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This paper presents research validating the forward scattered wave in bistatic radar geometries. In contrast to monostatic radar, where transmitter and receiver are collocated, bistatic radar incorporates receivers positioned in different locations from the transmitter. In the case of forward scattering, the receiver is positioned in the far field behind the reflecting target in line of sight of the transmitter. The paper describes forward scattering physics and presents forward scatter radar cross section measurements conducted at the Naval Air Warfare Center Weapons Division (NAWCWD) Radar Reflectivity Laboratory (RRL), which are validated with computational electromagnetic predictions.
Monolithic radomes for aircraft nosecones are designed for maximum transmission, minimum sidelobe increase, and minimum beam deflection at the desired radar frequency. In some cases, a radome may have a position dependent thickness to account for radar incidence angle. These radomes are manually tuned with an iterative process that uses radio frequency test range measurements to guide placement of tuning tape on to the radome. Generally, the radomes are thinner than desired, and the tuning adds an appropriate number of tape layers to center the optimum transmission window in frequency. This trial-and-error method is time consuming and range measurements are costly. Instead, this paper discusses an alternative method that is faster and less resource intensive. A microwave spot probe is raster scanned around the radome surface, and an algorithm inverts the electrical thickness at each measurement location from the measured reflection amplitude and phase. This thickness map is compared to the desired thickness and the appropriate number of tuning tape layers are calculated. This paper demonstrates the spot-probe method with a canonical wedge-shaped radome, where one side of the radome was purposely too thin. In addition, a lens-based far- field range is used to measure transmission efficiency and apparent beam deflection error of the wedge radome before and after it is tuned with fiberglass tape.
A new sparse sampling and compressive sensing based reconstruction and near-field imaging technique is introduced for the measurement of electrically large production test and diagnostics of nose-mounted commercial radomes. Simulated results are presented, where it is demonstrated that far- field results with an equivalent multi-path level of better than - 60dB can be obtained from circa 10% of the points required by a classical Nyquist equiangular spherical near-field acquisition scheme for the case of an electrically large, i.e. full size, commercial airliner nose-mounted radome enclosing an x-band weather radar. Furthermore, a new method for the rapid noninvasive nondestructive imaging and identification of defects within these radomes is presented that provides significantly clearer fault detection at a far earlier stage within the radome measurement campaign than has previously been possible.
This paper presents the design and simulation-based evaluation of a high-resolution millimeter-wave (mmWave) MIMO (Multiple-Input Multiple-Output) antenna array system for non-invasive medical diagnostics. The system is specifically optimized for applications such as early-stage tumor detection and soft tissue anomaly mapping, where high spatial resolution and tissue penetration are crucial. A 4×4 MIMO antenna array operating in the 28–40 GHz frequency band is proposed, leveraging the inherent advantages of mmWave frequencies— namely, shorter wavelengths for finer imaging resolution and wide bandwidth for enhanced contrast.The MIMO antenna array is designed using Rogers RT5880 substrate with a dielectric constant of 2.2 and a thickness of 0.787 mm to ensure minimal dielectric loss and mechanical stability. High-fidelity electromagnetic simulations were conducted using ANSYS HFSS to validate the antenna design. The resulting 3D radiation patterns confirm the beam directivity and uniform power distribution across all elements. The array was then integrated into a synthetic aperture radar (SAR)-based imaging model in MATLAB, where point- spread function (PSF) analysis revealed a lateral resolution of 3.2 mm and an axial resolution of 2.5 mm at 35 GHz. Imaging simulations on a multilayer human tissue-equivalent phantom model—comprising skin, fat, and muscle layers—demonstrated the system’s ability to resolve dielectric contrasts simulating benign and malignant tissue anomalies. The proposed MIMO antenna array enables real-time, contactless, and radiation-free imaging, positioning it as a cost-effective alternative to traditional imaging modalities such as X-ray or MRI for preliminary screening and continuous monitoring. The fully simulated results validate the concept’s feasibility and effectiveness for non-invasive medical diagnostics, particularly in point-of-care settings.
