Acceleration technique based on ray-tracing to analyze the RCS in open cavities

In this paper, a study on the optimization of fuzzy classifier using radar cross section(RCS) values is presented to classify shell- shaped targets. Method of moments(MOM) is exploited to construct RCS database of generic shell-shaped targets in uniform angular intervals. Relative orientations are estimated from various flight scenarios of shell-shaped targets, and associated RCS values are inter-polated from the generated RCS database with uniform angular intervals. Initial membership functions are determined using the inter-polated RCS values, and particle swarm optimization(PSO) is utilized to optimize the membership functions of the fuzzy classifier in terms of probability of correct classification.Key words: Classification, Fuzzy, RCS, PSO]$ 2013^4LIG_1` $ C `78$ abc.d e fg-hij@fhg(Department of Electrical Engineering, Pohang University of Science and Technology) *LIG_1`(LIGNEX1) Manuscript received December 12, 2013 ; Revised January 13, 2014 ; Accepted February 10, 2014. (ID No. 20131212-127)Corresponding Author: Kyung-Tae Kim (e-mail: kkt@postech.ac.kr)

In through-the-wall radar (TTWR) applications, scattering by indoor clutter elements can greatly confound the detection of humans. This paper analyzes the spectral and azimuthal scattering characteristics of various types of individual furniture targets and compares these to humans. Radar cross section (RCS) values of furniture and humans are obtained using the finite difference time domain (FDTD) technique over the 1-5 GHz frequency range and the 0-360 azimuth angle range for both co- and cross-polarized scattering. In the case of furniture, RCS responses show to the highest returns when viewing the planar surfaces of the clutter objects. Objects consisting primarily of smaller planar surfaces with more complex geometrical features showed a more uniform response with no preferred orientation showing a larger response. Human RCS produced from the biological models showed a more constant RCS when viewing the co-polarized response, where the back produced the highest response due to the more planar surface. The cross-polarized response was more varied providing for a wider range of RCS values.

Radar cross-section (RCS) is an important study parameter for defence applications specially dealing with airborne weapon system. The RCS parameter guides the detection range for a target and is therefore studied to understand the effectiveness of a weapon system. It is not only important to understand the RCS characteristics of a target but also to look into the diagnostic mode of study where factors contributing to a particular RCS values are studied. This further opens up subject like RCS suppression and stealth. The paper discusses the RCS principle, control, and need of measurements. Classification of RCS in terms of popular usage is explained with detailed theory of RF imaging and inverse synthetic aperture radar (ISAR). The various types of RCS measurement ranges are explained with brief discussion on outdoor RCS measurement range. The RCS calibration plays a critical role in referencing the measurement to absolute values and has been described.The RCS facility at Reseach Centre Imarat, Hyderabad, is explained with some details of different activities that are carried out including RAM evaluation, scale model testing, and diagnostic imaging.Defence Science Journal, 2010, 60(2), pp.204-212, DOI:http://dx.doi.org/10.14429/dsj.60.341

In this study, a radial basis function neural network approach is applied for the estimation of the localization and the radius of a conducting cylinder with a circular cross-section coated with a dielectric material. A set of features, the radar cross-section (RCS) values, are derived from scattered fields, which are calculated using the surface equivalence principle and the method of moment. RCS values are obtained using 10 different scattering angles that are fed into the network. The outputs of the network are the location (x_0, y_0) and the radius (r_p) of the conducting cylinder. This is an application of the electromagnetic inverse scattering of the objects embedded in a material based on the use of a neural network.

This paper presents the characteristics of radio wave scattering from rough sea surfaces in Ka-band. The physical optics method, which is one of the high frequency approximation algorithm, is employed to calculate radar cross section of electromagnetic simulation models of rough sea surfaces with Ship-EDF software. Rough sea surfaces are divided into six levels according to the wind speed over them. The simulation results show the effection that wind speed, the grazinng angle and frequency of radio wave have on the monostatic radar cross section of rough sea surfaces under the conditions of both horizontal and vertical polarization. With the increase of the roughness of sea surfaces and grazing angle of radio wave, the radar cross section value of rough sea surfaces increase. The frequencies of Ka-band have little contribution to the radar cross section value.

