transceiver ICs, has 48 virtual channels. We conduct a direction of arrival estimation with these virtual channels to determine the azimuth angle. To overcome the spatial limitation of the linear array, we use frequency-steered transmit antennas, which vary their main lobe direction during the frequency chirp, allowing the elevation angle to be determined by using a sliding window fast Fourier transform algorithm. In this study, we present the system’s concept along with the associated signal processing. By taking measurements in different scenarios, each with differently placed corner reflectors, we investigate the capability of the system to separate adjacent targets concerning range, azimuth, and elevation. These measurements are additionally employed to point out the design trade-offs inherent to the system.

Vibration Measurement of High-Speed Railway Bridges Based on GB-MIMO Interferometric Radar

As a novel type of ground-based interferometric radar, ground-based multiple-input multiple-output (GB-MIMO) interferometric radar utilizes multiple transmitting and receiving antennas to compose a specific structure and acquire a large synthetic aperture. Using electronic beam scanning instead of common mechanical scanning, GB-MIMO interferometric radar can achieve two-dimensional high-resolution imaging with image acquisition frequency at tens of Hertz, and has the ability to perform bridge health monitoring through vibration measurement. This study introduces the basic principle of the MIMO technique and the first Chinese made GB-MIMO interferometric radar. Experiments taken on a corner reflector and a high-speed railway bridge are respectively utilized to verify the vibration measurement ability of this novel type of GB-MIMO interferometric radar