Radar Experiment Research Articles

A novel approach for regularization matrix construction and its application in SBAS deformation model inversion

ABSTRACTThe Tikhonov regularization reduces the ill-conditioned nature of an equation by introducing a regularization parameter and a regularization matrix to correct an ill-conditioned matrix. Therefore, the appropriate determination of the regularization matrix can increase the reliability of solutions. In this paper, a regularization matrix construction approach based on the minimum mean square error is proposed. The approach constructs the regularization matrix using the small singular value vectors. The boundary of small singular values that satisfies the minimum mean square error is determined by comparing the reduced variance and introduced bias. The boundary value is utilized to construct the regularization matrix to obtain a more reliable parameter estimation. The proposed approach is applied to the small baseline subset interferometric synthetic aperture radar deformation inversion model experiment, and the feasibility and effectiveness of the approach are verified. Compared with the original approach of determining small singular values, the proposed approach is more stable and reliable, and it improves the accuracy of the Tikhonov regularization.

Exploring Polarimetric Phase of Microwave Backscatter from Typha Wetlands

Despite their natural and societal importance, wetlands are becoming increasingly threatened. The goal of this study is to investigate the potential of polarimetric synthetic aperture radar (SAR) for monitoring one important vegetation constituent of wetlands: Typha. An idealized cylindrical scattering model is developed to portray double bounce microwave scattering from Typha stalks. Then a thin cylinder Brewster angle is introduced; relating the co-pol phase difference (CPD) of Typha to its relative permittivity. Full polarization Radarsat-2 data were acquired for a variety of dates and incidence angle ranges in order to validate the scattering model. The dependence of CPD on incidence angle is found to be consistent with the model. The evolution of CPD with seasonal senescence was also investigated. Despite some agreement with expected trends in vegetation moisture, there are anomalies that remain unexplained; possibly due to ecosystem change. This suggests the need for radar scatterometer experiments in a controlled environment to better explore the dependence of CPD on incidence angle and seasonal change. Last, cross-pol phase difference (XPD) histograms support other research in demonstrating the existence of coherent depolarization in Typha scattering. Additional modeling, entailing the detailed structure of the vegetation, will be necessary to understand this behavior.

Robust sequential high‐resolution range profile recognition based on the infinite conditional restricted Boltzmann machine

Feature extraction for radar high-resolution range profiles (HRRPs) is an essential procedure for robust target recognition based on radar HRRPs. It is almost always better to utilise multiple HRRPs from the target than a single HRRP. The commonly used recognition techniques are not robust enough to extract features from HRRP sequences, especially when there is not enough training data. In this study, the authors present a compact model named the infinite conditional restricted Boltzmann machine (iCRBM) for jointly feature learning and recognition of radar HRRPs. The model is developed from the conditional restricted Boltzmann machine, which is a powerful model for representing high-dimensional and multi-modal conditional distributions. Unlike ordinary RBMs, iCRBM can automatically select the model complexity according to the data, which especially suits for the case of large data dimensionality and small training dataset. A multi-scale structure is also proposed for learning multiple scales of temporal/spatial dependencies. Two types of radar HRRP recognition experiments were conducted to validate the efficiency and robustness of iCRBM: the multi-view HRRP recognition and the small aperture HRRP recognition. The results indicate that, the proposed model can be more adaptive at learning the feature of HRRPs than other common methods. The multi-scale structure is helpful for better recovering missing HRRP samples from non-consecutive sequences.

Quantum Two-Mode Squeezing Radar and Noise Radar: Correlation Coefficient and Integration Time

Quantum two-mode squeezing (QTMS) radars and noise radars perform matched filtering of the received signal using a reference signal stored within the radar. Their target detection performance depends on the correlation between the received and reference signals, and the improved detection performance of QTMS radars over noise radars is due to the fact that it has an increased correlation. In this paper, we present a novel way of understanding how detection performance depends on the correlation by relating the correlation to the integration time. Concretely, we prove that increasing the correlation by a given factor is equivalent to increasing the integration time by the square of that factor. We apply this result to a recent QTMS radar experiment where the increase in correlation was approximately a factor of 3. This was found to be equivalent to increasing the integration time by a factor of 9, thus confirming the validity of our result and approximation.

