English

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 this paper, we propose and investigate a model based on asymptotic methods, designed to compute the radar cross section (RCS) of complex targets. A combined method of physical optics, geometrical optics, and the equivalent current method is applied to establish an effective backscattering analysis procedure. The scattering model includes shadowing effects, multiple bounce, and diffraction by edges. This model is used for RCS estimation and to generate inverse synthetic aperture radar (ISAR) raw data for imaging applications. We review the theoretical aspects and describe the proposed model and experimental setup in detail. Numerical results are provided and compared with the experimental results obtained in the anechoic chamber of ENSTA Bretagne to validate the approach through the computation of the RCS for canonical objects and a generic boat. Finally, a parallelepiped representation of the RCS is presented to be used for ISAR imagery, and the first results concerning the ISAR imaging of a generic boat are provided.

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.

Inverse synthetic aperture radar (ISAR) imaging is typically useful when there is a need to classify, recognize, or identify a moving target of interest. In fact, an ISAR image highlights two-dimensional (2-D) geometric features of a target, which can provide indications of target's type, size, and other salient information. Such information can be then used for target classification, recognition, and identification. In this chapter, we will provide five case studies on applications of ISAR imaging. Such case studies are chosen to diversify the type of application and to give additional indications about how to interpret ISAR images. Specifically, in the first case study (Section 12.1), we show an example of ground-based ISAR images of a noncooperative sailing ship. The ISAR techniques used to form the ISAR images are the range-Doppler (Chapter 3) and the ICBA (Chapter 5) techniques. Different time windows are chosen to show the effects of the coherent processing interval (CPI) length on the ISAR image. Since the radar is ground based, this represents a case where the ISAR image is formed by exploiting only the sea surface induced target's motions. The second case study (Section 12.2) refers to a scenario where the radar is carried by an aircraft and the target is a ship at sea. In this case, both the target and the platform motions concur to the ISAR image formation. Also in this case, the range-Doppler and ICBA are used to form the ISAR image sequence. The third case study (Section 12.3) concerns dual ground-based/satellite ISAR imaging of a noncooperative sailing ship. In this experiment two radars are used to image a sailing ship at the same time. Two techniques are here used to form the ISAR images: a refocus technique (see Chapter 8) to form the satellite ISAR image; and a range-Doppler with ICBA to form the ground-based ISAR image. In this case study, we show how a dual system is able to form ISAR images of the same target with different target's views and projections. This is a simple case of multiple-perspective ISAR images, which may be looked at as a way to improve a target's classification and recognition [1]. The fourth case study (Section 12.4) shows ISAR images of four aircrafts obtained by processing data acquired with a ground-base radar. This case study may be regarded as the classic ISAR imaging example. Four different airplanes have been selected to show how their characteristics are mapped onto ISAR images. Such characteristics can then be used by classifiers for recognition purposes.

An efficient method to compute the radar cross section (RCS) of open cavities is presented. To calculate this RCS, the ray-tracing for a grid of points and directions is made. This method has the advantage that the ray-tracing is computed only once for all the possible RCS values. The results prove the validity and efficiency of the proposed method.

The application of radar absorbing materials on the surface of metal aircraft can effectively reduce the radar cross section (RCS). In this paper, the physical optics (PO) method is used to calculate the RCS of electrically large coated targets. First, we calculate the RCS of the original X29 aircraft and the X29 aircraft coated with a broadband two-layer radar absorbing coating. In addition, the backscattered electric field data of coated and uncoated X29 aircraft are obtained by using the PO method, respectively. Finally, the two-dimensional Inverse Fourier Transform (IFT) of the collected data is taken to form the Inverse Synthetic Aperture Radar (ISAR) image.

