Radar Antenna Research Articles

Direction of Arrival Estimation of Meteors Echoes using Array Radio Antennas

Array antennas have an interesting role in the radio astronomy field. The array antennas allow astronomers to obtain high-resolution signals with high sensitivity to weak signals. This paper estimates the meteors' positions entering the Earth's atmosphere and develops a simulation for array antenna radar to analyze the meteor's echoes. The GNU radio software was used to process the echoes, which is a free open-source software development toolkit that provides signal processing blocks to implement in radio projects. Then, the simulation determines the azimuth and elevation of the meteors. An improved Multiple Signal Classification (MUSIC) algorithm has been suggested to analyze these echoes. The detected power of each meteor echo has a Doppler frequency shift due to the high speed of the meteors, which impacts the accuracy of the Direction of Arrival (DOA) estimation. The Doppler shift was considered in this simulation, and the results showed that the suggested method has low complexity and high resolution and can estimate the meteors' position with the minimum error.

An efficient feed network for small multibeam secondary surveillance radars

ABSTRACT In this paper, an efficient feed network for small secondary surveillance radar (SSR) antennas is introduced. It integrates all three required beams (SUM, DIFF, and CTRL) into a single-sheet design. The architecture employs a side element to generate the control (CTRL) beam for a 7-element 1.5-meter SSR antenna array. The target performance includes keeping the gain above 15 dBi and a side lobe level exceeding 20 dB at 1030 MHz and 1090 MHz for the SUM port while reducing the loss of the CTRL beam. In this work, a modified Gyzel unequal power combiner replaced the conventional Wilkinson power combiner to adjust the feed network’s power-sharing. Also, a practical method for implementing a high coupling value of 7 dB in a directional coupler is presented as one of the key steps to achieve a very low loss of 2.9 dB in the CTRL path (2.4 dB improvement). Simulation and measurement results validate the proposed feed network’s performance.

Calibration of Dual-Polarised Antennas for Air-Coupled Ground Penetrating Radar Applications

Radar polarimetry is a technique that can be used to enhance target detection, identification and classification; however, the quality of these measurements can be significantly influenced by the characteristics of the radar antenna. For an accurate and reliable system, the calibration of the antenna is vitally important to mitigate these effects. This study presents a methodology to calibrate Ultra-Wideband (UWB) dual-polarised antennas in the near-field using a thin elongated metallic cylinder as the calibration object. The calibration process involves measuring the scattering matrix of the metallic cylinder as it is rotated, in this case producing 100 distinct scattering matrices from which the calibration parameters are derived, facilitating a robust and stable solution. The calibration procedure was tested and validated using a Vector Network Analyser (VNA) and two quad-ridged antennas, which presented different performance levels. The calibration methodology demonstrated notable improvements, aligning the performance of both functioning and under-performing antennas to equivalent specifications. Mid-band validation measurements indicated minimal co-polar channel imbalance (<0.3 dB), low phase error (<0.8°) and improved cross-polar isolation (≈48 dB).

Design and Implementation of Wind Speed-Based Radar Antenna Safety System Prototype

Air defense radar is a system that detects the presence of one or more air objects at a certain distance, altitude, and direction. One type of air defense radar used by the Indonesian National Armed Forces (TNI) is the Thomson TRS 2215D. An essential part of the radar is the rotating part of the radar antenna support called the antenna pivot. The rotation of the radar antenna must constantly be monitored and controlled for rotational stability at a speed of 6 Rotations per Minute (RPM) with a maximum wind speed of 120 km/h to prevent damage to the driving gear. Stormy weather with high wind speeds can cause the rotation speed of the radar antenna to be uncontrollable, which can cause damage. The solution offered in this study is to build a safety system that will lock the radar antenna automatically when the wind speed is detected to exceed tolerances and maintain the security of the radar antenna and its support system. The safety system was designed using an ESP32 Wi-Fi device equipped with an anemometer wind speed sensor, a Liquid Crystal Display (LCD) monitor, a Direct Current (DC) motor, and a Blynk Internet of Things (IoT) application. The test was conducted in a simulation using a multi-meter and oscilloscope measuring instrument. Testing the radar antenna's safety system prototype on a laboratory scale shows that the safety system can work as designed. The system can lock the radar antenna when the airflow is set at a speed of 54 km/h or 15 m/s, communication with the Blynk server works well, and the ESP32 device can transmit data at a maximum distance of 14 meters.

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.