Rucio beyond ATLAS: experiences from Belle II, CMS, DUNE, EISCAT3D, LIGO/VIRGO, SKA, XENON

For many scientific projects, data management is an increasingly complicated challenge. The number of data-intensive instruments generating unprecedented volumes of data is growing and their accompanying workflows are becoming more complex. Their storage and computing resources are heterogeneous and are distributed at numerous geographical locations belonging to different administrative domains and organisations. These locations do not necessarily coincide with the places where data is produced nor where data is stored, analysed by researchers, or archived for safe long-term storage. To fulfil these needs, the data management system Rucio has been developed to allow the high-energy physics experiment ATLAS at LHC to manage its large volumes of data in an efficient and scalable way. But ATLAS is not alone, and several diverse scientific projects have started evaluating, adopting, and adapting the Rucio system for their own needs. As the Rucio community has grown, many improvements have been introduced, customisations have been added, and many bugs have been fixed. Additionally, new dataflows have been investigated and operational experiences have been documented. In this article we collect and compare the common successes, pitfalls, and oddities that arose in the evaluation efforts of multiple diverse experiments, and compare them with the ATLAS experience. This includes the high-energy physics experiments Belle II and CMS, the neutrino experiment DUNE, the scattering radar experiment EISCAT3D, the gravitational wave observatories LIGO and VIRGO, the SKA radio telescope, and the dark matter search experiment XENON.

UAV-Based GNSS-R for Water Detection as a Support to Flood Monitoring Operations: A Feasibility Study

Signals from global navigation satellite systems (GNSS) can be utilized as signals of opportunity in remote sensing applications. Geophysical properties of the earth surface can be detected and monitored by processing the back-scattered GNSS signals from the ground. In the literature, several airborne GNSS-based passive radar experiments have been successfully demonstrated. With the advancements in small unmanned aerial vehicles (UAVs) and their applications for environmental monitoring, we want to investigate whether GNSS-based passive radar can provide valuable geospatial information from such platforms. Low-cost GNSS reflectometry sensors, developed using commercial of the shelf components, can be mounted onboard UAVs and flown to sense environmental parameters. This paper presents the results of a preliminary study to investigate the feasibility of utilizing data collected by UAV-based GNSS-R sensors to detect surface water for a potential application in supporting flood monitoring operations. The study was conducted in the area surrounding the Avigliana lakes in Northern Italy. The results show the possibility of detecting small water surfaces with few tens of meters resolution, and estimating the area of the lake surface with 92% accuracy. Furthermore, it is proved through simulations that the use of multi-GNSS increases this accuracy to about 99%.

Calibration of a Ground-Based Array Radar for Tomographic Imaging of Natural Media

Ground-based tomographic radar measurements provide valuable knowledge about the electromagnetic scattering mechanisms and temporal variations of an observed scene and are essential in preparation for space-borne tomographic synthetic aperture radar (SAR) missions. Due to the short range between the radar antennas and a scene being observed, the tomographic radar observations are affected by several systematic errors. This article deals with the modelling and calibration of three systematic errors: mutual antenna coupling, magnitude and phase errors and the pixel-variant impulse response of the tomographic image. These errors must be compensated for so that the tomographic images represent an undistorted rendering of the scene reflectivity. New calibration methods were described, modelled and validated using experimental data. The proposed methods will be useful for future ground-based tomographic radar experiments in preparation for space-borne SAR missions.