One of the most important key performance indicators of Reconfigurable Intelligent Surfaces (RISs) represents the RIS reflection or bistatic RIS Radar Cross Section (RCS) pattern, which needs to be evaluated under Far-Field (FF) conditions. Since a bistatic setup that fulfills FF conditions is mechanically complex, expensive and results in a large setup footprint, the measurement of RIS reflection patterns within a monostatic setup is proposed. Subsequently, the monostatic pattern results are transformed into bistatic patterns using a Monostatic to Bistatic Equivalence Theorem (MBET). This approach reduces the total measurement time tremendously. However, the state- of-the art MBET proposed for RIS measurements, is limited to 1-D pattern application, where the illumination-/transmit- and the probing-/measurement- antennas are located in the same plane. As RIS can also be configured to reflect off-the-plane, the evaluation of 2-D scenarios is crucial. With the state-of-the-art 1-D MBET such scenarios cannot be investigated. To close this gap, this paper derives a novel 2-D MBET well suited for RIS measurements. The novel MBET is validated with an analytical metal plate reflection model, by comparing the resulting 2-D MBET transformed monostatic pattern with the bistatic reference pattern. This procedure is repeated for measurement and simulation data of two different RIS prototypes designed for the mmWave frequency range. The deviation of the resulting patterns after applying the novel derived MBET from the bistatic reference patterns is analyzed based on the pattern difference metric. This difference metric evaluated in the main cuts exhibits a worst case mean value of –24dB which proves the suitability of this novel MBET for 2-D RIS measurements.
Radar Cross Section (RCS) computation plays a critical role in the design and analysis of scattering objects in both civilian and military applications. Reliable and efficient simulation tools enable RCS minimization during the design phase, reducing reliance on measurements to the final stages of development. Two main classes of techniques are typically used for RCS prediction: high-frequency asymptotic methods and full-wave numerical methods. Unlike high-frequency approximations, full-wave methods such as the Method of Moments (MoM) provide highly accurate results by rigorously solving Maxwell’s equations removing any approximation. However, their application to electrically large problems is limited by high computational and memory cost. In this paper we present results from an efficient and accurate full-wave solver when computing the mono-static RCS of electrically large structures. The solver employs higher-order basis functions to reduce the number of unknowns and the Multilevel Fast Multipole Method (MLFMM) to significantly lower memory usage and computational time. Additionally a new so-called Fast Direct Solver (FDS) is utilized for a smaller selection of these RCS calculations. After a brief description of the implementation, several application cases are presented and validated against measurements and benchmarks, demonstrating the capability to handle complex scenarios with short simulation times and cost-effective hardware.
The primary role of an anechoic chamber is to provide a reflection free environment that can be used for electro-magnetic measurements, with antenna pattern being one of the most prominent measurements utilizing anechoic chambers. Real world anechoic chambers, however, rarely provide a reflection free environment. Reflections in an anechoic chamber can arise from a mismatch between the absorber size and the frequency used, the angle of incidence between the absorbers and the wave front, various metallic objects inside the chamber and more. As reflections can introduce impairments in the measurements, it is highly desirable to measure an anechoic chamber for reflections and reduce these reflections as much as possible (especially in the designated “quiet zone”). This paper introduces an innovative reflection evaluation method that harnesses both communication processing and radar processing to localize reflection sources in an anechoic chamber. The chamber setup consists of a probe and an antenna under test (AUT). The probe emits a signal, which is directly received by the AUT along with reflections within the anechoic chamber. Employing either a frequency modulated continuous-wave (FMCW) or stepped-frequency signal, the indirect path length is estimated, resulting in a ellipsoid representing potential reflection points. By intersecting multiple ellipsoids generated through relocating the probe and projecting the intersection onto the chamber, the reflection location is determined. The method’s efficiency has been demonstrated through implementation and validation in an anechoic chamber, with the paper presenting real measurement results for validation purposes.
