Radar Research Research Articles

Plakun Burial Ground: a new discovery of the well-known site based on the results of the aerial lidar and ground penetrating radar research

The article presents findings of complex interdisciplinary researches of a group of sopkas in the Plakun terrain feature. The monument is part of the Staroladozhky archaeological complex located in Volk- hovsky district, Leningrad region, 120 km east of St. Petersburg. The sopkas are one of the main landmarks of the region. They are high steep embankments 11 – 30 m in diameter and 3 – 8 m high. They date back to the 8th – 10th centuries. The ethnicity of their makers is uncertain. Historiographical data suggest that the monu- ment consisted of 6 sopkas divided into clusters 3 embankments each. In 1955, the southernmost sopka was excavated for demolition. In 2022 – 2023, scheduled scientific researches and Russian Science Foundation Grant No. 23-18-00515 implied an aerial laser scanning of the monument territory. The area was scanned at the attitude of 70 – 90 m with a DJI Matrice 300 RTK drone and an L1 LiDAR from a DJI D-RTK ground station. The coordinates are referenced in LCS-47 Zone 2 with Spectra Epoch 50 GNSS receiver and amended by Geospider survey station network. The findings allow to distinguish a range of small hills in two groups of remaining sopkas. The standard presentation of Digital Elevation Model (DEM) clearly distinguishes 5 remaining large rounded embankments and piles of the excavated southernmost one. However, the research matches several relief color gradations. The study combines several DEM copies in QGIS geographic information system. Consequently, it is revealed that the chain of remaining embankments includes 4 rounded elevations. 3 of them resemble ploughed embankments. In 2023, two identified elevations were studied with OKO-2 ground penetrating radar equipped with a probe antenna which radiates 100 and 700 MHz pulses. The research involves gridding the area of the alleged lost ploughed sopkas and one apparent embankment. The profiles of the site were double-scanned. The radargrams reveal common structure features in the hills and sopka such as contrast mound foundations, heterogeneous centers, multi-layered structures and local depressions in the top layer around 0.5 meters thick. The findings suggest that 3 out of 4 hills can be viewed as demolished embank- ments of a sopka burial. The fourth one requires additional research.

High-resolution SAR optoelectronic processor based on sensor-less adaptive optics

Studying phase error is central to synthetic aperture radar (SAR) research. Phase error due to the real motion status of the SAR platform and propagation effects can reduce the utility of high-resolution SAR images even with theoretical estimation-based phase error correction. Adaptive optics (AO) can be used to correct optical aberrations. This study proposes an advanced, high-resolution SAR optoelectronic processor by integrating conventional processors with sensor-less AO techniques. This processor provides accurate adaptive phase error correction capabilities. The processing results of SAR echo data demonstrate the effectiveness of the proposed system in adaptive phase error correction and imaging improvement.

MOSAIC – a neglected fragment of UK’s computer story

The development of MOSAIC (Ministry of Supply Automatic Integrator or Computer), derived from Alan Turing’s innovative design for an Automatic Computing Engine (ACE) is examined. MOSAIC reflects some of the important technology developments in stored program computing and the nascent UK computer industry. The contribution from the British Post Office (BPO), particularly the Dollis Hill research establishment, in developing MOSAIC is significant. Further development of the machine took place following its deployment at the Radar Research Establishment (RRE) in Malvern, demonstrating aspects of the ongoing evolution of the computer field. Its development is described with reference to the main ACE development allowing its place in the evolution of computer architectures to be evaluated.

High-resolution wide-swath SAR imaging with multifrequency pulse diversity mode in azimuth multichannel system

ABSTRACT High-resolution wide-swath (HRWS) imaging has emerged as a focal point in synthetic aperture radar (SAR) research. However, conventional SAR systems face challenges in achieving both high azimuth resolution and wide swath simultaneously due to the minimum antenna area constraint. In this paper, we propose a HRWS imaging method based on multifrequency pulse diversity (MFPD) and azimuth multichannel (AMC) technique, capable of resolving range and Doppler ambiguities concurrently. In MFPD mode, range ambiguous echoes can be separated by matched filters in the range frequency domain, as multifrequency pulses are transmitted by a single channel in the transmitter. To further enhance the ambiguity resolution ability of the system and address azimuth incoherence, a novel scheme applying the MFPD to AMC system is proposed, categorized into two distinct scenarios. 1) Uniform Sampling: This scenario satisfies the displaced phase centre antenna condition. Under this condition, high range resolution imaging can be achieved through spectrum splicing in range frequency domain, simultaneously resolving Doppler ambiguity. 2) Non-uniform Sampling: In this scenario, the ambiguous echoes are processed by spatial digital beamforming and spectrum splicing in two-dimensional frequency domain. Finally, the HRWS imaging can be obtained by performing the traditional SAR algorithm. Furthermore, the proposed method can synthesize a wideband signal from multifrequency signals, thereby enhancing the feasibility of super-high-resolution imaging. Simulation results demonstrate the effectiveness of the proposed method.