Evaluation of Brightness Temperature Sensitivity to Snowpack Physical Properties Using Coupled Snow Physics and Microwave Radiative Transfer Models

There are multiple existing microwave radiative transfer models (RTMs) to simulate the brightness temperature (Tb) of snowpacks. It is still challenging to have consistent Tb responses from RTMs due to individual physical formulations of the snowpack scattering process. This article examines three of the widely-used multi-layer RTMs: 1) the microwave emission model of layered snowpacks (MEMLS); 2) the dense media radiative transfer based on the quasi-crystalline approximation (QCA) of Mie scattering of densely packed sticky spheres (DMRT-QMS); and 3) the Helsinki University of Technology (HUT) model. Interestingly, these models yield slightly different Tb responses when driven by the same physical snowpack properties. Tb variations, dependent on the choice of RTMs, are then evaluated to improve the understanding of model differences in microwave emission from a snowpack. We first perform a sensitivity study of the Tb predictions from the three RTMs as a function of snow grain sizes, densities, and depths. While Tb from all three RTMs decreases with increasing snow grain sizes, it is found that a scaling factor is required to have the same amount of Tb attenuation for small grain sizes within the Rayleigh scattering regime. For larger grain sizes, however, a scaling coefficient is not enough to match the model outputs due to the different scattering assumptions of the RTMs. For a single snow layer with increasing snow depths and densities, all three RTMs exhibit Tb attenuations arising from the increase in path lengths and optical depths. Further evaluations are conducted by feeding the three RTMs with the output of a snow physics model driven by in situ weather forcing in a coupled simulation. Outputs of this coupled model include snowpack physical properties and Tbs. By using snow stratigraphy observations, another set of Tb simulation is also conducted with RTMs driven by in situ snowpit observations. The snow physics outputs from the coupled case are compared against in situ snow stratigraphy observations. And both Tb simulations are compared against ground-based microwave observations from the European Space Agency (ESA) Nordic Snow Radar Experiment (NoSREx) 2009–2012. For three consecutive years, the in situ driven Tbs have 21.0-K root-mean-squared error (RMSE) while the coupled simulations have 24.7-K RMSE. However, after isolating the dry snow period and excluding diurnal melting snow conditions, 12.2- and 6.3-K RMSEs are achieved from in situ and coupled cases, respectively, in the 2011 water year.

Ground-penetrating radar measurements of subsurface structures of lacustrine sediments in the Qaidam Basin (NW China): Possible implications for future in-situ radar experiments on Mars

The stratigraphic profile of paleolakes on Mars preserves a record of past climatic, hydrological and sedimentary environment. Radar could be used to detect the structure and distribution of buried lacustrine sediments. But orbiter radar sounders rarely detect the internal structure or the bottom of the ancient Martian lake deposits. Future Martian missions will employ ground-penetrating radar (GPR) onboard rovers to investigate the shallow subsurface structure of paleolake basins. In this case, ground experiments are necessary to test the potential of GPR detection. This study reports on GPR experiments operating at 100 MHz and 200 MHz carried out in the Qaidam Basin, one of the analogue sites for Martian paleolake environments, to detect the subsurface structure of lacustrine sediments and measure the relative permittivity of sediments with both laboratory instrument and GPR data. Two GPR measurements were performed on top of yardangs representing layered lacustrine sedimentary outcrops. Another survey site is a polygonal patterned ground, which is a common landform in the Qaidam Basin and on Mars. The observations revealed by GPR experiments show that (1) sediments of three sites have varied compositions, density and porosity, and have a wide range of relative permittivity values, from 1.56 to 4.56; (2) the detection depth of our measurements could reach 20 m; (3) The interfaces between sedimentary layers can be seen in radargrams, but reflectors in radargrams may not always match with exposed layers of the yardang outcrops due to the undetected change of permittivity values or thin thickness of layers; (4) A distinct and continuous reflector is observed beneath the polygonal terrain which we interpret as a subsurface layer with low water/brine content. Our ground experiments suggest that a similar GPR on Martian rover could detect the near-surface structure of lacustrine sediments, e.g. deposition anomaly, interfaces of drastic permittivity change such as buried ice/brine considering that the design frequency is close to our equipment.

