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Sergey Geyman

Publications and source records attributed to Sergey Geyman.

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Giant Rotational Meta-Doppler from Genetically Designed Superscatterers

The motion of a rigid body interacting with a wave leaves spectral signatures, with the Doppler shift as the dominant contribution. Since any motion can be decomposed into translational and rotational components, rotational Doppler provides additional information about the object's dynamics. In the electromagnetic domain, rotating objects generally produce rotational Doppler, or micro-Doppler, signals determined by the symmetry and spatial structure of the scattering process. For objects that are subwavelength or comparable in size to the wavelength, the response is typically dominated by the lowest dipolar scattering channel, so the leading spectral component commonly appears at twice the angular frequency. Here, we introduce the concept of artificially engineered rotational micro-Doppler by designing a compact, strongly scattering structure that operates through a high-order multipolar cascade of resonances, thereby producing a giant enhancement. Magneto-electric arrays composed of strongly coupled electric and magnetic resonators are optimized in the GHz range using a covariance matrix adaptation genetic algorithm to maximize the micro-Doppler frequency. Unlike conventional higher-order multipole designs used in superscatterers for a specific angle of incidence and polarization, our approach jointly optimizes excitation and scattering under radar-relevant conditions for a rotating blade. The resulting arrays exhibit a giant rotational meta-micro-Doppler response, exceeding the dipolar limit by two orders of magnitude and mapping rotations of tens of hertz into the kilohertz range. Beyond its fundamental significance, this mapping has practical value because it shifts rotor micro-Doppler signatures well above slow-moving radar clutter, thereby improving the detectability of slow motion.

physics.app-ph

Optically Transparent Meta-Grating Embedded in Rear Windshields for Automotive Radar Detection

Radar plays a crucial role in automotive safety by enabling reliable object detection, thereby assisting drivers and, prospectively, serving as one of the primary sensors in autonomous driving. The radar visibility of a road participant depends on its radar cross-section (RCS). While RCS is an inherent property, enhancing it, similar to using reflective vests for optical visibility, can significantly improve radar detection through cooperative target design. However, modern vehicles are not designed for this purpose, and embedded reflectors are not utilized due to the industry's conservative approach and the limited space available on the vehicle's exterior. Rear windshields offer a vast unused area, but they must still serve their primary function and remain transparent. We propose utilizing this area by embedding a reflecting surface that accounts for the interrogation scenario geometry and the angular tilt of the rear windshield, ensuring the wave is retroreflected back to the radar. The surface is realized as an array of thin conductive wires with a periodicity that provides in-phase excitation for the design incidence angle. Given that automotive radars operate in the millimeter-wave regime (77-81 GHz), large-scale surfaces with sub-millimeter manufacturing accuracy are required. This is achieved by imprinting conductive inks, composed of silver nanoparticles and binders, into grooves in the glass. The fabricated 10x10 sq. sm. sample, with around 90% optical transparency, demonstrates an RCS of 8 sq. m., surpassing the typical RCS of a car. Extrapolating this performance to the entire rear window with an embedded meta grating, a typical RCS of 1000 sq. m. can be achieved, thereby enhancing the detectability range by nearly an order of magnitude. Smart windows enable advanced applications in wireless communication, such as automotive scenarios, IoT, and many others.

physics.app-ph

Drone Carry-on Weight and Wind Flow Assessment via Micro-Doppler Analysis

Remote monitoring of drones has become a global objective due to emerging applications in national security and managing aerial delivery traffic. Despite their relatively small size, drones can carry significant payloads, which require monitoring, especially in cases of unauthorized transportation of dangerous goods. A drone's flight dynamics heavily depend on outdoor wind conditions and the carry-on weight, which affect the tilt angle of a drone's body and the rotation velocity of the blades. A surveillance radar can capture both effects, provided a sufficient signal-to-noise ratio for the received echoes and an adjusted postprocessing detection algorithm. Here, we conduct a systematic study to demonstrate that micro-Doppler analysis enables the disentanglement of the impacts of wind and weight on a hovering drone. The physics behind the effect is related to the flight controller, as the way the drone counteracts weight and wind differs. When the payload is balanced, it imposes an additional load symmetrically on all four rotors, causing them to rotate faster, thereby generating a blade-related micro-Doppler shift at a higher frequency. However, the impact of the wind is different. The wind attempts to displace the drone, and to counteract this, the drone tilts to the side. As a result, the forward and rear rotors rotate at different velocities to maintain the tilt angle of the drone body relative to the airflow direction. This causes the splitting in the micro-Doppler spectra. By performing a set of experiments in a controlled environment, specifically, an anechoic chamber for electromagnetic isolation and a wind tunnel for imposing deterministic wind conditions, we demonstrate that both wind and payload details can be extracted using a simple deterministic algorithm based on branching in the micro-Doppler spectra.

physics.app-ph

Long-Range Over-a-Meter NFC Antenna Design and Impedance Matching

NFC and RFID technologies have seen significant advancements, with expanding applications necessitating the design of novel antenna structures that enhance range capabilities. This paper presents a study on the design and impedance matching of long-range NFC coils, focusing on optimizing antenna performance over distances exceeding one meter. Through numerical analyses of various coil geometries, including single-turn and multi-wire configurations, we explore the effects of coil size, wire separation, and current distribution on magnetic field generation. Additionally, an adaptive impedance matching approach is proposed to maintain efficient power transfer, significantly improving field strength and system performance. The proposed designs demonstrate superior interrogation distances compared to existing configurations, highlighting the potential for enhanced long-range NFC applications.

physics.app-ph