Abstract. As a result of increasing use of wind energy as a sustainable source of electricity, large Wind Parks with numerous Wind Turbines have been constructed. Wind turbines are extremely tall objects consisting of stationary and moving parts. The presence of wind turbines in the vicinity of weather radar systems can significantly impact their performance, leading to false alarms and errors in radar measurements. Accurate weather forecasting is challenging in this circumstance. Large Radar Cross Section (RCS) of wind turbines results in interference, also known asWind Turbine Clutter (WTC) orWind Turbine Interference (WTI), within and beyond the radar main beam, Multipath Interference (MPI), and phenomena referred to as ”shadowing effects” behind the wind turbines. These effects vary significantly in both time and space as a result of various wind turbine operations and meteorological conditions. It can often be difficult to distinguish wind turbine returns from weather-like signals. For the assessment of WTC or WTI, it is essential to understand the scattering properties of these wind turbines. In this paper, the bistatic scattering characteristics of a wind park turbine using a Unmanned Aerial Vehicle (UAV)-mounted receiver recording C-band weather radar signals were investigated by determining the average received power (PRxAvg (θs)) and RCS of wind turbine as a function of the scattering angle. For this purpose, the measurements and data provided by the German Meteorological Service (DWD, DeutscherWetterdienst) were utilised. The average received power as a function of scattering angle (θs) was calculated by using I-Q (In-phase and Quadrature) signals. Forward, back and side scattering of the calculated average received power were analysed separately. Moreover, Front-to-Back ratio, Front-to-Right side ratio and Front-to-Left side ratio were calculated and compared using forward, back and side scatter values. RCS values were also calculated depending on the scattering angle (θs) of the wind turbine.

Drones and birds are typically small, slow targets that fly at a low altitude that surveillance radar systems cannot easily detect. Classic radar detection based on signal amplitude threshold detection. If the envelope of the receiver output exceeds a pre-established threshold, a signal is described as present from a target. The entire premise of amplitude detection is that RCS of an object is larger than the noise in a background, and the signal-to-noise ratio (SNR) is utilized to maintaining the detection probability. If the detection probability is larger than 50%, the SNR of the target is at least 13.1 dB for single pulse detection. This method sometimes fails to detect those weak signals at a long distance due to their small radar cross section (RCS) values and low velocities. Here, we propose a novel radar detection method based on detecting signal to clutter ratios (SCR) in the spectrum. The SCR is identified as the ratio between the spectral peak amplitude of the target to the mean amplitude of the entire spectrum. Although the spectral peak amplitude of the target is lower along the increasing range, the power of the background clutter decays as well. Therefore, SCR value of a target is independent of the detection range. This is useful for detecting targets with small RCS values, including birds, drones, vortex et.al. Theoretically, by using the SCR threshold, the detection range of a target can be as long as the range when the Doppler frequency is unambiguous. We present detection results of birds and drones by using a Ku-band pulsed Doppler radar. When we set the SCR detection threshold at 8 dB, we can detect radar echoes from birds and drones in different channels and range gates well, even at the range of 10km from the radar. We find that birds and multirotor drones have the similar SCR. When using SCR to detect a target, the crucial problem is the recognition of the target peaks, because the false alarm rate must be controlled.

The main goal of the paper is to develop a Frequency Modulation Interrupted Continuous Wave radar simulator. The radar working frequency is 35.4 GHz and it is intended to detect clouds. The simulated output data are compared with output data acquired by the real radar. The real data are acquired from the observation of a static object - the chimney. Radar Cross Section (RCS) of the chimney is calculated and used for simulations. RCS value is used in the simulation for better approximation of results. Paper contains a method for detection based on Power Spectral Density.

Detection of thin wires for different purposes is a frequently studied subject in the literature. It is aimed in this study to investigate the EM behavior of conducting thin wires. The radar cross section (RCS) value of a thin wire varies depending on the angle of incidence and frequency of the electromagnetic wave. Wire targets are considered in this study as cylindrical object, and the monostatic RCS simulation results are obtained depending on the frequency and the angle of incidence of the wave. As a result of these simulations, it has been surprisingly observed that the RCS value increased with the decrease in frequency in case for oblique incidence angle for thin wires, while for normal incidence angles we observed an inverse relationship as expected. High range and cross range resolution are needed for the high detection accuracy and at the same time to distinguish the multiple wires. In this study, to meet these requirements stripmap mode SAR system is established experimentally with high bandwidth signal. Time Domain Back Projection (TDBP) algorithm is applied to the measured SAR raw data and SAR images of wires are obtained. Finally, the frequency dependent detection and ranging accuracy for the thin wires lying on the ground in the target area is observed.

The paper considers results of researches of influence of unorthogonal of edges of the trihedral corner reflectors (TCR) with triangular edges on changes of the maximum and median values of the radar cross section (RCS) within the central lobe of back scattering diagram (BSD) in wide frequency band. Fluctuations of RCS on frequency in radio frequency range are considered. Expressions for assessment of maximum deviation of results of calculation of RCS within the central lobe of BSD TCR with triangular edges caused by unorthogonal of their edges are presented. The received estimates of mean square deviation of the analyzed values for RCS TCR in working frequency band give the chance to compare the calculated values of RCS within the central lobe of BSD with results of electrodynamic modeling by method MoM taking into account reclining of their edges. These results can be used for the benefit of phonotarget information support of space means of arms and also when carrying out tests of samples of space arms. The provided scientific result gives the chance of assessment of RCS TCR RCS within the central lobe of BSD in wide frequency band with a margin error smaller, than at direct measurements of RCS.