With the increasing number of channels in integrated radar MMICs, radar modules and networks, beamformer calibration techniques must adapt to the physical dimensions of these sensors. Typical far-field calibration requires measurements at the Fraunhofer distance. This ensures a maximum phase error of 22.5° over the aperture. However, literature shows that phase errors below 5° are required for acceptable side-lobe suppression. Compact Antenna Test Ranges (CATR) create virtual far-field conditions in limited space but unfortunately they introduce magnitude and phase errors in their measurement. A method for calibrating MIMO radars in CATR settings is presented using spatial averaging to reduce these errors systematically. Simulations with a 16-channel FMCW radar show maximum errors of below 0.25dB for magnitude and less than 2◦ for the phase with a single-digit number of spatial averages. Calibration with a 77-GHz MIMO radar sensor in the CATR confirms the technique’s ability to mitigate test zone non-idealities, improving radar imaging quality.
This paper presents a system-level simulation methodology for large-scale active antenna arrays, demonstrated through a 32-port phased-array antenna designed for 5G base station applications in the 3.3-3.8 GHz band. The methodology integrates electromagnetic simulation of the antenna array with behavioral modeling of power amplifiers (PAs) under realistic impedance mismatch conditions. A reduced Polyharmonic Distortion model for the PAs is extracted using load-pull measurements, enabling accurate prediction of nonlinear behavior and memory effects. The 32-element array, simulated in CST Studio Suite, is characterized by a multi-port S- parameter matrix that captures inter-element coupling and active reflection coefficients. These models are incorporated into a system simulation using IVCAD Suite, which computes incident and reflected power waves at all nodes, facilitating beam-steering simulations with variable scan angles and frequencies. The results illustrate how beam-steering alters the active impedance seen by each PA, affecting gain, output power, and power-added efficiency. This workflow allows for fast, scalable, and accurate performance evaluation of active antenna systems without requiring circuit-level simulation or costly hardware setups, making it particularly valuable for dense 5G arrays or radar front-ends.
In support of the National Science Foundation Next Generation Radar Designs Mid-Scale-Research-Infrastructure-1 (MSRI-1) project, Raytheon, an RTX company, has finished preliminary design of a high power phased array transmitter for integration onto the 100-meter Green Bank Telescope (GBT). GBT is the largest steerable radio astronomy antenna in the world located in Green Bank, WV. This system combines a fixed transmit-only phased array with a steerable reflector system. Due to the unique size and architecture of the Green Bank Telescope assembly, along with the power output of a fully collimated transmitter, a safe terrestrial calibration reflector is not a readily convincible option. As such, a novel calibration approach for the high-power transmitter feed is necessary, combining radio astronomy techniques for receive-only calibration in combination with a purposeful rigidity of variables for a valid transmit-only calibration. Additionally, due to the number of individual transmitter elements involved, a wideband calibration waveform is proposed for separable over-the-air calibration of all the individual transmitter elements on a drastically reduced timescale. This paper walks through the patent-pending Raytheon proposed calibration process and the details of this novel approach.
This paper presents a novel broadband dual-polarized low radar cross-section feed, designed for enabling an ultra Compact Antenna Test Range (CATR) with focal length shorter than 60% of the quiet zone diameter. The feed achieves a 50° half-power beamwidth across a 3:1 bandwidth. Key innovations include a broadband quad-ridged junction orthomode transducer with coaxial-to-waveguide transition and a hollow dielectric waveguide diffusing lens that lowers directivity, while maintaining a stable phase center over frequency. Two feed variants are demonstrated: one optimized for low path loss and another for improved quiet zone uniformity. Numerical simulations and measurements confirm a performance comparable to or even better than traditional circular corrugated choke horns, which require significantly larger volume and multiple units to cover the same bandwidth.
