Multi-target ranging using optical reservoir computing approach in the laterally coupled semiconductor lasers with self-feedback

In this work, we utilize three parallel reservoir computers using semiconductor lasers with optical feedback and light injection to model radar probe signals with delays. Three radar probe signals are generated by driving lasers constructed by a three-element lase array with self-feedback. The response lasers are implemented also by a three-element lase array with both delay-time feedback and optical injection, which are utilized as nonlinear nodes to realize the reservoirs. We show that each delayed radar probe signal can well be predicted and to synchronize with its corresponding trained reservoir, even when there exist parameter mismatches between the response laser array and the driving laser array. Based on this, the three synchronous probe signals are utilized for ranging to three targets, respectively, using Hilbert transform. It is demonstrated that the relative errors for ranging can be very small and less than 0.6%. Our findings show that optical reservoir computing provides an effective way for applications of target ranging.

Giant Photoluminescence Enhancement and Carrier Dynamics in MoS2 Bilayers with Anomalous Interlayer Coupling

Fundamental researches and explorations based on transition metal dichalcogenides (TMDCs) mainly focus on their monolayer counterparts, where optical densities are limited owing to the atomic monolayer thickness. Photoluminescence (PL) yield in bilayer TMDCs is much suppressed owing to indirect-bandgap properties. Here, optical properties are explored in artificially twisted bilayers of molybdenum disulfide (MoS2). Anomalous interlayer coupling and resultant giant PL enhancement are firstly observed in MoS2 bilayers, related to the suspension of the top layer material and independent of twisted angle. Moreover, carrier dynamics in MoS2 bilayers with anomalous interlayer coupling are revealed with pump-probe measurements, and the secondary rising behavior in pump-probe signal of B-exciton resonance, originating from valley depolarization of A-exciton, is firstly reported and discussed in this work. These results lay the groundwork for future advancement and applications beyond TMDCs monolayers.

Improving the Authentication with Built-In Camera Protocol Using Built-In Motion Sensors: A Deep Learning Solution

In this paper, we propose an enhanced version of the Authentication with Built-in Camera (ABC) protocol by employing a deep learning solution based on built-in motion sensors. The standard ABC protocol identifies mobile devices based on the photo-response non-uniformity (PRNU) of the camera sensor, while also considering QR-code-based meta-information. During registration, users are required to capture photos using their smartphone camera. The photos are sent to a server that computes the camera fingerprint, storing it as an authentication trait. During authentication, the user is required to take two photos that contain two QR codes presented on a screen. The presented QR code images also contain a unique probe signal, similar to a camera fingerprint, generated by the protocol. During verification, the server computes the fingerprint of the received photos and authenticates the user if (i) the probe signal is present, (ii) the metadata embedded in the QR codes is correct and (iii) the camera fingerprint is identified correctly. However, the protocol is vulnerable to forgery attacks when the attacker can compute the camera fingerprint from external photos, as shown in our preliminary work. Hence, attackers can easily remove their PRNU from the authentication photos without completely altering the probe signal, resulting in attacks that bypass the defense systems of the ABC protocol. In this context, we propose an enhancement to the ABC protocol, using motion sensor data as an additional and passive authentication layer. Smartphones can be identified through their motion sensor data, which, unlike photos, is never posted by users on social media platforms, thus being more secure than using photographs alone. To this end, we transform motion signals into embedding vectors produced by deep neural networks, applying Support Vector Machines for the smartphone identification task. Our change to the ABC protocol results in a multi-modal protocol that lowers the false acceptance rate for the attack proposed in our previous work to a percentage as low as 0.07%. In this paper, we present the attack that makes ABC vulnerable, as well as our multi-modal ABC protocol along with relevant experiments and results.

The influence the horizontal structure of the forest on the passing the L1 range of navigation satellites signals

Experimental data on the passing of signals from navigation satellites of the L1 range through forest plantations with an anisotropic horizontal tree arrangement structure are presented. A feature of the studied environment is an irregular distance between trees in rows and a constant distance between rows. Signals were recorded by an antenna located inside the forest at heights of 0.5 and 10 meters. Based on the results of processing the amplitude-time dependences of the recorded signal by means of fast Fourier transform, qualitative differences were revealed depending on the orientation of the probe signal path in the forest stand.

THE ABILITY TO ASSESS THE DEGREE OF CORROSION DAMAGE BY EDDY CURRENT TESTING

Considers possibility of corrosion damage evaluation using eddy current method implemented with surface probe. Comparative analysis of amplitude-phase and phase suppression methods implementation has been conducted. Finite-element model for calculating probe signal response to defects of different corrosion type was designed. Experimental research has been conducted that allowed to verify the designed model and to confirm results gained with mathematical simulation.

DIAGNOSTICS OF THE STOCHASTIC IONOSPHERIC CHANNEL IN THE DECAMETER BAND OF RADIO WAVES

We propose a method for direct diagnostics of a stochastic ionospheric radio channel. This method can recalculate probe signal characteristics into transmitted signal characteristics. We derive analytical equations of second-order statistical moments for trajectory characteristics of the main and probe signals propagating in a three-dimensional randomly inhomogeneous ionosphere. We take into account boundary conditions at signal transmission and reception points. As a model of random irregularities of permittivity of the ionosphere, we utilize the concept of a changing space-time correlation ellipsoid, which is self-consistent with spatial changes in the average ionosphere. Time fluctuations of random irregularities are taken into account by the hypothesis of frozen transfer. We use analytical relationships to calculate the expected statistical characteristics of decameter signals along oblique probing paths of the ionosphere. An operational numerical algorithmization of the formulas derived is proposed. We report results of numerical experiments to determine the expected phase variances, group delay, and Doppler frequency shift of the main signal on a given single-hop path, based on measurements of these characteristics of a probe signal on a secondary path. We demonstrate the efficiency of the proposed method for diagnosing statistical trajectory characteristics of a decameter signal along single-hop paths under conditions when ground points of transmission and reception of the main and probe signals are outside the vicinity of focusing points of the wave field.

DIAGNOSTICS OF THE STOCHASTIC IONOSPHERIC CHANNEL IN THE DECAMETER BAND OF RADIO WAVES

We propose a method for direct diagnostics of a stochastic ionospheric radio channel. This method can recalculate probe signal characteristics into transmitted signal characteristics. We derive analytical equations of second-order statistical moments for trajectory characteristics of the main and probe signals propagating in a three-dimensional randomly inhomogeneous ionosphere. We take into account boundary conditions at signal transmission and reception points. As a model of random irregularities of permittivity of the ionosphere, we utilize the concept of a changing space-time correlation ellipsoid, which is self-consistent with spatial changes in the average ionosphere. Time fluctuations of random irregularities are taken into account by the hypothesis of frozen transfer. We use analytical relationships to calculate the expected statistical characteristics of decameter signals along oblique probing paths of the ionosphere. An operational numerical algorithmization of the formulas derived is proposed. We report results of numerical experiments to determine the expected phase variances, group delay, and Doppler frequency shift of the main signal on a given single-hop path, based on measurements of these characteristics of a probe signal on a secondary path. We demonstrate the efficiency of the proposed method for diagnosing statistical trajectory characteristics of a decameter signal along single-hop paths under conditions when ground points of transmission and reception of the main and probe signals are outside the vicinity of focusing points of the wave field.