Abstract: Radar-based pedestrian detection is a key enabler of advanced driver-assistance systems (ADAS) and future autonomous driving functions, particularly under conditions where vision sensors are limited by poor lighting or adverse weather. In this study, we present a structured dataset collected at the ZalaZONE proving ground, a state-of-the-art automotive testing facility in Hungary, using a Continental ARS 408‑21 automotive radar operating at 77 GHz . The dataset contains static radar measurements of both a real human subject and a pedestrian dummy, recorded at multiple controlled distances (5 m and 10 m) and orientations (front-facing and side-facing). Each radar scan includes radar cross-section (RCS), object distance, relative velocity, and metadata retrieved directly from the vehicle’s CAN bus interface. The results demonstrate that RCS values strongly depend on target type, orientation, and distance. Real pedestrians produce significantly higher variance due to posture, clothing materials, and micro‑movements, whereas dummy mannequins exhibit stable, narrow RCS distributions. Interestingly, measurements at longer distances show less negative RCS values, likely influenced by multipath reflections and environmental dispersion effects. The dataset is fully labeled and formatted for direct use in supervised machine learning pipelines, supporting classification models such as logistic regression, support vector machines, and neural networks. It also pro-vides a foundation for future extensions with dynamic scenes and temporal sequence modeling, enabling the development of more robust and generalizable radar-based pedestrian detection algorithms. By combining controlled measurements with realistic environmental variability, this dataset contributes to the advancement of radar sensing technologies for safe and reliable autonomous driving. Quantitatively, the mean RCS difference between real pedestrians and dummy targets reached 3.8 dB at 5 m and 4.5 dB at 10 m, confirming the discriminative potential of the dataset for classification tasks.

The paper considers the influence of the interaction of the object under test with the top part of the pylon on the results of radar cross-section (RCS) measurement. The computer simulation of an experimental RCS measurement of the object in the field of a plane wave is carried out. The computations are performed in the FEKO program by the method of moments. Zones of the pylon that most affect the single-position RCS values of the object have been identified. These zones must be covered with a radar absorbing material (RAM) when conducting experimental studies of the objects scattering properties. The errors of the RCS measurement for two types of objects - spheres and vertically located cylinders - depending on the levels of the measured values are revealed. Three sizes of objects by their RCS values are considered to evaluate the measurement error at levels of approximate 0.1 m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> , 0.01 m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> , and 0.001 m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> .

For RCS (Radar Cross Section, RCS) measurements at a high grazing angle, target echo is generally easy to measure because it is much larger than background clutter. However, it is widely known that calibration technology becomes more difficult in this low signal to noise ratio situation especially. After a great number of experiments, this paper puts forward a new calibration method of broadband radar system at a high grazing angle, in other words, we choose calibrate toward radar system on the ground. In free space situation, amplitude and phase of metal ball is easily obtained, target’s RCS at a high grazing angle is also achieved with revised coefficient according to the metal ball. The experiments results present that this method meets accurate calibration precision and field variation in metal ball area is well-distribute. The error between measured RCS and theoretical values is less than 0.5 dB.

: In a comparison of measured, simulated, and theoretical calculations of radar cross section (RCS), the radar target was a simple missile shape (a cylinder with hemispherical ends). For the measurements, the target was rotated on a turntable from 5 to 365 deg in azimuth, and its RCS was measured with a W-band frequency agile instrumentation radar. (Clutter and noise in the measured RCS data were reduced by spatial filtering.) For modeling the target geometry, the ACAD (advanced computer aided design) geometric modeling program was used to create both an IGES (initial graphics exchange specification) and a facet model. For modeling the RCS, three high frequency prediction codes were used (Xpatch, CADDSCAT, and NcPTD), as well as a point scatter model. Various methods were used to process and simulate the target returns, depending upon the aspect angle. Agreement between the measured and simulated bandwidth averaged RCS values depended on the portion of the target that dominated the radar return: agreement was close for radar returns dominated by returns from the hemispherical ends of the target. However, for aspect angles near broadside to the target (for which the cylindrical part of the target dominated the returns), RCS measurements suggested an interaction between the target and the pylons supporting it.

During radar operation, changes in the radar cross section (RCS) of a target have an adverse effect on the radar detection performance. In particular, the RCS of a target with high maneuvering characteristics can be changed rapidly. Therefore, a precise prediction of the RCS change is essential for satisfactory radar detection performance. In this study, a modeling and simulation (M&amp;S) tool was developed for the estimation of radar detection performance. The M&amp;S tool comprises a radar model, target model, and wave propagation model. In particular, pre-obtained RCS simulation data were utilized to consider the effect of the RCS change of the target. Using the developed tool, the RCS based on the relative attitude is extracted from the RCS simulation data and the RCS processed data using the moving average method. The M&amp;S model is verified by comparing the two test results with the radar received signal power. Consequently, we verified that when using the RCS manufacturing data, the signal power is more similar to the test data than the other RCS simulation methods. It is expected that the radar performance on the high-maneuvering target can be estimated using the developed M&amp;S tool.