Radar Operating Research Articles

Evolution of Over-the-Horizon Radar in Australia From Humble Origins to Operational Capabilities

The successful realization of high frequency (HF) over-the-horizon radar (OTHR) is one of the more significant radar developments since World War II. The first project to develop OTHR in Australia commenced in 1974 and was called Jindalee. The operational outcome of that project carries this iconic name in the Jindalee Operational Radar Network (JORN). JORN consists of three operational OTHR systems that deliver wide-area surveillance over Australia's northern approaches as a key element of an integrated defense surveillance system. JORN is one of Australia's quietest achievers and is widely recognized in a global sense as the frontier of OTHR capability. The now Defence Science and Technology Group pioneered the development of OTHR in Australia from humble origins in the 1960s and continues to lead innovation in HF radar systems to the present day. This article reviews the evolution of OTHR in Australia including the most recent phases of JORN. Through the lens of JORN as an exemplar Australian program, it reflects on pivotal factors contributing to the successful transition of use-inspired scientific innovation to defense operational capability.

Multiscale Decomposition Prediction of Propagation Loss for EM Waves in Marine Evaporation Duct Using Deep Learning

A tropospheric duct (TD) is an anomalous atmospheric refraction structure in marine environments that seriously interferes with the propagation path and range of electromagnetic (EM) waves, resulting in serious influence on the normal operation of radar. Since the propagation loss (PL) can reflect the propagation characteristics of EM waves inside the duct layer, it is important to obtain an accurate cognition of the PL of EM waves in marine TDs. However, the PL is strongly non−linear with propagation range due to the trapped propagation effect inside duct layer, which makes accurate prediction of PL more difficult. To resolve this problem, a novel multiscale decomposition prediction method (VMD−PSO−LSTM) based on the long short−term memory (LSTM) network, variational mode decomposition (VMD) method and particle swarm optimization (PSO) algorithm is proposed in this study. Firstly, VMD is used to decompose PL into several smooth subsequences with different frequency scales. Then, a LSTM−based model for each subsequence is built to predict the corresponding subsequence. In addition, PSO is used to optimize the hyperparameters of each LSTM prediction model. Finally, the predicted subsequences are reconstructed to obtain the final PL prediction results. The performance of the VMD−PSO−LSTM method is verified by combining the measured PL. The minimum RMSE and MAE indicators for the VMD−PSO−PSTM method are 0.368 and 0.276, respectively. The percentage improvement of prediction performance compared to other prediction methods can reach at most 72.46 and 77.61% in RMSE and MAE, respectively, showing that the VMD−PSO−LSTM method has the advantages of high accuracy and outperforms other comparison methods.

Parallel Radars: From Digital Twins to Digital Intelligence for Smart Radar Systems.

Radar is widely employed in many applications, especially in autonomous driving. At present, radars are only designed as simple data collectors, and they are unable to meet new requirements for real-time and intelligent information processing as environmental complexity increases. It is inevitable that smart radar systems will need to be developed to deal with these challenges and digital twins in cyber-physical systems (CPS) have proven to be effective tools in many aspects. However, human involvement is closely related to radar technology and plays an important role in the operation and management of radars; thus, digital twins' radars in CPS are insufficient to realize smart radar systems due to the inadequate consideration of human factors. ACP-based parallel intelligence in cyber-physical-social systems (CPSS) is used to construct a novel framework for smart radars, called Parallel Radars. A Parallel Radar consists of three main parts: a Descriptive Radar for constructing artificial radar systems in cyberspace, a Predictive Radar for conducting computational experiments with artificial systems, and a Prescriptive Radar for providing prescriptive control to both physical and artificial radars to complete parallel execution. To connect silos of data and protect data privacy, federated radars are proposed. Additionally, taking mines as an example, the application of Parallel Radars in autonomous driving is discussed in detail, and various experiments have been conducted to demonstrate the effectiveness of Parallel Radars.

