Adaptive 3D ray tracing approach for indoor radio signal prediction at 3.5 GHz

This paper explained an adaptive ray tracing technique in modelling indoor radio wave propagation. As compared with conventional ray tracing approach, the presented ray tracing approach offers an optimized method to trace the travelling radio signal by introducing flexibility and adaptive features in ray launching algorithm in modelling the radio wave for indoor scenarios. The simulation result was compared with measurements data for verification. By analyzing the results, the proposed adaptive technique showed a better improvement in simulation time, power level and coverage in modelling the radio wave propagation for indoor scenario and may benefit in the development of signal propagation simulators for future technologies.

Акустооптическая многолучевая аксиальная дифракция в парателлурите

To form a multi-beam radiation pattern, it is proposed to use the axial geometry of acousto-optic interaction in paratellurite. In single frequency mode, the use of this geometry for angular scanning is characterized by a dip in the frequency response. Optimization of a multifrequency radio signal makes it possible to effectively divide laser radiation into several beams, while maintaining the fundamental advantages of axial geometry: minimum crystal size and power consumption

On the solar dynamics from radio signal communication by recent solar probes

The very inquisition of the humanity always remains about its parent star of this planetary system. Scientists across the world are always egger to investigate the details of the phenomenon of the solar flares and coronal mass ejections (CMEs). There are some fundamental mysteries related to the solar coronal heating along with the acceleration of the solar wind and energetic particles. In this context we have discussed on the solar radio signal data obtained from the Parker Solar Probe (PSP) mission of National Aeronautics and Space Administration (NASA), USA in course of its journey towards the Sun and the very recent data of Solar and Heliospheric Observatory (SOHO) space probe of European Space Agency (ESA) and NASA. In this work the simultaneous and periodical analysis of the data from the SOHO and PSP will light into the delicate features of the near and far Earth observations on the solar coronal mass ejections related dynamics and that reveals some interesting facts in relation to the solar magnetic field.

Outbreak of Negative Narrow Bipolar Events in Two Mid-Latitude Thunderstorms Featuring Overshooting Tops

Lightning discharges are the electrical production in thunderclouds. They radiate the bulk of radio signals in the very low-frequency and low-frequency (VLF/LF) that can be detected by ground-based receivers. One kind of special intra-cloud lightning discharges known as narrow bipolar events (NBEs) have been shown to be rare but closely linked to the convective activity that leads to hazardous weather. However, there is still lack of understanding on the meteorological conditions for thunderstorm-producing NBEs, especially for those of negative polarity, due to their rare occurrence. In this work, we aim to investigate what meteorological and electrical conditions of thunderclouds favor the production of negative NBEs. Combining with the VLF/LF radio signal measured by Jianghuai Area Sferic Array (JASA), S-band Doppler radar observation and balloon sounding data, two mid-latitude thunderstorms with outbreaks of negative NBEs at midnight in East China were analyzed. The comparison with the vertical radar profile shows that the bursts of negative NBEs occurred near thunderclouds with overshooting tops higher than 18 km. Manifestation of negative NBEs is observed with a relatively low spectrum width near thundercloud tops. Our findings suggest that the detection of negative NBEs would provide a unique electrical means to remotely probe overshooting tops with implications for the exchange of troposphere and stratosphere.

Radio signal time delay estimation performance of TDOA/SSR-based source localization systems

The work is devoted to the development of an algorithm for the optimal Radio Signal Time Delay Estimation Performance in passive location systems of stationary targets based on the TDOA method in two-dimensional space. A realistic model of the radio signal at the input of sensors (base station receivers) is considered, considering the random power value as a function of the distance to the source. The optimal estimate is based on the strategy of maximum posterior probability density. The calculation of the statistical characteristics of the obtained estimate of the radio signal delay time is carried out. The Bayesian Cramér - Rao lower bound (BCRLB) of the latency estimate is calculated. It is shown that the use of a priori statistical information on the path loss of a radio signal model can improve the accuracy of estimating the propagation delay time of a radio signal in TDOA/SSR-Based Source Localization Systems.

New Searches for Continuous Gravitational Waves from Seven Fast Pulsars

We conduct searches for continuous gravitational waves from seven pulsars that have not been targeted in continuous wave searches of Advanced LIGO data before. We target emission at exactly twice the rotation frequency of the pulsars and in a small band around such a frequency. The former search assumes that the gravitational-wave quadrupole is changing in a phase-locked manner with the rotation of the pulsar. The latter search over a range of frequencies allows for differential rotation between the component emitting the radio signal and the component emitting the gravitational waves, for example the crust or magnetosphere versus the core. Timing solutions derived from the Arecibo 327 MHz Drift-Scan Pulsar Survey observations are used. No evidence of a signal is found and upper limits are set on the gravitational-wave amplitude. For one of the pulsars we probe gravitational-wave intrinsic amplitudes just a factor of 3.8 higher than the spin-down limit, assuming a canonical moment of inertia of 1038 kg m2. Our tightest ellipticity constraint is 1.5 × 10−8, which is a value well within the range of what a neutron star crust could support.

Investigation of UWB RF signal technology for solving indoor positioning problem

The article considers the process of developing a local positioning system using an ultra-wideband radio signal system and its integration with a strapdown inertial navigation system (SINS). A system based on Ultra-Wide Band (UWB) technology is used as a radio navigation system. An overview of the developed experimental integrated navigation system model is presented. Algorithms for calculating the position using the propagation time of the radio signal are used to obtain a navigation solution. An analysis of the accuracy of Single-Sided Two-Way Ranging and Double-Sided Two-Way Ranging algorithms using a UWB radio module is presented. The modeling errors of the inertial navigation system were performed. The maximum permissible parameters of the sensitive element errors were obtained for integration with the radio navigation system. The scheme of integration of the navigation solution of the UWB and SINS systems is determined.

No Need of Data Pre-processing

Device-free context awareness is important to many applications. There are two broadly used approaches for device-free context awareness, i.e., video-based and radio-based. Video-based approaches can deliver good performance, but privacy is a serious concern. Radio-based context awareness applications have drawn researchers' attention instead, because it does not violate privacy and radio signal can penetrate obstacles. The existing works design explicit methods for each radio-based application. Furthermore, they use one additional step to extract features before conducting classification and exploit deep learning as a classification tool. Although this feature extraction step helps explore patterns of raw signals, it generates unnecessary noise and information loss. The use of raw CSI signal without initial data processing was, however, considered as no usable patterns. In this article, we are the first to propose an innovative deep learning–based general framework for both signal processing and classification. The key novelty of this article is that the framework can be generalised for all the radio-based context awareness applications with the use of raw CSI. We also eliminate the extra work to extract features from raw radio signals. We conduct extensive evaluations to show the superior performance of our proposed method and its generalisation.