Spaceborne Demonstration of Distributed SAR Imaging With TerraSAR-X and TanDEM-X

Multistatic or distributed satellite systems offer new and unique capabilities necessary for Earth observation with high spatial and temporal resolution. This letter describes a multistatic synthetic aperture radar (SAR) experiment employing the satellites TerraSAR-X and TanDEM-X. In order to demonstrate distributed SAR imaging from space, special data acquisitions with a dedicated geometry were performed. The data evaluation approach is outlined and azimuth profiles over a region with high-contrast backscatter are used to evaluate the azimuth signal reconstruction performance. The results are verified with simulations performed with a flexible SAR simulator reproducing the acquired scene. Finally, the effect of target motion on the reconstruction is analyzed and discussed based on the experimental data.

Efficient knowledge‐aided target relocation algorithm for airborne radar

This letter addresses the problem of target relocation in wide-area ground moving target indication system. The antenna pattern information is exploited as prior knowledge to enhance the performance of airborne radar. Firstly, the ideal target relocation model for moving targets based on the dual-channel radar system is analysed and the mismatch model of the receiving channel is constructed. Then the reason for poor relocation performance is analysed and the channel error model is constructed. Based on this fact, the problem of target relocation is converted into a problem of channel phase estimation. Moreover, a least-squares method is utilised to estimate the phase error by exploiting the real antenna pattern information and a modified mono-pulse curve (MPC) is derived. Finally, the real geometry location of the moving target can be achieved with the modified MPC. Airborne radar experiments are given to verify the effectiveness of the proposed algorithm.

Photonic Components for Signal Generation and Distribution for Large Aperture Radar in Autonomous Driving

Abstract Fully autonomous driving, even under bad weather conditions, requires use of multiple sensor systems including radar imaging. Microwave photonics, especially the optical generation and distribution of radar signals, can overcome many of the electronic disadvantages. This article will give an overview about several photonic components and how they could be incorporated into a photonic synchronized radar system, where all the complexity is shifted to a central station. A first proof-of-concept radar experiment with of the shelf telecommunication equipment shows an angular resolution of 1.1°. Furthermore an overview about possible photonic electronic integration is given, leading to comprising low complexity transmitter and receiver chips.

Variational Assimilation of Radar Data and GLM Lightning-Derived Water Vapor for the Short-Term Forecasts of High-Impact Convective Events

Abstract The assimilation of water vapor mass mixing ratio derived from total lightning data from the Geostationary Lightning Mapper (GLM) within a three-dimensional variational (3DVAR) system is evaluated for the analysis and short-term forecast (≤6 h) of a high-impact convective event over the northern Great Plains in the United States. Building on recent work, the lightning data assimilation (LDA) method adjusts water vapor mass mixing ratio within a fixed layer depth above the lifted condensation level by assuming nearly water-saturated conditions at observed lightning locations. In this algorithm, the total water vapor mass added by the LDA is balanced by an equal removal outside observed lightning locations. Additional refinements were also devised to partially alleviate the seasonal and geographical dependence of the original scheme. To gauge the added value of lightning, radar data (radial velocity and reflectivity) were also assimilated with or without lightning. Although the method was evaluated in quasi–real time for several high-impact weather events throughout 2018, this work will focus on one specific, illustrative severe weather case wherein the control simulation—which did not assimilate any data—was eventually able to initiate and forecast the majority of the observed storms. Given a relatively reasonable forecast in the control experiment, the GLM and radar assimilation experiments were still able to improve the short-term forecast of accumulated rainfall and composite radar reflectivity further, as measured by neighborhood-based metrics. These results held whether the simulations made use of one single 3DVAR analysis or high-frequency (10 min) successive cycling over a 1-h period.