Microwave Photonic Crystal Video Receiver for Radar Interception

This article introduces an approach of a crystal video receiver (CVR) based on microwave photonics (MWP) to detect pulsed radar signals. The pulsed radiofrequency (RF) envelope detection is achieved using the optical self-homodyne technique on the photodetection process. The proposed architecture uses a phase modulator (PM) to modulate the optical carrier and a fiber Bragg grating (FBG) to filter the spectrum to convert phase to intensity modulation. The self-homodyne technique eliminates the optical carrier at photodetector to reduce the shot noise and saturation on it. Moreover, the photodetection is performed at the radar pulse baseband, allowing to obtain transimpedance gain. The theoretical principle and an experimental demonstration are presented. A CVR sensitivity of 53 V/mW and a tangential signal sensitivity (TSS) equal to −40 dBm is achieved for a pulsed radar operating at 17 GHz.

Cooperative Interferometric Receiver With Time-Agile Radar Sensing and Radio Communication Capability

A cooperative radar-communication (RadCom) system architecture employing a multiport interferometer receiver is introduced and demonstrated for low-power and low-cost multifunction wireless applications. The proposed system operates in both radar sensing and radio communication modes, which are arranged in different time slots within a single hardware platform. In the radar sensing cycle, a triangular frequency-modulated continuous-wave (FMCW) scheme is adopted for distance and velocity measurements. The radio cycle following the radar sensing cycle is used to communicate beat frequency information among different measurement stations for a cooperative radar operation, which can also be used for other data transmissions. The interferometric receiver for a unified multifunction operation benefits from the cooperative approach as it does not require a receiver front-end with a high dynamic range. The receiver architecture also makes use of a balanced detection scheme to suppress the frequency mixing components generated between radar echoes and cooperative radar responses, which eliminates undesired interferences and false targets as well as to enhance the signal quality. A mathematical model of the proposed sensing system is derived to design and implement the system for operation in a multistation environment. The system performance consisting of two stations in a low microwave frequency band has been established and evaluated for both modes with several experiments. In radar sensing mode, the distance and velocity measurements demonstrate the target finding capability of our proposed system. In radio mode, the demodulation of various digitally modulated signals has been successfully studied at different data rates.

Gale Wind Speed Retrieval Algorithm Using Ku-Band Radar Data Onboard GPM Satellite

An algorithm to retrieve the wind speed within a wide swath from the normalized radar cross section (NRCS) is developed for the data of Ku-band radar operating in scanning mode installed onboard the Global Precipitation Measurement (GPM) satellite. NRCS at the nadir is calculated within a wide swath and is used to obtain the wind speed. The scatterometer data are used to obtain the dependence between NRCS at the nadir and the wind speed for gale winds. The algorithm was validated also using the Advanced Scatterometer (ASCAT) data and revealed good accuracy.

A novel radar operating mode identification approach based on variational relevance vector machine with chaotic gravitational search optimization

Radar operating mode identification is one of the top priorities in the electronic countermeasure field for threat prediction. However, the inference speed and accuracy of existing identification methods are still not satisfactory for threat detection, and some of them need extra prior knowledge to extract features. This paper introduces an identification approach for radar operating mode to solve these problems. The variational relevance vector machine (VRVM) is presented as the feature extractor and the basic unit of identification. An improved chaotic gravity search algorithm (CGSA) is developed to increase the search breadth and optimize the hyperparameters of VRVM. Threshold-one-versus-one (TOVO) is further proposed to screen the identification results to form the final ensemble method called CGSA–VRVM–TOVO. Experimental results indicate the CGSA–VRVM–TOVO achieves 99.44% accuracy without prior knowledge. Compared with XGBoost, Random Forest, and LightGBM, our approach is 1.94%, 0.55%, and 1.11% higher in accuracy, respectively, and twice as fast as the fastest method of them all.

Rationality Now!

Rationality Now!

