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This paper aims to propose a method for accurate radar echo simulation of wind turbines (WTs) array. It can solve the problem of passive interference from wind farms to neighboring radar stations.

First of all, the equivalent model of scattering centers of a single WT is obtained by using the spatial spectrum estimation method, and the accuracy of this model is verified by the scaled model experiment; then scattering centers model of WTs array was established by using the spatial coordinate transformation method. According to the position relationship between the model and the radar, and combined with the multipath scattering theory, the radar echo equation of WTs array was deduced. Finally, the simulation analysis is carried out with the four GoldWind 77/1500 WTs as an example and compared with the traditional methods.

This paper verifies the accuracy of the equivalent model of scattering centers through the WT scaled model experiment, and through simulation analysis, it is found that the result of this method is more consistent with the multipath scattering of radar echo between WTs array in practical engineering than the traditional method.

Based on the theory of high-frequency scattering, this paper introduces scattering centers into the solution of radar echo and considers the multipath scattering of radar echo, then a method for solving the radar echo of WTs array based on scattering centers is proposed.

By reducing the coating thickness of the weak scattering source, the coating weight of the absorbing material can be reduced by 35% with little effect on the RCS.

To alleviate the weight-increasing problem caused by a large number of coating of absorbing materials, a method for zonal coating of absorbing materials for a stealth helicopter was proposed. By appropriately reducing the thickness of the coating at the secondary scattering locations, the amount of coating used is significantly reduced.

Compared with the full-coated, the zonal coating scheme achieves the corresponding RCS reduction effect.

Zonal coating design can achieve the effect of reducing coating weight and cost.

The effects of different coating methods on RCS were verified by electromagnetic scattering simulation, and the applicability of the zonal coating design of the absorbing material to the stealth helicopter was verified.

The purpose of his paper is to study the radar stealth performance of a Y-type quadrotor with coaxial rotors and parallel rotors.

This Y-type quadrotor is designed as an aerodynamic layout with parallel twin rotors at the front and coaxial twin rotors at the rear. The multi-rotor scattering (MRS) method based on multi-rotor dynamic simulation (MRDS) and electromagnetic scattering module (ESM) is presented. MRDS is used to simulate the complex rotation of parallel rotors and coaxial rotors. ESM is used to calculate the instantaneous radar cross-section (RCS) of the quadrotor.

For a single rotor, the minimum period of the RCS curve at a given azimuth is equal to the basic passage time of the blade, where increasing the speed can shorten this minimum period. When the elevation angle increases, the forward RCS fluctuation of the quadrotor increases, while the average RCS decreases. The change of the roll angle will affect both the mean and the maximum difference of the RCS–time curve at the given lateral azimuth. The increase of the pitch angle will enhance the dynamic amplitude of the RCS–time curve under the forward azimuth.

The research in this article can provide reference for the stealth design of the Y-type quadcopter in the future.

The originality is the establishment of the MRS method. This method could provide value for dealing with the electromagnetic scattering problem of coaxial rotors and parallel rotors.

The purpose of this paper is to develop an algorithm, using PCA‐based neural network, to retrieve the vertical rainfall structure in a precipitating atmosphere. The algorithm is powered by a rigorous solution to the plane parallel radiative transfer equation for the atmosphere with thermodynamically consistent vertical profiles of humidity, temperature and cloud structures, together with “measured” vertical profiles of the rain structure derived from a radar.

The raining atmosphere is considered to be a plane parallel, radiatively participating medium. The atmospheric thermodynamic profiles such as pressure, temperature and relative humidity along with wind speed at sea surface and cloud parameters corresponding to Nargis, a category 4 tropical cyclone that made its landfall on May 2, 2008 at the Republic of Myanmar, are obtained by solving the flux form of Euler's equations in three‐dimensional form. The state‐of‐the‐art community software Weather Research and Forecasting has been used for solving the set of equations. The three‐dimensional rain profiles for the same cyclone at the same instant of time are obtained from National Aeronautics and Space Administration's space borne Tropical Rainfall Measuring Mission's precipitation radar over collocated pixels. An in‐house Micro‐Tropiques code is used to perform radiative transfer simulations for frequencies corresponding to a typical space borne radiometer, and hence to generate the database which is later used for training the neural network. The back propagation‐based neural network is optimized with reduced number of parameters using principal component analysis (PCA).

The results show that neural network is capable of retrieving the vertical rainfall structure with a correlation coefficient of over 0.99. Further, reducing the ill‐posedness in retrieving 56 parameters from just nine measurements using PCA has improved the root mean square error in the retrievals at reduced computational time.

The paper shows that combining numerically generated atmospheric profiles together with radar measurements to serve as input to a radiative transfer model brings in the much‐required synergy between numerical weather prediction, radar measurements and radiative transfer. This strategy can be gainfully used in satellite meteorology. Using principal components to reduce the ill‐posedness, thereby increasing the robustness in retrieving vertical rain structure, has been attempted for the first time. A well‐trained network can be used as one possible option for an operational algorithm for the proposed Indian climate research satellite Megha‐Tropiques, due to be launched in early 2011.

This paper aims to discuss the classification of targets based on their radar cross-section (RCS). The wavelength, the dimensions of the targets and the distance from the antenna are in the order of 1 mm, 1 m and 10 m, respectively.

