This paper presents an investigation of the electromagnetic signature and the coupling mechanism of quadcopter drones with incident electromagnetic (EM) wave and radar cross section (RCS) analysis. Coupling analysis is performed based on the dominant coupling path: when an incident EM wave with a magnitude of 50 kV/m contacts a commercial quadcopter drone, its motor power wires are identified as the dominant coupling path. Higher coupling voltages are obtained for frequencies that have large impedance values at both ends of the load on the motor power wire. This induced voltage can affect the integrated circuit chip on a printed circuit board, as well as parallel plate resonances. Furthermore, the RCS of a quadcopter drone is measured in the frequency range of 0.5–3 GHz. The internal-component vulnerability characteristics of quadcopters can spike at specific frequencies with high RCS values and can be analyzed with or without motor power wires. We verified these hypotheses via 2D inverse synthetic aperture radar images, and we analyzed the results by comparing the empirical and full-wave simulation values.

To measure the electromagnetic properties of steel fiber-reinforced concrete (SFRC) in the X-band, 1-port measurements were performed using a lens horn antenna in a free-space measurement system. Free-space 1-port calibration with translations of the position of the reflector regarding the characteristics of the focused beam lens horn antenna was applied. The intrinsic impedance and complex permittivity of the SFRC were obtained from the measured reflection characteristics. The steel fiber content increased and the electromagnetic properties of the SFRC gradually changed from a dielectric to a conductor, even in very low frequencies compared to the plasma frequencies of general metal, which are optical frequencies. This is considered to be the plasmon effect of the metallic structure formed by the steel fiber. This result is applicable for analyses of the electromagnetic phenomenon of large structures with fiber content.

This communication presents a novel technique for obtaining bistatic radar cross sections (RCSs) extracted from a monostatic scattering field dataset using a discrete scattering center model and basis pursuit denoising (BPDN) algorithm, which is compressive sensing (CS) technique. With the high-frequency assumption, a complex vector of independent point sources is formulated in a monostatic configuration for a geometrical relationship among the transmitter, receiver, and equivalent scatterers. A matrix equation for the scattering problem of an underdetermined form is effectively calculated by an iterative BPDN solver. Then, compensating the phase difference in the bistatic condition can derive the bistatic RCS at specific frequency points and observation angles. The accuracy of the proposed method for extracting bistatic results is verified using two numerical examples, and the performance of the method in terms of measurement efficiency and data resolution in frequency and angle domains is compared with that of conventional method.

한국전자파학회논문지 (The Journal of Korean Institute of Electromagnetic Engineering and Science)

This paper presents a novel technique for radar cross section (RCS) feature extraction using discrete scattering center modeling and a basis pursuit denoising (BPDN) algorithm for compressive sensing (CS). From the Stratton-Chu formula, a high-frequency assumption has been applied to define the target object as a combination of independent point scatterers. Using the BPDN solver, complex-valued scattering sources are determined from a matrix equation for the scattering problem. Using a numerical example, it has been verified that the proposed method can extract the RCS feature accurately, and the measurement efficiency is much higher compared to that of conventional methods.

Near-field to far-field transformation (NFFFT) is a frequently-used method in antenna and radar cross section (RCS) measurements for various applications. For weapon systems, most measurements are captured in the near-field area in an anechoic chamber, considering the security requirements for the design process and high spatial costs of far-field measurements. As the theoretical RCS value is the power ratio of the scattered wave to the incident wave in the far-field region, a scattered wave measured in the near-field region needs to be converted into field values in the far-field region. Therefore, this paper proposes a near-field to far-field transformation algorithm based on spherical wave expansion for application in near-field RCS measurement systems. If the distance and angular coordinates of each measurement point are known, the spherical wave functions in an orthogonal relationship can be calculated. If each weight is assumed to be unknown, a system of linear equations as numerous as the number of samples measured in the near electric field can be generated. In this system of linear equations, each weight value can be calculated using the iterative least squares QR-factorization method. Based on this theory, the validity of the proposed NFFFT is verified for several scatterer types, frequencies and measurement distances.