Radio frequency interference detection and mitigation in the DWD C-band weather radar network

Abstract. C-band weather radar data are commonly compromised by interference from external sources even though weather radars are the primary and therefore privileged user of this frequency band. This is also the case for the radar network of the German Meteorological Service (Deutscher Wetterdienst, DWD). Theoretically, dynamic frequency selection (DFS) by devices operating in the C band should prevent any disturbance of the primary user. In practice, this does not always work as intended under the current regulations. As it is not possible to separate a superimposed interference signal from measured weather radar data, the protection of the frequency band is of utmost importance. Currently, the only available option is to discard the compromised portions of the radar data. Therefore, the current best course of action is to shut down radio frequency interference (RFI) sources as quickly as possible. The automated RFI detection algorithm for the German C-band weather radar network, operational since July 2017, makes use of routinely measured radar moments. Built upon data gathered since 2017, an RFI classification with respect to the severity and duration of RFI sources was first implemented in 2019. An independent verification of the RFI detection algorithm was performed by using a commercially available Wi-Fi adapter, which is directly integrated into the radar receiver. Subsequently, a mitigation workflow was implemented to efficiently identify and shut down detected RFI sources by the German Federal Network Agency (Bundesnetzagentur, BNetzA). By following this workflow with great effort, the number of persistent RFI sources has been decreasing since October 2019, while a steady increase in short-lived RFI sources over the last 5 years also exists. In total, 11 889 RFI sources have been identified from July 2017 to May 2022. Most of these (94.8 %) are such short-lived sources that an unambiguous identification by the BNetzA is, in general, not feasible. However, as stated by the C-band regulations, any non-compliant transmitter compromising the operation of a weather radar has to be shut down. This is important, as even these short-lived RFI sources negatively affect meteorological product generation.

Using cloud radar to investigate the effect of rainfall on migratory insect flight

Abstract The fate of migrating insects that encounter rainfall in flight is a critical consideration when modelling insect movement, but few field observations of this common phenomenon have ever been collected due to the logistical challenges of witnessing these encounters. Operational cloud radars have been deployed around the world by meteorological agencies to study precipitation physics, and as a byproduct, provide a rich database of insect observations that is freely available to researchers. Although considered unwanted ‘clutter’ by the meteorologists who collect the data, the analysis method presented here enables ecologists to delineate co‐occurring signals from insects and raindrops. We present a method that uses image processing techniques on cloud radar velocity spectra to examine the fate of migrating insects when they encounter precipitation. By analysing velocity spectra, we can distinguish flying insects from falling rain and compare the relative density of insects in flight before, during and after the rainfall. We demonstrate the method on a case of insect migration in Oklahoma, USA. Using this method, we show the first reconstructed images of migrating insect layers in flight during rainfall. Our analysis shows that mild to moderate rainfall diminishes the number of insects aloft but does not cause full termination of migratory flight, as has previously been suggested. We hope this technique will spur further investigations of how changing weather conditions impact insect migration, and enable some of the first of such studies in regions of the world that are underrepresented in the literature.

Aerosol characteristics and polarimetric signatures for a deep convective storm over the northwestern part of Europe – modeling and observations

Abstract. The Terrestrial Systems Modeling Platform (TSMP) was extended with a chemical transport model and polarimetric radar forward operator to enable detailed studies of aerosol–cloud–precipitation interactions. The model was used at kilometer-scale (convection-permitting) resolution to simulate a deep convective storm event over Germany which produced large hail, high precipitation, and severe damaging winds. The ensemble model simulation was, in general, able to capture the storm structure, its evolution, and the spatial pattern of accumulated precipitation. However, the model was found to underestimate regions of high accumulated precipitation (> 35 mm) and convective area fraction in the early period of the storm. While the model tends to simulate too high reflectivity in the downdraft region of the storm above the melting layer (mostly contributed by graupel), the model also simulates very weak polarimetric signatures in this region, when compared to the radar observations. The above findings remained almost unchanged when using a narrower cloud drop size distribution (CDSD) acknowledging the missing feedback between aerosol physical and chemical properties and CDSD shape parameters. The kilometer-scale simulation showed that the strong updraft in the convective core produces aerosol-tower-like features, increasing the aerosol number concentrations and hence increasing the cloud droplet number concentration and reducing the mean cloud drop size. This could also be a source of discrepancy between the simulated polarimetric features like differential reflectivity (ZDR) and specific differential-phase (KDP) columns along the vicinity of the convective core compared to the X-band radar observations. However, the use of narrow CDSD did improve the simulation of ZDR columns. Besides, the evaluation of simulated trace gases and aerosols was encouraging; however, a low bias was observed for aerosol optical depth (AOD), which could be partly linked to an underestimation of dust mass in the forcing data associated with a Saharan dust event. This study illustrates the importance and the additional complexity associated with the inclusion of chemistry transport model when studying aerosol–cloud–precipitation interactions. But, along with polarimetric radar data for model evaluation, it allows us to identify and better constrain the traditional two-moment bulk cloud microphysical schemes used in the numerical weather prediction models for weather and climate.