The near-field RCS is considered, and the physical optics approximation is used for its numerical calculation. To model real scenarios, the authors assume that the incident angle is a random variable within a narrow interval, and repeated observations of the RCS are made for its random realizations. Then, the histogram of the RCS is calculated from the samples. The authors use a nearest neighbor rule to classify conducting plates with different shapes based on their RCS histogram.

This setup is considered as a simple model of traffic road sign classification by millimeter-wavelength radar. The performance and limitations of the algorithm are demonstrated through a set of representative numerical examples.

The proposed method extends the existing tools by using near-field RCS histograms as target features to achieve a classification algorithm.

The purpose of this paper is to investigate the numerical aspects of the electromagnetic scattering of a plane wave by a set of buried cylinders.

The cylindrical wave approach is employed. The analytical model is implemented in a Fortran code. The numerical aspects of the technique are presented, with particular emphasis on the numerical evaluation of the integrals involved in the procedure.

The tool obtained allows a fast computation of the electromagnetic field scattered by an arbitrary disposition of circular cylinders below an interface. Comparisons with the finite element method are proposed, showing the very good agreement between the results obtained with the two different approaches.

The advantages of the proposed technique in terms of computational weight are explained. The method can be useful in a wide class of application, e.g. in the ground penetrating radar applications, microscopy, biomedical applications, etc.

This paper aims to discuss the electromagnetic scattering characteristics of the afterbody model with two drag plates.

The plane shape of the drag plate model is designed as a rectangle. High-precision unstructured grid technology is used to treat the target surface. A calculation method based on multiple tracking and dynamic scattering module is presented to calculate the radar cross section (RCS).

The results show that under the given observation conditions, the RCS and surface scattering characteristics of a single drag plate change with the increase of the opening angle, which makes the forward RCS of the afterbody model change more than 8.43 dBm2. The opening of two resistance plates at different fixed angles has little effect on the peak value and position of the RCS of the afterbody model. The dynamic deflection of the two drag plates can bring 16.78 dBm2 fluctuations to the forward RCS of the afterbody model, and more than 25.59 dBm2 fluctuations to the side RCS.

The installation positions of the drag plate on the aircraft are various, so the method in this paper can provide reference and support for RCS analysis of the speed brake at other positions.

The presented calculation method is of engineering value to analyze the electromagnetic scattering characteristics of the drag plate.

This study aims to learn the dynamic radar cross-section (RCS) of a deflection air brake.

The aircraft model with delta wing, V-shaped tail and blended wing body is designed, and high-precision unstructured grid technology is used to deal with the surface of air brake and fuselage. The calculation method based on multiple tracking and dynamic scattering is presented to calculate RCS.

The fuselage has a low scattering level, and the opening air brake will bring obvious dynamic RCS effects to itself and the whole machine. The average indicator of air brake RCS can be lower than –0.6 dBm² under the tail azimuth, while that of forward and lateral direction is lower. The mean RCS of fuselage is obviously higher than that of air brake, while the deflected air brake and its cabin can still provide strong scattering sources at some azimuths. When the air brake is opening, the change amplitude of the aircraft forward RCS can exceed 19.81 dBm².

This research has practical significance for the dynamic electromagnetic scattering analysis and stealth design of the air brake.

The calculation method for aircraft RCS considering air brake dynamic deflection has been established.

This study focuses on the classification of targets with varying shapes using radar cross section (RCS), which is influenced by the target’s shape. This study aims to develop a robust classification method by considering an incident angle with minor random fluctuations and using a physical optics simulation to generate data sets.

The approach involves several supervised machine learning and classification methods, including traditional algorithms and a deep neural network classifier. It uses histogram-based definitions of the RCS for feature extraction, with an emphasis on resilience against noise in the RCS data. Data enrichment techniques are incorporated, including the use of noise-impacted histogram data sets.

The classification algorithms are extensively evaluated, highlighting their efficacy in feature extraction from RCS histograms. Among the studied algorithms, the K-nearest neighbour is found to be the most accurate of the traditional methods, but it is surpassed in accuracy by a deep learning network classifier. The results demonstrate the robustness of the feature extraction from the RCS histograms, motivated by mm-wave radar applications.

This study presents a novel approach to target classification that extends beyond traditional methods by integrating deep neural networks and focusing on histogram-based methodologies. It also incorporates data enrichment techniques to enhance the analysis, providing a comprehensive perspective for target detection using RCS.

This study aims to study the radar cross-section (RCS) of an intermeshing rotor with blade pitch.

The variation of rotor blade pitch is designed into three modes: fixed mode, linear mode and smooth mode. The dynamic process of two crossed rotors is simulated, where the instantaneous RCS is calculated by physical optics and physical theory of diffraction.

Increasing the pitch angle in the fixed mode can reduce the average RCS of rotor at the given head azimuth. The RCS curve of helicopter in linear mode and smooth mode will have a large peak in the side direction at the given moment. Although the blade pitch in smooth mode is generally larger than that in fixed mode, the smooth mode is conducive to reducing the peak and mean value of helicopter RCS at the given heading azimuth.

The calculation method for analyzing RCS of intermeshing rotor with variable blade pitch is established.