Design and performance validation of CWT-MCA based interference mitigation for automotive radars

Interference mitigation has been a vital area of focus within the realm of automotive radar research, holding paramount importance for augmenting advanced driver-assistance capabilities, particularly in vehicle-dense scenarios. This paper presents a novel interference mitigation scheme based on continuous wavelet transform and morphological component analysis (CWT-MCA). This method, in essence, transforms the time-domain signal into the time-frequency domain, subsequently enabling the direct separation of target and interference components, thereby circumventing the necessity for interference detection and identification. Additionally, this paper introduces a series of MCA algorithms grounded in various transform domains, which are subsequently compared with the traditional linear prediction based approach. We show through comprehensive numerical simulations and real-data experiments that CWT-MCA algorithm exhibits markedly superior interference mitigation performance while offering lower computational complexity, which makes it well-suited for real-time implementation in automotive radar systems.

Python Indian Weather Radar Toolkit (pyiwr): An open-source Python library for processing, analyzing and visualizing weather radar data

The Python Indian Weather Radar Toolkit, abbreviated as "pyiwr", is an open-source Python library tailored for the purpose of handling data from the Indian Doppler Weather Radar (DWR). This paper provides a comprehensive overview of the pyiwr, which serves as a toolkit to read, analyze, process, and visualize weather radar data. Apart from this, the toolkit offers a range of robust functions implementing various algorithms covering several aspects of the radar data processing and quality control that facilitate the manipulation and analysis of weather radar data. To demonstrate the practical applicability of pyiwr, various case studies are presented, focusing on processing raw reflectivity data (clutter correction), Quantitative Precipitation Estimation (QPE) using Z-R relationship and time-series analysis of reflectivity and rain intensity, both spatially as well as at a specific location, during various meteorological events. This module enhances the accessibility and compatibility of radar data, enabling researchers, weather forecasters, and hydrologists to efficiently work with DWR data (particularly Indian DWR) that fosters advancements in weather radar research and applications. The open availability of pyiwr's source code on GitHub ensures that researchers and practitioners can not only access the toolkit but also contribute to its ongoing development.

Bibliometric Analysis of Weather Radar Research from 1945 to 2024: Formations, Developments, and Trends.

In the development of meteorological detection technology and services, weather radar undoubtedly plays a pivotal role, especially in the monitoring and early warning of severe convective weather events, where it serves an irreplaceable function. This research delves into the landscape of weather radar research from 1945 to 2024, employing scientometric methods to investigate 13,981 publications from the Web of Science (WoS) core collection database. This study aims to unravel, for the first time, the foundational structures shaping the knowledge domain of weather radar over an 80-year period, exploring general features, collaboration, co-citation, and keyword co-occurrence. Key findings reveal a significant surge in both publications and citations post-1990, peaking in 2022 with 1083 publications and 13832 citations, signaling sustained growth and interest in the field after a period of stagnation. The United States, China, and European countries emerge as key drivers of weather radar research, with robust international collaboration playing a pivotal role in the field's rapid evolution. Analysis uncovers 30 distinct co-citation clusters, showcasing the progression of weather radar knowledge structures. Notably, deep learning emerges as a dynamic cluster, garnering attention and yielding substantial outcomes in contemporary research efforts. Over eight decades, the focus of weather radar investigations has transitioned from hardware and software enhancements to Artificial Intelligence (AI) technology integration and multifunctional applications across diverse scenarios. This study identifies four key areas for future research: leveraging AI technology, advancing all-weather observation techniques, enhancing system refinement, and fostering networked collaborative observation technologies. This research endeavors to support academics by offering an in-depth comprehension of the progression of weather radar research. The findings can be a valuable resource for scholars in efficiently locating pertinent publications and journals. Furthermore, policymakers can rely on the insights gleaned from this study as a well-organized reference point.