Group delay (GD) is a critical parameter in satellite payloads and radar systems, directly impacting overall system performance. Although several antenna group delay measurement methods exist, most overlook the challenges posed by frequency conversion chains commonly used in these applications. This paper introduces a method to accurately address this issue by implementing an additional calibration step of the vector network analyzer (VNA) using a harmonic phase reference (HPR). The method is validated through far-field measurements on a device equipped with a mixer.
This work presents an integrated 3D-printed ultra-wideband (UWB) graded-index (GRIN) lens antenna that offers a simple, efficient, and cost-effective solution to the inherent wide beamwidth and asymmetric radiation problems of the commercial wideband antenna probes. The integration of the proposed antenna enables the effective use of these wideband probes on UAV/UAS platforms, which was previously not feasible due to the aforementioned problems. The proposed integrated antenna system covers a wide range of frequencies from 3 to 32 GHz, enabling the use of a single probe antenna for in-situ UAV-based calibration of maritime, weather, surveillance, and airborne radars. The proposed GRIN lens provides symmetric radiation patterns and reduced half-power beamwidth performance, especially in the lower part of the frequency band between 3 to 7 GHz, where the commercial UWB ridged-horn probes have significantly wider beamwidth values. Measured results show that the integration of the GRIN lens achieves a relatively constant beamwidth as well as an average beamwidth reduction of around 68% in both E- and H-planes, meeting the probe antenna performance requirements for radar characterization using UAVs/UAS.
This paper presents a computational imaging method that uses a metasurface-based transmitting antenna to reconstruct high-resolution scattering signatures of arbitrarily shaped radar targets. Instead of relying on mechanical scanning or bulky antenna arrays, the proposed approach takes advantage of programmable phase distributions on a metasurface to generate diverse illumination patterns. These patterns help encode different scattering responses from the target, which are collected by a single receiving antenna. The scattered electric field is modeled as a linear matrix equation. This model includes the effects of each transmitting unit cell, the distribution of equivalent point scatterers on the target surface, and the propagation paths between the transmitter, the target, and the receiver. The result is a forward model that links randomized metasurface phase patterns to the measured backscattered field. To achieve high-resolution image recovery, a large number of unknowns—representing the complex amplitudes of point scatterers—must be estimated. Although multiple phase masks are used to increase measurement diversity, the number of measurements is still much smaller than the number of unknowns, making the system underdetermined. To solve this, we use a compressive sensing technique known as basis pursuit denoising (BPDN), which finds sparse solutions in the complex domain and enables accurate reconstruction despite the limited data. We verify the proposed method using numerical simulations on canonical radar targets. The reconstructed images show high similarity to the original targets, confirmed by quantitative comparisons such as structural similarity indices and error norms. These results demonstrate that the method can effectively extract scattering profiles using a compact, electronically reconfigurable antenna system. This work shows the potential of combining metasurface technology with compressive sensing to build efficient, lightweight radar imaging systems that do not require complex hardware setups.
Advanced Driver Assistance Systems (ADAS) rely heavily on Vehicle-to-Everything (V2X) communication, where radar antennas play a pivotal role. This paper presents the design of a radar antenna operating in the W-band at 77 GHz, achieving a VSWR < 2 and a peak gain of 8 dBi. The optimal placement of this antenna on an electric bike is investigated using the 3D Computational Electromagnetic (CEM) solver, Altair FEKO. Furthermore, Altair WinProp is utilized to analyze wave propagation in dynamic environments, considering pitch, yaw, and roll effects for Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) communications. By integrating transmitting and receiving antennas on the vehicle, realistic drive-test scenarios are simulated to compute field strength, delay, and Doppler effects for each propagation path. Case studies highlight improved radar reliability and enhanced communication capabilities, particularly for two-wheeler applications, emphasizing the system’s adaptability to real-world vehicular environments.