Interferometry of ionospheric E-region irregularities based on Kunming VHF radars

There is a long history of using VHF radar systems to detect ionospheric irregularities based on the theory of coherent scattering. According to previous work, there is a high occurrence of field-aligned irregularities (FAIs) in the ionospheric E-region over Kunming, China. In this paper, the VHF coherent scattering radar at Kunming is used to study the FAIs in the ionospheric E-region. Different arrangement of VHF radar antenna arrays, interferometry, and FAI echo parameter inversion methods are designed and tested. The measurement results show that the temporal and spatial characteristics of the irregularities can be obtained using these methods, as well as more refined spatial three-dimensional structure information. It is indicated that the new arrangement of the VHF radar antenna array is feasible to operate interferometry detection of E-region FAIs with the Kunming VHF radar.

Terahertz single/dual beam scanning with tunable field of view by cascaded metasurfaces

Dynamic beam scanning with a dynamically tunable beam number, beam direction, and beam polarization remains a challenge in the terahertz gap, which is urgently needed for terahertz radar, next-generation wireless communication, and imaging applications. Different from programmable metasurfaces with element-level phase control, the beam direction is dynamically controlled by two cascaded all-dielectric metasurfaces during in-plane rotation. For a pair of circularly polarized beams with opposite handedness, the scanning field of view (FOV) can be the same or different according to the independent phase modulation in both layers and for both polarization states. Switchable single-beam and dual-beam scanning is achieved by controlling the incident polarization, which covers the ±60° FOV at 0.291 THz with an angular step of 1° and an average gain of 16.2 dBi. The output beam is quasi-circular polarized with an average ellipticity of 0.83. Single beam scanning along a Fibonacci spiral trajectory and dual beam scanning along symmetric and asymmetric trajectories are experimentally validated. Different beam scanning processes are recorded using a terahertz camera, which show good agreement with the theoretical prediction. The wide field-of-view continuous beam scanning with a switchable number of beams and a flexible FOV may have a significant impact on the development of terahertz radar and terahertz intelligent antennas.

Design of Automotive Radar Antenna for Covering Middle- and Long-Range With Dual-Circular Polarization

Design of Automotive Radar Antenna for Covering Middle- and Long-Range With Dual-Circular Polarization

Research on optimization of flatness evaluation method for antenna array of a radar vehicle

Abstract Radar vehicles play an important role in providing radar services in the aviation field. The flatness of the antenna array is one of the key factors in ensuring the detection accuracy of radar vehicles for airborne targets. In this paper, the mechanical structure of a new type of radar antenna truck is designed, the stress analysis under various working conditions is carried out, the mechanical performance of the whole vehicle is checked, and the evaluation method of the flatness of the antenna array is discussed. Using ANSYS to carry out static finite element analysis and using the deformation results of each element node in ANSYS, the evaluation method based on the multiple regression function is applied to the calculation scheme of antenna array flatness. The final results show that the safety factor of the radar vehicle structure can reach more than 1.75 under extreme working conditions and more than 2.0 under other working conditions. It can work safely. Through the optimization of the shape evaluation method, the accuracy of the final shape calculation result is less than 10mm. The precision of shape error processing is improved.

A Multiple Targets ISAR Imaging Method with Removal of Micro-Motion Connection Based on Joint Constraints

Combining multiple data sources, Digital Earth is an integrated observation platform based on air–space–ground–sea monitoring systems. Among these data sources, the Inverse Synthetic Aperture Radar (ISAR) is a crucial observation method. ISAR is typically utilized to monitor both military and civilian ships due to its all-day and all-weather superiority. However, in complex scenarios, multiple targets may exist within the same radar antenna beam, resulting in severe defocusing due to different motion conditions. Therefore, this paper proposes a multiple-target ISAR imaging method with the removal of micro-motion connections based on the integration of joint constraints. The fully motion-compensated targets exhibit low rank and local similarity in the high-resolution range profile (HRRP) domain, while the micro-motion components possess sparsity. Additionally, targets display sparsity in the image domain. Inspired by this, we formulate a novel optimization by promoting the low-rank, the Laplacian, and the sparsity constraints of targets and the sparsity constraints of the micro-motion components. This optimization problem is solved by the linearized alternative direction method with adaptive penalty (LADMAP). Furthermore, the different motions of various targets degrade their inherent characteristics. Therefore, we integrate motion compensation transformation into the optimization, accordingly achieving the separation of rigid bodies and the micro-motion components of different targets. Experiments based on simulated data demonstrate the effectiveness of the proposed method.