D region observations by VHF and HF radars during a rocket campaign at Andøya dedicated to investigations of PMWE

Abstract. In April 2018 the PMWE1 sounding rocket campaign was conducted at the Andøya Space Center involving coordinated measurements with rockets and ground instruments to measure parameters relevant for testing of the existing theories of polar mesospheric winter echo (PMWE) formation. The Middle Atmosphere Alomar Radar System (MAARSY) was operated to detect PMWE with multiple beam directions to detect favorable launch conditions. A dedicated experiment configuration with five different beam positions was used to point the radar beam along the planned trajectory of the payload. This special radar experiment allowed to obtain basic information about the spatial structure of the PMWE and its dynamical behavior around the flight of the two rockets. PMWE with signal strengths between 10−17 and 10−15 m−1 have been observed by MAARSY during the whole campaign period, starting with a moderate occurrence at the beginning which decreased towards the end of the campaign. Furthermore real common-volume observations by rocket instruments and radar soundings have been carried out at PMWE altitudes on up-leg and down-leg of the rocket flights. The Saura MF radar was operated during both flights probing the mesosphere with a multiple beam scan experiment to derive horizontal winds and electron density profiles. The obtained PMWE characteristics as signal strength and spectral width of the received radar signals as well as estimated horizontal winds and electron densities are presented with particular emphasis to the launch times of the sounding rockets.

Experimental Characterization of Multi-Polarization Radar Backscatter Response of Vehicles at ${J}$ -Band

This paper proposes radar sensors operating at ${J}$ -band (220–320 GHz) for automotive applications. Operating at ${J}$ -band, at about three times higher frequency than the currently available automotive radars operating at 77 GHz, will result in three-fold improvement in cross-range resolution for the same antenna size. Since the characterization of the radar backscatter from different objects on the traffic scenes is necessary for optimizing the design of automotive sensors, the work reported in this paper is the start of a broader study that attempts to fill the lack of knowledge on radar backscatter behavior of road environment at this frequency band. Considering vehicles as the most important object for automotive radars, this paper investigates the response of vehicles from different aspects. A combination of outdoor high-resolution synthetic aperture radar imaging experiments and real-aperture imaging measurements of vehicles are performed using a 222-GHz polarimetric instrumentation radar. The aim of these experiments is to identify the scattering centers on different vehicle bodies and to determine the statistics of the radar return. The results show that significant scattering is due to a limited number of fixtures on the vehicle’s outer surfaces facing the radar. The strongest scattering phase-centers observed are due to specular reflections and, hence, have a strong dependence on the relative look angle. The statistics associated with backscatter from vehicles are found, in most cases, to best fit the Weibull distribution.

Demonstration of distributed digital array radar experiment system

The distributed array radar (DAR) increases the aperture size of radar by coherently synthesising distributed sub-arrays. These sub-arrays form a long baseline, large array, and are capable of improving the angular resolution and detection range of targets. The DAR brings more freedom in the designing of large physical aperture array radar. This study demonstrates a distributed digital array radar experimental system, which can be used for the DAR principle experiment and performance test. This system combines the advantages of ultra-wideband antenna and digital array radar, and enables the array aperture to be reconstructed flexibly in both horizontal and vertical. The system can be used to optimise DAR systems for different array size requirements. A description of system design is demonstrated, while the key performance is briefly analysed.

Micro-Doppler Period Estimation Based on Concentration Statistics of Ambiguity Function

Radar micro-Doppler (m-D) signature, which reflects the micromotion dynamic and structural characteristics of radar target with micromotion, has received increasing attention. Most of the existing m-D signature-extraction methods operate in the time domain or the time-frequency domain. Different from these methods, in this paper, an m-D period estimation approach that operates in the ambiguity domain is proposed. Although the ambiguity function (AF) has been widely used in the field of radar signal processing, its application for m-D signal is introduced for the first time. It is proved that the AF of m-D signal exhibits periodicity along the lag axis and has the best concentration when the lag equals to multiples of the m-D period. Based on this, three AF concentration statistics are employed to capture the periodicity and to provide the m-D estimate. The most important property of the AF concentration statistics is that they are (or approximately) invariant to polynomial translations with terms not larger than second order even if the signal is Doppler ambiguous. Numeric simulation and real radar experiments are used to validate the effectiveness of the proposed technique.