Auroral Oval Boundary Dynamics on the Nature of Geomagnetic Storm

During emergency events, we could significantly depend on the stable operation of radio communication, navigation, and radars. The ionosphere, especially its auroral regions, significantly influences radio systems, which is why scientists and engineers create systems to monitor these regions. Using data from the global GNSS network, we analyzed the 10 strongest magnetic storms of solar cycle 24: five coronal mass ejection-driven (CME-driven) and five high-speed stream-driven (HSS-driven) storms. The analysis was based on the calculation of the standard deviation of the total electron content (TEC) derivative (rate of TEC index, ROTI). Under all the storms, the ROTI featured similar dynamics: the average ROTI reaches the highest values during the main phase, and the higher the intensity is, the more intense and equatorward the average ROTI registered. The highest cross-correlations are observed with a lag of 1 h, between the IMF z-component Bz and the magnetic latitude where the highest ROTI values appear. The auroral electrojet (SME index) shows the highest impact on the ROTI dynamics. An increase in the space weather indices (in absolute value) is accompanied by a decrease in the latitude where the maximal ROTI occurs. We found that the peculiarities of a storm affect the ROTI dynamics: all the CME-driven storms feature a high cross-correlation (>0.75) between the IMF z-component Bz and the magnetic latitude where the highest ROTI appears, while the HSS-driven storms feature a lower cross-correlation (<0.75) between them. The difference in duration of similar (by maximal values of geomagnetic indices) HSS- and CME-driven storms could produce differences in the highest ROTI values. Correlations show that compared to HSS-driven storms, CME-driven ones more directly impact the ROTI values and locations of regions with a high ROTI.

Evaluating Latent-Heat-Nudging Schemes and Radar forward Operator Settings for a Convective Summer Period over Germany Using the ICON-KENDA System

Radar data assimilation has been operational at the Deutscher Wetterdienst for several years and is essential for generating accurate precipitation forecasts. The current work attempts to further enhance the radar data assimilation by improving the latent heat nudging (LHN) scheme and by reducing the observation error (OE) caused by the representation error of the efficient modular volume radar operator (EMVORADO). First of all, a series of hindcasts for a one-month convective period over Germany are performed. Compared with radar reflectivity and satellite observations, it is found that the LHN scheme that implicitly adjusts temperature performs better, and the beam broadening effect and the choice of the scattering schemes in EMVORADO are important. Moreover, the Mie scheme with the new parameterization to reduce the brightband effect not only proves to be the best in hindcasts but also that it results in the smallest standard deviations and the shortest horizontal correlation length scales of the OE in data assimilation experiments.

Generation Mechanism and Characteristic Analysis of Dual-Frequency Pseudo-Signal Interference of the Swept-Frequency Radar