Parameter estimation of ground moving targets in synthetic aperture radar systems based on vortex echo data

Ground Moving Target Indication is a critical field within synthetic aperture radar (SAR) research, as traditional SAR images are defocused and displaced due to the target’s trajectory-direction velocity and radial velocity, respectively. Therefore, an accurate estimation of the target’s motion parameters is required. This study introduces a two-dimensional method for estimating target motion parameters using vortex SAR. It utilises the Bessel magnitude and spatial phase term from vortex echo data to calculate the pitch and azimuth angle, from which the motion parameters of ground slow-motion targets are derived. The proposed algorithm operates faster and has a lower computational cost than the traditional parameter estimation algorithm. Its efficacy was confirmed through simulation experiments and mean square error analysis of the estimated parameters.

Шынайы георадар деректері үшін радиолокациялық зерттеулер әдістері мен алгоритмдерін талдау

Georadar research is gaining popularity today and actively used in various fields of activity: archaeology, soil studies, groundwater, ecology and others. Moreover, it is used for inspecting highways to assess the thickness of the coating and identify the causes of damage to the coatings, for diagnosing railway tracks, etc. A device that uses the principles of ground penetrating radar is called a georadar. When the GPR moves across the environment under study, a radarogram (profile) is obtained. The main task of interpreting radarograms is to determine the geophysical section of the environment. To solve these problems, algorithms based on engineering technical methods, and computer and mathematical modeling are used. The engineering and technical method of interpreting a radarogram is a comparison of the experiment with already known types of radarograms. The article provides an analysis of radar research methods and algorithms for real ground penetrating radar data. A detailed analysis of the developed domestic algorithms is provided.

Yutu-2 Radar Observations at the Chang’E-4 Landing Site: The Shallow Geological Structure and Its Dielectric Properties

China has successfully carried out five lunar exploration missions since 2007. These missions indicate that China has successfully implemented a three-step lunar exploration program of “orbiting, landing, and returning”. Among them, the Lunar Penetrating Radar (LPR) carried by the Yutu-2 rover in the Chang’E-4 (CE-4) mission is the only one still operating on the far side of the Moon. Up to now, the Yutu-2 radar has measured a large amount of scientific data, and its observations are of great significance to human cognition of the geological evolution of the lunar surface and the exploration of possible lunar in situ resources. This paper reviews the scientific results obtained by previous researchers based on the radar exploration data of Yutu-2, focusing mainly on three aspects, e.g., the geological structure of the shallow surface at the CE-4 landing site, the dielectric properties of the shallow subsurface materials and the special geological features. Finally, the prospects of Yutu-2 radar research priorities and future exploration, and the application trend of Moon-based ground-penetrating radar are given.

A novel method of estimating atmospheric boundary layer height using a 205 MHz VHF radar

The present study proposes a novel methodology for the estimation of atmospheric boundary layer height (ABLH) using data from a 205 MHz VHF (very high frequency) radar installed at the Advanced Centre for Atmospheric Radar Research, Cochin University of Science and Technology, India. Using a year-long dedicated experimental campaign involving collocated, concurrent radar and radiosonde operations in 2021, clear-sky days were identified for the analysis in order to avoid any further ambiguity in the results. The reference ABLH is derived from the mixing ratio and its gradient profiles from the radiosonde data. A new method has been devised to estimate the boundary layer height using the dataset from radar by combining three parameters, viz., signal-to-noise ratio, wind speed and wind direction. The ABLH is identified as that height at which the sum of the normalized standard deviations of three parameters peaks and subsequently decreases abruptly and substantially above it. This method has been verified against the ABLH estimated from four other variables from the radiosonde data, and a strong correlation (r = 0.91 at 99 % confidence level) between the ABLH derived from both methods has been obtained. This study extends ample opportunity to explore the high temporal variability such as the diurnal cycle of ABLH from the radar, unlike sparsely available radiosonde measurements.