Estimation of Turbulence Parameters in the Lower Troposphere from ShUREX (2016–2017) UAV Data

Turbulence parameters in the lower troposphere (up to ~4.5 km) are estimated from measurements of high-resolution and fast-response cold-wire temperature and Pitot tube velocity from sensors onboard DataHawk Unmanned Aerial Vehicles (UAVs) operated at the Shigaraki Middle and Upper atmosphere (MU) Observatory during two ShUREX (Shigaraki UAV Radar Experiment) campaigns in 2016 and 2017. The practical processing methods used for estimating turbulence kinetic energy dissipation rate ε and temperature structure function parameter C T 2 from one-dimensional wind and temperature frequency spectra are first described in detail. Both are based on the identification of inertial (−5/3) subranges in respective spectra. Using a formulation relating ε and C T 2 valid for Kolmogorov turbulence in steady state, the flux Richardson number R f and the mixing efficiency χ m are then estimated. The statistical analysis confirms the variability of R f and χ m around ~ 0.13 − 0.14 and ~ 0.16 − 0.17 , respectively, values close to the canonical values found from some earlier experimental and theoretical studies of both the atmosphere and the oceans. The relevance of the interpretation of the inertial subranges in terms of Kolmogorov turbulence is confirmed by assessing the consistency of additional parameters, the Ozmidov length scale L O , the buoyancy Reynolds number R e b , and the gradient Richardson number Ri. Finally, a case study is presented showing altitude differences between the peaks of N 2 , C T 2 and ε , suggesting turbulent stirring at the margin of a stable temperature gradient sheet. The possible contribution of this sheet and layer structure on clear air radar backscattering mechanisms is examined.

Observational Evidence for Throat Aurora Being Associated With Magnetopause Reconnection

AbstractThroat auroras have been suggested to be related to indentations on the subsolar magnetopause. However, the indentation generation process and the resulting ionospheric responses have remained unknown. An EISCAT Svalbard Radar experiment was designed to run with all‐sky cameras, which enabled us for the first time to observe the temporal and spatial evolution of flow reversals, Joule heating, and ion upflows associated with throat aurora. The high‐resolution data enabled us to discriminate that the flow bursts and Joule heating were concurrent and co‐located, but were always observed on the west side of the associated throat auroras, reflecting that the upward/downward field‐aligned currents associated with throat aurora are always to the east/west, respectively. These results are consistent with the geometry of Southwood (1987) flux transfer event model and provide strong evidence for throat aurora being associated with magnetopause reconnection events. The results also support a conceptual model of the throat aurora.

New Aspects of the Ionospheric Behavior Over Millstone Hill During the 30‐Day Incoherent Scatter Radar Experiment in October 2002

AbstractThe geomagnetic storm‐driven ionospheric changes and the involved processes are interesting and challenging topics in understanding and predicting the ionosphere. In this study we investigate the response of the ionosphere to geomagnetic disturbances during the 30‐day incoherent scatter radar measurements conducted at Millstone Hill (42.6°N, 71.5°W) from 4 October to 4 November 2002. During geomagnetically disturbed periods, while the peak electron density of the F2 layer (NmF2) and total electron content deviate remarkably from the quiet time ones in a similar way, the incoherent scatter radar measurements reveal that the changes in electron density are frequently different between low and high altitudes. The electron density is significantly depleted at low altitudes; however, at topside it either changes slightly or sometime is enhanced. The enhanced vertical scale height around 600 km under geomagnetically active conditions implies that the topside electron density profiles become much steeper. The increase in the peak height of F2 layer (hmF2) indicates the upward motions under the action of the storm‐driven dynamic processes. Further, sometimes strong differences are shown in total electron content between Millstone Hill and longitude 100°W. The competing contributions from dynamic processes and disturbance composition to the storm‐time ionospheric changes over Millstone Hill are indicated in the different responses in electron density at the bottomside and topside of the ionosphere.