Application of small-size antennas for estimation of angles of arrival of HF signals scattered by ionospheric irregularities

A modification of the Doppler Interferometry Technique is suggested to enable estimating angles of arrival of comparatively broadband HF signals scattered by random irregularities of the ionospheric plasma with the use of small-size weakly directional antennas. The technique is based on the measurements of cross-spectra phases of the probe radiation recorded at least in three spatially separated points. The developed algorithm has been used to investigate the angular and frequency-time characteristics of HF signals propagating at frequencies above the maximum usable one (MUF) for the direct radio path Moscow-Kharkiv. The received signal spectra show presence of three families of spatial components attributed, respectively, to scattering by plasma irregularities near the middle point of the radio path, ground backscatter signals and scattering of the sounding signals by the intense plasma turbulence associated with auroral activations. It has been shown that the regions responsible for the formation of the third family components are located well inside the auroral oval. The drift velocity and direction of the auroral ionosphere plasma have been determined. The obtained estimates are consistent with the classical conception of the ionospheric plasma convection at high latitudes and do not contradict the results of investigations of the auroral ionosphere dynamics using the SuperDARN network.     

Potential of IRNSS/NavIC L5 signals for ionospheric studies

Indian Space Research Organization (ISRO) has developed an indigenous system named Indian Regional Navigation Satellite System (IRNSS) or NavIC (Navigation with Indian Constellation), that consists of 7 satellites and transmits navigation signal in L and S bands. ISRO, for validation of the system, has installed many IGS (IRNSS/GPS/SBAS) receivers scattered over the Indian region. Using preliminary data from two geographically widely separated stations over India, this paper presents the results on studies on parameters of IRNSS signal quality and discusses how these parameters may be used to study the ionospheric behavior over the Indian region. The results show the importance and advantages of using IRNSS data for such studies.     

Erratum to: Use of the DBM Model to the Predict of Arrival of Coronal Mass Ejections to the Earth

Cosmic Research - An Erratum to this paper has been published: https://doi.org/10.1134/S0010952521120017     

Method of energy efficiency assessment for power supply of autonomous drive systems for perspective mobile objects

Based on an integrated approach, we solve the optimization problem for energy content and weight-dimensional characteristics of the electric servo drive by synthesis of structure and analysis of characteristics for different power supplies. The generalized power supply model, developed for different power supply of drive control systems, is given.     

On the stability of stationary motions of a system of coaxial bodies

We consider the stability of stationary motions of a model of a spacecraft as a system of coaxial bodies with small asymmetry caused by the shift of the axes of dynamic symmetry of bodies relative to the axis of rotation. We determine the stationary motions of the system; their stability is studied with respect to both the projections of angular velocity and the position of the axis of rotation. The sufficient conditions for the stability of these stationary motions are obtained by constructing a Lyapunov function, and the necessary conditions are obtained by analyzing the corresponding linearized equations of perturbed motion.     

Study of thin-walled parts shaping process based on flanging and embossing

This paper presents the results of analyzing the shaping of thin-walled conical parts with the uniform thickness along generatrix.     

An Artificial Neural Network based approach for estimation of rain intensity from spectral moments of a Doppler Weather Radar

By using a Doppler Weather Radar (DWR) at Shriharikota (13.66°N & 80.23°E), an Artificial Neural Network (ANN) based technique is proposed to improve the accuracy of rain intensity estimation. Three spectral moments of a Doppler spectra are utilized as an input data to an ANN. Rain intensity, as measured by the tipping bucket rain gauges around the DWR station, are considered as a target values for the given inputs. Rain intensity as estimated by the developed ANN model is validated by the rain gauges measurements. With the help of a developed technique, reasonable improvement in the estimation of rain intensity is observed. By using the developed technique, root mean square error and bias are reduced in the range of 34–18% and 17–3% respectively, compared to Z–R approach.