A Wide-Beam Antenna for Automotive Radar Based on Improved Particle Swarm Algorithm

Article A Wide-Beam Antenna for Automotive Radar Based on Improved Particle Swarm Algorithm Bin Wang 1, Zhenhua Li 1 and Shufei Yin 1,2,* 1 Shanghai Baolong Automotive Corporation, Shanghai 201619, China 2 School of Automotive Engineering, Wuhan University of Technology, Wuhan 430070, China * Correspondence: yinshufei@chinabaolong.net Received: 26 August 2024; Revised: 9 September 2024; Accepted: 11 September 2024; Published: 23 September 2024 Abstract: The traditional automotive corner radar antenna has the problem that the horizontal filled of view (FOV) is not large enough, which affects wide detection area capability and driving safety. In order to solve the problem, this paper proposes a wide-beam antenna design method for automotive corner radar based on improved particle swarm optimization (IPSO) algorithm. The mathematical model of comb-line antenna for 77 GHz corner radar is established and combined with the IPSO algorithm to achieve wide beam. The algorithm avoids the search process falling into local optimum by introducing an adaptive shrinkage factor and chaotic disturbance when the non-superior particle position is updated. The computational results show that the convergence of the IPSO algorithm is significantly better than standard particle swarm optimization (SPSO) in wide beam forming under the same number of iterations.

Design and Simulation of Circular Dielectric Resonator Antenna and Investigation of Structure, Microstructure, and Dielectric Properties of Mn‐Modified Sr2SnO4

Samples with compositions of Sr2Sn1−xMnxO4(SSM) with 0 ≤ x ≤ 0.10 are prepared by conventional ceramic route via heat treatment at 1350 °C. Phase and crystal structure analysis is studied using X‐ray diffraction and Rietveld refinement to confirm the crystallization of samples in the tetragonal structure under space group I4/mmm. The size‐strain plot method is employed to identify the role of Mn on crystallite size/microstrain/dislocation density. The scanning electron microscope and energy‐dispersive X‐ray spectroscopy analysis confirm a significant change in the grain size and compositional homogeneity of all samples with Mn‐doping. Dielectric properties of samples are explained in terms of interfacial and orientation polarization of dipoles . Modulus studies show the exclusion of electrode contribution from the electrical properties. The single‐segment circular dielectric resonator antenna is designed with the help of experimental dielectric parameters and showed two major resonant frequencies at 3.6 and 6.7 GHz. The reduction in the S11 parameter and −10 dB reflection coefficient bandwidth with Mn‐doping observed due to overlapping of the E‐field line suggests the application in patch array antenna for radar and satellite communication applications. This study also enables to explore Sr2SnO4‐based Ruddlesden Popper oxide for antenna and mm‐wave communication applications.

Research on identification method of coal-rock interface based on ground penetrating radar in the driving face of soft coal seam

Coal–rock interface recognition is one of the key challenges in advancing unmanned rapid tunneling systems. To address this, a method based on variations in ground-penetrating radar (GPR) reflection wave amplitude is proposed for identifying coal-rock interfaces in soft coal seams. A mathematical model derived from Maxwell's equations calculates the coal seam area based on the reflected wave amplitude. Experiments using a 400 MHz radar antenna show that the method achieves identification errors of 3.58 cm, 3.74 cm, and 4.23 cm for coal-to-rock ratios of 1:2, 1:1, and 2:1, respectively. In practical applications within a coal mine excavation face, the identification error is 6.64 cm. This method provides crucial data for drum height adjustment and cutting arm speed regulation in unmanned tunneling systems.

A low-profile ultra-wideband magneto-electric dipole antenna for ground penetrating radar

ABSTRACT Ultra-wideband antennas that operate at low frequencies usually have a large geometry, which makes them very limited in practical engineering application environment where space is often constrained. In this paper, a novel low-frequency low-profile ultra-wideband magneto-electric (ME) dipole antenna is designed for the application in ground penetrating radar (GPR) to detect deeply buried targets. The antenna is designed at the operation frequency of 230 MHz, so that the objects that are buried as deep as 1.5 m can be detected. Compared to the traditional low-frequency _antennas, it has a profile as low as 740 mm × 140 mm × 150 mm ( 0.49 λ × 0.09 λ × 0.10 λ ). Based on the simulation analysis and validation measurements, the proposed ME dipole antenna has a wide impedance bandwidth for S 11 < − 10 dB from 135 MHz to 382 MHz even when environmental influence is considered. The antenna is further validated with a GPR experiment, where a pipeline with a diameter of about 200 mm at 1200 mm beneath the road surface is successfully detected by an impulse GPR system where the proposed antennas are integrated.