This paper aims at the problems of small Radar Cross-Section (RCS) and short coherent accumulation time in radar detection of low altitude small UAVs. An Inverse Synthetic Aperture Radar (ISAR) super-resolution imaging method based on Bayesian Statistical Machine Learning is proposed. The sparse prior characteristics of UAV with respect to the air-background is utilized by introducing a heavy-tailed Laplacian prior probability distribution, and a Bayesian posterior inference model is derived based on the Gaussian distribution assumption of observation system noise. In view of the non-conjugation of prior distribution, a hierarchical Bayesian model is introduced. Finally, the variational Bayesian expectation maximization algorithm is applied, and the posterior probability density function of the target is solved analytically. Meanwhile, the imaging defocus caused by the non-systematic translational error of the target is corrected, cooperatively. Compared with traditional methods, this method can effectively solve the problem of low imaging signal-to-noise ratio caused by the small RCS of UAV target and low imaging resolution caused by the short coherent accumulation time. The experimental results of simulation and radar data prove the effectiveness and superiority of the proposed method.

An extensive 3D radar cross-section (RCS) data set has recently been acquired at the HARC Microwave Imaging Facility. This data set includes diversity in azimuth and elevation through antenna placement as well as frequency diversity. The addition of elevation diversity to standard Inverse Synthetic Aperture Radar (ISAR) imaging allows 3D object reconstruction, as opposed to the 2D defocused projections obtained by conventional ISAR. The method, based on spherical collection and a paracentric approximation for the target space, relates the reconstruction to the acquired data by a 3D Fourier transform. Resulting images are presented for full- and quasi-3D reconstructions, including 2D tomographic slices of the 3D target and a focused projection of the 3D target data onto a single horizontal plane. >

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.

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.

Translational motion compensation for maneuvering targets is a challenging step in inverse synthetic aperture radar (ISAR) imaging. On one hand, nonuniform translational motion and rotational motion of maneuvering targets result in nonlinear bending of the range profile and create high-order slow time phases. On the other hand, radar cross section (RCS) fluctuation of targets may cause a sparse aperture and, therefore, sharply weakens the correlation between the pulses. Under this condition, traditional methods of translational motion compensation are sometimes difficult to get ideal results. Therefore, we propose an effective and novel method to achieve translational motion compensation for maneuvering targets with sparse aperture. In this method, the translational and rotational motions are modeled as cubic polynomial and quadratic polynomial, respectively. Based on this model, we use the echo to construct a 1-D optimization to estimate all translational parameters simultaneously and use the root-mean-square prop-momentum gradient descent (RMSprop-MGD) algorithm to solve the optimization to maintain the accuracy of parameter estimation. Finally, we use those translational parameters to compensate for the translational motion. Since this method converts the multiparameter optimization into a 1-D optimization, we named it dimension compressed optimization (DCO). Experimental results of the measured dataset prove that the proposed method is effective for full-aperture echoes, random sparse echoes, and block sparse echoes. Moreover, this method is robust under a low pulse sampling rate and low signal-to-noise ratio (SNR) environment.

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.

A brief overview of radar cross section (RCS) measurement techniques is presented. Parameters to be measured include: RCS versus target aspect angle; RCS versus frequency; high-resolution range profiles (one-dimensional images); and high-resolution two-dimensional inverse synthetic aperture radar (ISAR) images. In this review, the measurement radar is limited to ground-based radar systems. Targets include: operational full-scale ships and aircraft; full-scale aircraft mounted on pylons; scale model aircraft mounted on pylons; and scale model ships in water. The review includes compact ranges in anechoic chambers.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

The results of an investigation into processing techniques for reducing target-support contamination in inverse synthetic aperture radar (ISAR) and radar cross-section (RCS) measurements are presented. A three-stage processing approach is described, and its feasibility is successfully demonstrated on actual experimental data. The improvement in RCS accuracy after processing was very good. This is illustrated by two-dimensional displays of target cross-section versus angle over 360/spl deg/ and frequency from 0.5 to 2.0 GHz on a 30 dB scale (max = -3.4 dBsm). >

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.