The MIMO radar technique enables high angular resolution by virtually synthesizing a larger number of receiving antennas [1]. This paper leverages this technique to generate reliable point cloud data of an outdoor space, by applying a series of radar processing techniques and a point cloud denoising function. This work provides a comprehensive explanation of our methodology, from calibration and measurements to data processing and plotting. Our strategy is validated through real-world measurements conducted using the cascaded TI AWR2243 radar, highlighting the potential of mmWave MIMO radars in static 3D mapping scenarios and offering insight into practical implementation challenges.
This paper investigates the use of self-supervised learning algorithms to reconstruct a high-quality image directly using data from microwave imaging systems. Specifically, we propose using neural fields, particularly the model entitled Instant Neural Graphics Primitives (InstantNGP) [1], chosen for its balance between speed and ability to capture fine details—to improve the spatial resolution of microwave image reconstructions. The performance of this approach is verified using both simulated and real experimental data of an Inverse Synthetic Aperture Radar (ISAR) operating in the C-band. The real and imaginary components of the complex return signal generated by this simulator were used as ground truth to compare to the predicted/synthesized return signal from the machine learning (ML) model. Both the neural field approach and the conventional reconstruction using matched filtering (MF) were used to produce reconstructed images, and a qualitative comparison between the images was performed. Preliminary results indicate that the ML approach produces reconstructed images with improved range and cross-range resolution compared to those created using a traditional matched filter technique.
This paper investigates measurement uncertainty in a Reverberation Chamber (RC) within the lower FR2 bands (24.25-29.5 GHz). The study focuses on the impact of several factors contributing to RC measurement uncertainty, including finite sample size, polarization imbalance, and spatial non- uniformity. A series of 24 measurements were conducted using a horn antenna, known for its directivity in mmWave frequencies, varying antenna parameters such as height, orientation, position on the turntable, and polarization within a predefined chamber volume. The measurement uncertainty was evaluated by a method based on the standardized 3GPP and CTIA approaches, incorporating uncorrelated measurements and analyzing Pearson correlation coefficients between measurement pairs. An analysis of variance (ANOVA) was performed on the frequency-averaged power transfer function to identify the significance and impact of each variable on measurement variability. Additionally, the K-factor was estimated for each measurement set as part of the RC characterization, using an alternative approach to account for the turntable stirring effect. The findings highlight which variables most significantly influence measurement uncertainty, where the antenna orientation emerges as the most significant factor for the mmWave directive antenna setup.
We present a bench top demonstration of dropped-channel polarimetric compressive sensing to recover range profiles of a simple scene. Four antennas (H and V transmit and H and V receive) are connected to an arbitrary waveform generator and digital oscilloscope with programmable attenuators and phase shifters inline to control crosstalk. Range profiles of the scene are generated for three measured channels; the fourth is reconstructed from information imbedded in crosstalk using basis pursuit denoising. Reconstructed range profiles are shown to agree with measurements of all channels obtained without crosstalk contamination. Thus, the bench top setup demonstrates the potential use of dropped-channel polarimetric compressive sensing to reduce data storage and transmission burden while preserving full pol information.
The impact of receiver internal leakage on planar near-field measurement uncertainty is significantly influenced by the selection of near-field parameters. Understanding how specific scan parameters affect the far-field leakage level is essential for effective mitigation. This paper establishes quantitative relationships between near-field parameters and the far-field peak amplitudes of both leakage and the antenna under test (AUT), as well as the mean noise level in the far-field pattern, based on empirical results. Systematic scans were performed by altering only one or two specified near-field setup parameters per measurement, and graphical comparisons are provided. Practical approaches for mitigating receiver leakage are demonstrated through a case study involving receiver leakage on a planar scanner with a maximum scan area of 3.6 m x 3.6 m (12 ft x 12 ft). Additionally, a method for estimating the far-field receiver leakage level relative to the beam peak is discussed.