Investigations into optimum non‐periodic bursts scheme in radar pulse train designed for fixed‐wing drone detections by multi‐function radar

AbstractDrone surveillance with multi‐function radar (MFR) can benefit a lot from the careful radar pulse train organisation into dedicated sub‐RPTs serving particular needs of tasks. In contemporary scenarios of MFR applications, where navigation, search and rescue, and natural environment safeguarding are to be shared, of particular importance is a case where airborne small drone detection radar performs other tasks concurrently. Resource sharing within the radar unit is based on variables and unpredictable circumstances, leading to strains in resources in MFR. Consequently, such constraints limit MFR functioning with optimal drone sensitivity for its own sake. To ensure a high quality of radar services performed quickly, with a low DC power consumption, the task sharing approach by the common MFR platform, non‐periodic bursts emission of radar pulse energy has gained our major attention. At the same time, it was assumed that bursts feature periodic time intervals between radar pulses, which is a favourable circumstance in the control and implementation of signal processing. Each sub‐RPTs is designed to cope with particular detection tasks. One to four linear polarisations (VV, VH, HV, HH) are activated. The focus of the investigation was on the radar emitting a few thousand pulses per second, but only a few 10 pulses per second were expected to be required to detect small airborne drones. The core of the research study was the optimisation process of the scheme operating with 4 to 16 pulse bursts optimised for drone detection with a modest use of resources at MFR. While performing several activities, the X‐band MFR platform called ENAVI was developed in‐house. The proposed non‐periodic burst scheme optimisation approach was validated with in‐field tests with the ENAVI radar model. The in‐air target was a 3‐metre fixed‐wing drone having low RCS and flying at different altitudes with a speed close to 200 km/h. The radar antenna was a 26 dBi low‐profile dual‐polarisation array making it feasible to detect drones remaining a few degrees off the antenna breadboard direction. A very high likelihood of detection of drones from a few kilometres distance was demonstrated within one second. The authors present the effectiveness of the cell‐averaging technique which proved to correctly detect drones within a 7‐km range, and how MFR radar echoes can be used for basic weather surveillance. One vertical VV polarisation was used for drone detection and two VV and VH polarisations for weather observation. Weather radar capabilities were examined against heavy rain clouds imposing a hazard to the safety of drone flights.

Graphene-Based Tunable Polarization Conversion Metasurface for Array Antenna Radar Cross-Section Reduction.

A graphene-based tunable polarization conversion metasurface (PCM) was designed and analyzed for the purpose of reducing the radar cross-section (RCS) of array antennas. The metasurface comprises periodic shuttle-shaped metal patches, square-patterned graphene, and inclined grating-patterned graphene. By adjusting the Fermi energy levels of the upper (μ1) and lower (μ2) graphene layers, different states were achieved. In State 1, with μ1 = 0 eV and μ2 = 0.5 eV, the polarization conversion ratio (PCR) exceeded 0.9 in the bandwidths of 1.65-2.19 THz and 2.29-2.45 THz. In State 2, with μ1 = μ2 = 0.5 eV, the PCR was greater than 0.9 in the 1.23-1.85 THz and 2.24-2.60 THz bands. In State 3, with μ1 = μ2 = 1 eV, the PCR exceeded 0.9 in the 2.56-2.75 THz and 3.73-4.05 THz bands. By integrating the PCM with the array antenna, tunable RCS reduction was obtained without affecting the basic radiation functionality of the antenna. In State 1, RCS reduction was greater than 10 dB in the 1.60-2.43 THz and 3.63-3.72 THz frequency ranges. In State 2, the RCS reduction exceeded 10 dB in the 2.07-2.53 THz, 2.78-2.98 THz, and 3.70-3.81 THz bands. In State 3, RCS reduction was greater than 10 dB in the 1.32-1.43 THz, 2.51-2.76 THz, and 3.76-4.13 THz frequency ranges. This polarization conversion metasurface shows significant potential for applications in switchable and tunable antenna RCS reduction.

Gradient-Based Aero-Stealth Optimization of a Simplified Aircraft

Modern fighter aircraft increasingly need to conjugate aerodynamic performance and low observability. In this paper, we showcase a methodology for a gradient-based bidisciplinary aero-stealth optimization. The shape of the aircraft is parameterized with the help of a CAD modeler, and we optimize it with the SLSQP algorithm. The drag, computed with the help of a RANS method, is used as the aerodynamic criterion. For the stealth criterion, a function is derived from the radar cross-section in a given cone of directions and weighed with a function whose goal is to cancel the electromagnetic intensity in a given direction. Stealth is achieved passively by scattering back the electromagnetic energy away from the radar antenna, and no energy is absorbed by the aircraft, which is considered as a perfect conductor. A Pareto front is identified by varying the weights of the aerodynamic and stealth criteria. The Pareto front allows for an easy identification of the CAD model corresponding to a chosen aero-stealth trade-off.