Towerpy: An open-source toolbox for processing polarimetric weather radar data

Weather radars produce high spatial and temporal resolution observations of precipitation events. Over the years, weather radar operators have updated their radar networks to exploit the latest technological advancements. One of the most significant improvements in this matter was providing the radars with polarimetric capabilities, as this allows the radars to gather more detailed information about the precipitation targets’ shape, size, phase, and orientation. The radar research community has been working along with these advancements to develop robust algorithms that boost the radar data applications, such as radar quantitative precipitation estimation (QPE), rain microphysics analysis, nowcasting of precipitation or numerical weather prediction based on radar measurements. Some of these algorithms have been implemented in open-source toolboxes that aim to facilitate the processing and quality control of radar data produced by different radar systems. However, these open-source projects have not yet included a chain process tailored to the UK radar research context. This paper presents a TOolbox to process WEather Radar data in PYthon (Towerpy). Towerpy can read, process and display polarimetric radar data from different radar systems, but it is specially customised for data produced by the UK Met Office radar network. Towerpy is built upon robust algorithms that cover various aspects of the radar data quality control (e.g., calibration of radar measurements, identification of non-meteorological echoes, attenuation correction, among others) and the computation of radar rainfall rates. Additionally, a radar processing chain was devised using the Towerpy modules to produce radar rainfall estimates. Raw polarimetric radar measurements collected by the UK Met Office radar network throughout the UK’s wettest day on record were used as input for this processing chain. The results confirm that Towerpy is a powerful radar research tool and demonstrate its ability to generate functional radar QPE that can be used to improve operational radar rainfall products.

Role of Radar Cross Section Facilities, In a Radar and Electronic Warfare Defence Research and Evaluation Capability

This paper demonstrates the role of Radar Cross Section (RCS) facilities, consisting of modelling and simulation (M&S), Hardware in the Loop- (HWIL) and field Test and Evaluation (T&E) environments, in a Radar and Electronic Warfare (EW) Defence Research and Evaluation capability. The link between the development and utilisation of radar and EW facilities and the scientific process is illustrated by examples

Joint Collaboration on Comparing NOAA’s Ground-Based Weather Radar and NASA–JAXA’s Spaceborne Radar

Abstract The National Aeronautics and Space Administration (NASA) and National Oceanic and Atmospheric Administration (NOAA) have a long and successful history of weather radar research. The NOAA ground-based radars—WSR-88D network—provide nationwide precipitation observations and estimates with advanced polarimetric capability. As a counterpart, the NASA–JAXA spaceborne radar—the Global Precipitation Measurement Dual-Frequency Precipitation Radar (GPM DPR)—has global coverage and higher vertical resolution than ground-based radars. While significant advances from both NOAA’s WSR-88D network and NASA–JAXA’s spaceborne radar DPR have been made, no systematic comparisons between the WSR-88D network and the DPR have been done. This study for the first time generates nationwide comprehensive comparisons at 136 WSR-88D radar sites from 2014 to 2020. Systematic differences in reflectivity are found, with ground radar reflectivity on average 2.4 dB smaller than that of the DPR (DPR version 6). This research found the discrepancies between WSR-88D and DPR arise from different calibration standards, signal attenuation correction, and differences in the ground and spaceborne scattering volumes. The recently updated DPR version 7 product improves rain detection and attenuation corrections, effectively reducing the overall average WSR-88D and DPR reflectivity differences to 1.0 dB. The goal of this study is to examine the systematic differences of radar reflectivity between the NOAA WSR-88D network and the NASA–JAXA DPR and to draw attention to radar-application users in recognizing their differences. Further investigation into understanding and alleviating the systematic bias between the two platforms is needed.

The research on phased array radar technology and its applications

Radar technology first appeared in 1842, proposed by the Austrian physicist Doppler. Over time, radar has had different applications in many fields. Among them, the use and advanced degree of radar in the military field is the highest. It was used to detect enemies to attack or defense. In recent decades, a more advanced phased array radar can replace the traditional radar in the military. In this report, it is focused on the principle and function of phase array radar and the applications and development of it are also discussed. Research on current phased array radar will help to develop higher performance and lower power consumption radar in the future. Combining the advantages and disadvantages of phased array radar helps to have a clearer view on the future direction of radar research.

Passive Radar Tracking in Clutter Using Range and Range-Rate Measurements

Passive bistatic radar research is essential for accurate 3D target tracking, especially in the presence of missing or low-quality bearing information. Traditional extended Kalman filter (EKF) methods often introduce bias in such scenarios. To overcome this limitation, we propose employing the unscented Kalman filter (UKF) for handling the nonlinearities in 3D tracking, utilizing range and range-rate measurements. Additionally, we incorporate the probabilistic data association (PDA) algorithm with the UKF to handle cluttered environments. Through extensive simulations, we demonstrate a successful implementation of the UKF-PDA framework, showing that the proposed method effectively reduces bias and significantly advances tracking capabilities in passive bistatic radars.