In order to master the law of the pseudo-signal interference effect of dual-frequency electromagnetic radiation in typical radar equipment, a certain type of Ku-band swept-frequency ranging radar was used as the test object to carry out single-frequency continuous wave and dual-frequency continuous wave pseudo-signal interference effect experiments. Through experiments, it is found that dual-frequency electromagnetic radiation will cause “hill” and “spike” type pseudo-signal interference to the swept-frequency radar. Based on the frequency analysis of the radar receiving circuit, the interference mechanism of the dual-frequency pseudo-signal is revealed, and the morphological characteristics and distance law of the pseudo-signal are explained. The variation law of the pseudo-signal level with interference field strength is obtained. The results show that the in-band dual-frequency nonintermodulation interference is similar to the single-frequency interference, and the only difference is that the number of pseudo-signals increases; when the interference frequency difference is about 400∼600 MHz, the out-of-band dual-frequency second-order intermodulation signal will cause “hill” type pseudo-signal interference, and the pseudo-signal distance is random; when the interference frequency difference is less than 5 MHz, both the dual-frequency second-order intermodulation signal and the third-order intermodulation signal will cause “spike” pseudo-signal interference inside and outside the radar operating frequency band; the pseudo-signal distance is fixed.

Возможности обнаружения излучения морских радиолокаторов с низкой вероятностью перехвата их излучения

Object and purpose of research. This paper presents analytical estimates for emission characteristics of foreign low-probability-of-intercept (LPI) radars. It also gives a quantitative assessment to the possibility of detecting the operation of these radars by standard naval EW tools. Subject matter and methods. This paper reviews the publications of leading foreign experts in order to analyse performance parameters of existing foreign LPI radars and ESM tools. Emission characteristics of these “stealthy” radars in marine conditions were calculated by means of the four-beam model of electromagnetic wave scattering over an underlying surface developed by Krylov State Research Centre researchers. Main results. The study yielded a quantitative estimate for the possibility to detect the emission of radar homing head for RBS-15 anti-ship missile by standard naval tools of radioelectronic surveillance. Conclusion. The study has shown that ESM tools currently available with foreign navies cannot reliably detect the operation of LPI radars.

The Study of the Possibility of Applying Parallel Programming to the Algorithms of Space-Time Adaptive Processing

The article presents the description, assumptions and subsequent steps of the space-time adaptive processing (STAP) algorithms used as a signal processing tool in radars. The possibilities of object detection using the Sample Matrix Inversion (SMI) and Data Domain Least Squares (DDLS) algorithms were compared and showned. The article shows the impact of the use of parallel programming on the computation time of both algorithms. The main aim of this study was to propose an efficient method for the real-time implementation of the STAP algorithm in airborne radar systems. The idea of using parallel programming in STAP, supported only by the preliminary research results presented above, gives a real chance for the casual implementation of the STAP algorithm in a radar operating in close to real time mode.

Radar range profile processing using Green’s function

In this study, a useful method for synthesizing range profiles to be used in ultra-wideband radar operations is discussed. One-dimensional transmission-reflection geometry of the radar scenario, which consists of a single receiver and single transmitter, is formulated by using the Green’s function. A one-dimensional time domain Green’s function is employed in the formulation and the impulsive characteristic of this function, which provides focus on the target position, has been determined. This characteristic represents the impulse response of the propagating medium to the electromagnetic wave. The resulting derivation offers a framework that can also be used in higher dimensional and complex radar problems by taking the advantage of its flexibility. Proposed method has been detailed and tested on an exemplary implementation and successful results that provide good focus on the target positions are shown in the conclusions. Finally, outcomes and benefits are discussed.

Optimizing radar scan strategies for tracking isolated deep convection using observing system simulation experiments