Dimensional tolerance optimization of SAR antennas with uncertainty quantification and reliability analysis based on structural-electromagnetic coupling model

The dimensional tolerances greatly impact the structural-electromagnetic performance of spaceborne synthetic aperture radar (SAR) antenna. However, few works have conducted the tolerance allocation of the extendible support structure to guarantee system reliability. To bridge the above gap, an integrated optimization methodology is proposed to design the dimensional tolerances with the structural-electromagnetic coupling model in this study. First, the absolute nodal coordinate formulation is developed to predict the structural deformation triggered by the dimensional deviations. Then, the coupling relationship between the displacement field and the electromagnetic field is elucidated for the SAR system. Subsequently, taking advantage of the surrogate model and the parallel update criterion, the interval uncertainty quantification stemming from dimensional tolerances is executed to quickly identify the worst-case scenarios of structural response. Moreover, a multi-point selection strategy is incorporated into the adaptive Bayesian probabilistic integration with active learning, which significantly improves the computational efficiency of electromagnetic reliability. Based on the above tolerance analysis, the inverse optimization design of the dimensional tolerance is realized by the particle swarm algorithm. Finally, the effectiveness and superiority of the proposed methods are validated in the case study. Our innovative framework and analytical methodology not only furnish a comprehensive structural-electromagnetic coupling model but also transition the design paradigm from experiential to robust tolerance allocation.

Active on-orbit surface accuracy adjustment for spaceborne antennas based on multi-fidelity adaptive migration learning strategy

For the large spaceborne synthetic aperture radar antenna, its surface accuracy has a decisive impact on the on-orbit electrical performance, which is affected by manufacturing errors, assembly misalignments, and thermal deformations. Therefore, ensuring the surface accuracy on orbit and reducing its fluctuation are highly concerned issues for the large spaceborne antenna in practice. To this end, this study proposes an active adjustment method based on a multi-fidelity adaptive migration learning strategy to guarantee on-orbit surface accuracy. First, the theoretical surface accuracy model considering space thermal deformation is completely established. Then, the surrogate model of surface accuracy is developed to realize fast prediction and optimization, in which a new dynamic Kriging modeling method is proposed. Furthermore, the surrogate prediction model at other sites on the orbit is efficiently obtained by an innovative multi-fidelity migration learning strategy. On this basis, the active adjustment optimization model is constructed based on the surrogate prediction model, and the corresponding adjustment amounts can be obtained accordingly by solving this optimization problem. Finally, the effectiveness and advantages of the proposed method are comprehensively proven through case studies and experimental verification.

Object detection based deinterleaving of radar signals using deep learning for cognitive EW

In a real-world environment, multifunction radars (MFRs) pose major challenges to the electronic support system that is a part of cognitive electronic warfare. One of the main problems is deinterleaving of signals belonging to MFRs. The ability of MFRs to change their carrier frequency, pulse width, and pulse repetition interval (PRI) from pulse to pulse makes the deinterleaving task challenging. In this paper, an object detection based deinterleaving approach exploiting amplitude patterns caused by radar beam motions, which are determined based on radar antenna scan types, is proposed to deinterleave MFR signals. Amplitude patterns are created in two-dimensional images using amplitude (AMP) and time of arrival (TOA) parameters obtained from radar pulses. Deinterleaving is performed using a deep learning algorithm applied to these images. To the best of the authors’ knowledge, object detection based deinterleaving of radar signals using AMP-TOA images has not been considered so far. Contrary to the common approaches, in which searching for PRI patterns is required, amplitude patterns formed by the radar beam motions on the electronic support system are used in the proposed method. This enables robust identification of signals of MFRs having PRI, carrier frequency, and pulse width agility. With the proposed method, the intention of the radar, i.e., search or tracking, can be acquired in the deinterleaving stage, which ensures earlier situational awareness. The performance of the method is evaluated for varying number of radar signals from one to five through simulations, in which scenarios with missing pulses at different rates are considered. Simulation results demonstrate that, on the average, more than 0.98 mean average precision (mAP50) is achieved at 30% missing pulse rate. The performance of the method for search radar signals is slightly lower compared to that achieved for tracking radar signals due to the lower number of pulses received by the system. However, more than 0.93 AP50 is achieved for search radar signals in the presence of five radar signals with different missing pulse rates. Besides, real-time performance can be achieved using the proposed method on the GPU platform.