Эволюция межпланетных миссий радиолокационных исследований планет Солнечной системы с учетом развития бортовых радиолокационных средств космических аппаратов

The paper gives a detailed retrospective review of radio studies of the Solar system planets. The history of missions and the evolution of the spacecraft designed for radar research are considered. It presents analysis of the options in constructing the existing spacecraft radar facilities for interplanetary research. On the basis of this analysis, the appearance of a new generation of radar equipment for interplanetary research missions is proposed. Principles of construction and technical solutions for creation of the onboard radar equipment for the promising research spacecraft were determined. Promising missions of the Venus radar survey were analyzed, and approaches to construction of the spacecraft radar equipment based on the advanced technical solutions were proposed.

On the question of constructing the distribution of the flux density of meteoroids over the celestial sphere in ground-based single-position radar measurements of meteor activity and velocity: The experience of past years

The construction of the distribution of the flux density of meteor bodies over the celestial sphere is necessary for solving problems of meteor astronomy and others. To construct such distributions, experimental data on the coordinates of meteor radiants are needed. Meteor radars provide determination of the coordinates of the radiant in the presence of one transmitter and three spaced receivers. In this research, we are talking about ground-based meteor observations of the number of meteors using single-station meteor back-skatter radars as simpler than measurements of meteor radiants. In the 1950–80s in Kharkiv (Ukraine), active meteor radar research was carried out, both simple single-station and complex with remote points. The authors in the 1980s were participants in the meteor international program GLOBMET (Kashcheev, 1982; Roper, 1990). At that time, they modified an algorithm for calculating the flux density of meteor bodies over the heliocentric celestial sphere by number, range and velocity for radar observations with using single-station meteor backscatter. An algorithm was developed for dividing the celestial sphere into regions with a combination of “celestial” and “antenna” regions with a binding of a meteor to the antenna region in radar observations with a narrowly directed antenna without goniometr. This algorithm was applied to specific equipment for measuring the number of meteors by the Kharkiv Meteor Automated Radar System (MARS), 31.1 MHz. The correctness of the algorithm was confirmed by constructing the density distribution of the incident flux over the celestial sphere based on measurements in October-December 1989. The distributions are constructed using two methods for approximating the amplitude-time characteristics of signals. The results represent the experience of past years, which may be of interest as a scientific and technical solution.

A MIMO moving target detection radar with optimal transmit and receive weightage

Target detection using multiple-input multiple-output (MIMO) radar has recently gained popularity in radar research due to its ability to mitigate the target radar cross-section fading and substantial spatial diversity gain. Recently, an optimal MIMO radar detector, including optimal transmit and receive weightage, has been proposed for the detection of steady targets. A moving target differs the scenario from a steady target case due to its Doppler. Hence, the optimal detector of a steady target case does not work for the case of a moving target. Therefore, in this paper, we proposed a MIMO radar detector for the context of moving targets, including optimal transmit and receive weight schemes. For obtaining the proposed detector, knowledge about the target fading that can be applied to a moving target scenario is a prerequisite. Therefore, we proposed to use a training mechanism in which a few transmit pulses are introduced once in every coherent processing interval, and the corresponding target returns are used to estimate the target fading. However, in a moving target scenario, the target returns are Doppler-steered versions of the target fading. Therefore, it is proposed to compensate the Doppler for target fading estimation by matching a steering vector to the target returns. This type of use of online estimation of the target fading characteristics and applying it for moving target detection is the first of its kind in radar research. The proposed radar is shown to outperform the state-of-the-art MIMO radars addressed in the literature.

Youth and social cohesion in times of the COVID pandemic: Most negatively affected? Most resilient?

The current article reports findings from three large representative survey studies in the German federal state of Baden-Württemberg. The studies are part of the Social Cohesion Radar research initiative of Bertelsmann Stiftung. The article explores the role of social cohesion in the relationship between COVID-based objective and subjective strain, on the one hand, and future optimism for the youth, citizens of active age, and the elderly. In particular, it focuses on the question whether the degree of social cohesion perceived by respondents moderates the relationship between strain and optimism in the different age groups. Findings show that the impact of perceived social cohesion in people's life context has only modest effects on the relationship between strain and future optimism. Yet, the results show that having been affected by COVID in one way or the other leads to a small but persistent bounce-back effect. People affected by COVID tend to look more optimistic into the future than those who were not.