Abstract. Optimizing radar observation strategies is one of the most important considerations in pre-field campaign periods. This is especially true for isolated convective clouds that typically evolve faster than the observations captured by operational radar networks. This study investigates uncertainties in radar observations of the evolution of the microphysical and dynamical properties of isolated deep convective clouds developing in clean and polluted environments. It aims to optimize the radar observation strategy for deep convection through the use of high-spatiotemporal cloud-resolving model simulations, which resolve the evolution of individual convective cells every 1 min, coupled with a radar simulator and a cell tracking algorithm. The radar simulation settings are based on the Tracking Aerosol Convection Interactions ExpeRiment (TRACER) and Experiment of Sea Breeze Convection, Aerosols, Precipitation and Environment (ESCAPE) field campaigns held in the Houston, TX, area but are generalizable to other field campaigns focusing on isolated deep convection. Our analysis produces the following four outcomes. First, a 5–7 m s−1 median difference in maximum updrafts of tracked cells is shown between the clean and polluted simulations in the early stages of the cloud lifetimes. This demonstrates the importance of obtaining accurate estimates of vertical velocity from observations if aerosol impacts are to be properly resolved. Second, tracking of individual cells and using vertical cross section scanning every minute capture the evolution of precipitation particle number concentration and size represented by polarimetric observables better than the operational radar observations that update the volume scan every 5 min. This approach also improves multi-Doppler radar updraft retrievals above 5 km above ground level for regions with updraft velocities greater than 10 m s−1. Third, we propose an optimized strategy composed of cell tracking by quick (1–2 min) vertical cross section scans from more than one radar in addition to the operational volume scans. We also propose the use of a single-RHI (range height indicator) updraft retrieval technique for cells close to the radars, for which multi-Doppler radar retrievals are still challenging. Finally, increasing the number of deep convective cells sampled by such observations better represents the median maximum updraft evolution with sample sizes of more than 10 deep cells, which decreases the error associated with sampling the true population to less than 3 m s−1.

Non-Imaging Fall Detection Based on Spectral Signatures Obtained Using a Micro-Doppler Millimeter-Wave Radar

Falls are the leading cause of accidents among the elderly population. In recent years, radar has been employed in fall detection due to its superior sensing capabilities, small dimensions, low cost and primarily non-intrusive sensing capabilities in addition to its robustness under a range of heat and lighting conditions. In this paper, we present a technique for identifying when a person is falling using a low-power millimeter-wave radar operating in the W-band. This detection, conducted in real time, is based on the transmission of a continuous wave and heterodyning of the received signal reflected from the person to obtain micro-Doppler shifts associated with the person’s motion. These results make it possible to obtain a high-quality time-frequency distribution and spectrogram, from which the person’s unique fall movement characteristics can be determined. In this paper, we present experimental results based on 94 GHz real radar data obtained from a falling person. This carrier frequency is higher than that of current systems, allowing higher frequency resolution and more accurate results. Compared to other tracking systems, this sensor does not simulate or violate privacy. However, the high-frequency system enables high-resolution realizations with high reliability.

РЕЗУЛЬТАТИ ЕКСПЕРИМЕНТАЛЬНИХ ДОСЛІДЖЕНЬ БАГАТОДІАПАЗОННОГО ІМІТАТОРА ПОСТАНОВНИКА АКТИВНИХ ШУМОВИХ ПЕРЕШКОД

The article provides information on the results of experimental studies of a multi-band hardware and software complex for simulating the action of an active noise jammer, which has been created for the training of operators of radar stations of radio engineering troops. One of the important elements of the professional training of the radar stations operators of the air defense radio engineering forces is their ability to work in difficult target and jamming conditions. The existing simulators for training operators do not fully meet the requirements of the quality of training, since they form only secondary bearing marks on the jammer manufacturer and do not reproduce the situation of deterioration of target detection conditions as a result of the simultaneous action of active and passive noise jammer, as well as the influence of the autocompensator of jammer on the quality of the radar, as it happens in real situation. The offered device for simulating the influence of active jammer has been built according to the modular principle and implemented using software-defined radio technology, which allows to quickly change both the type of signal and its parameters. Power amplifiers and antenna systems have been designed to operate in the 140–190 MHz, 470–900 MHz, and 2500–3500 MHz bands, and for experimental research radar stations in the meter, decimeter, and centimeter wave ranges have been involved. The method of using the simulator has been substantiated, and the conducted studies showed that for radar stations in which the angular beams of the directional pattern have different operating frequencies, there is an additional possibility of simulating the action of the active jammer by changing the frequency of the jammer in the case of operation of the complex directly near the suppression object, where the directional pattern of the radar station antenna has not yet been formed. The method of using the complex both for training sessions and during tactical exercises of the radio technical troops unit to simulate the action of an air-based jamming device or a dropped jamming transmitter has been substantiated. Keywords: active noise jammer; simulation; hardware and software complex; radar station; programmed radio.