A new global version of M(3000)F2 prediction model based on artificial neural networks

A new version of global empirical model for the ionospheric propagation factor, M(3000)F2 prediction is presented. Artificial neural network (ANN) technique was employed by considering the relevant geophysical input parameters which are known to influence the M(3000)F2 parameter. This new version is an update to the previous neural network based M(3000)F2 global model developed by Oyeyemi et al. (2007), and aims to address the inadequacy of the International Reference Ionosphere (IRI) M(3000)F2 model (the International Radio Consultative Committee (CCIR) M(3000)F2 model). The M(3000)F2 has been found to be relatively inaccurate in representing the diurnal structure of the low latitude region and the equatorial ionosphere. In particular, the existing hmF2 IRI model is unable to reproduce the sharp post-sunset drop in M(3000)F2 values, which correspond to a sharp post-sunset peak in the peak height of the F2 layer, hmF2. Data from 80 ionospheric stations globally, including a good number of stations in the low latitude region were considered for this work. M(3000)F2 hourly values from 1987 to 2008, spanning all periods of low and high solar activity were used for model development and verification process. The ability of the new model to predict the M(3000)F2 parameter especially in the low latitude and equatorial regions, which is known to be problematic for the existing IRI model is demonstrated.     

Rocket berthing to an asteroid: Design problems

The results of research in a process of a probe rocket berthing to an asteroid are presented. Control laws were obtained as solutions of three problems, namely berthing considering transient processes in a rocket engine, fastest berthing with regard to fuel consumption and berthing in a scheduled time considering fuel consumption. A program trajectory obtained at solving of the first problem is suitable for mathematical modeling of berthing with the feedback control law and stabilization of angular motion. The solutions of the problems are reduced to simple formulas for controlling parameters calculation in the corresponding structures of control laws. The results can be applied in designing promising space vehicles intended for berthing to other space objects.     

Spherical accretion of massive black holes: A model for galactic nuclei

The possibility of explaining the continuous emission of active galactic nuclei in the frame of a model of spherical accretion onto a massive black hole is discussed. Cool inhomogeneities (T 10⁴°K) within the accretion flow could be responsible for the broad line emission if half of the accreting matter is in the dense phase. A crucial test of this hypothesis is the expected correlation between the ratio of the luminosity in lines to the total luminosity and the hardness of the continuous spectrum.     

改进PASTd算法在大型自适应阵中的应用

矩阵特征分解算法中紧缩近似投影子空间跟踪(PASTd)算法在自适应阵波束形成中得到了广泛应用.在对其仿真中发现仅在信噪比较低时该算法才能得到较好的结果.针对这一缺陷,正交近似投影子空间跟踪(OPAST)算法被引伸到PASTd中.改进算法可在不知道信号维数的情况下估算信号的特征向量与特征值,并保证特征向量的正交性,因此具有更好的收敛性能,而算法复杂度基本不变.改进算法与多重信号分类(MUSIC)算法相结合应用于大型自适应阵,可对主瓣及其附近区域的干扰进行抑制,并大大降低MUSIC算法的计算量,对其干扰零点的形成有很强实用价值.     

Spectroscopic analysis of the solar flare event on 2002 August 3 with the use of RHESSI and RESIK data

We use simultaneous observations from RESIK and RHESSI instruments to compare plasma properties of a major solar flare in its rise and gradual phase. This event occurred on 2002 August 3 (peak time at 19:06 UT). The flare had a very good coverage with RESIK data and well-resolved soft and hard X-ray sources were seen in RHESSI images. Spectra of X-ray radiation from RHESSI images are studied and compared with RESIK measurements in different flare phases. Result shows large differences in flare morphology and spectra between flare rise and gradual phase.     

The FAST Satellite Fields Instrument

We describe the electric field sensors and electric and magnetic field signal processing on the FAST (Fast Auroral SnapshoT) satellite. The FAST satellite was designed to make high time resolution observations of particles and electromagnetic fields in the auroral zone to study small-scale plasma interactions in the auroral acceleration region. The DC and AC electric fields are measured with three-axis dipole antennas with 56 m, 8 m, and 5 m baselines. A three-axis flux-gate magnetometer measures the DC magnetic field and a three-axis search coil measures the AC magnetic field. A central signal processing system receives all signals from the electric and magnetic field sensors. Spectral coverage is from DC to 4 MHz. There are several types of processed data. Survey data are continuous over the auroral zone and have full-orbit coverage for fluxgate magnetometer data. Burst data include a few minutes of a selected region of the auroral zone at the highest time resolution. A subset of the burst data, high speed burst memory data, are waveform data at 2×10⁶ sample s^–1. Electric field and magnetic field data are primarily waveforms and power spectral density as a function of frequency and time. There are also various types of focused data processing, including cross-spectral analysis, fine-frequency plasma wave tracking, high-frequency polarity measurement, and wave-particle correlations.     

Magnetospheric Science Objectives of the <Emphasis Type="Italic">Juno</Emphasis> Mission

In July 2016, NASA’s Juno mission becomes the first spacecraft to enter polar orbit of Jupiter and venture deep into unexplored polar territories of the magnetosphere. Focusing on these polar regions, we review current understanding of the structure and dynamics of the magnetosphere and summarize the outstanding issues. The Juno mission profile involves (a) a several-week approach from the dawn side of Jupiter’s magnetosphere, with an orbit-insertion maneuver on July 6, 2016; (b) a 107-day capture orbit, also on the dawn flank; and (c) a series of thirty 11-day science orbits with the spacecraft flying over Jupiter’s poles and ducking under the radiation belts. We show how Juno’s view of the magnetosphere evolves over the year of science orbits. The Juno spacecraft carries a range of instruments that take particles and fields measurements, remote sensing observations of auroral emissions at UV, visible, IR and radio wavelengths, and detect microwave emission from Jupiter’s radiation belts. We summarize how these Juno measurements address issues of auroral processes, microphysical plasma physics, ionosphere-magnetosphere and satellite-magnetosphere coupling, sources and sinks of plasma, the radiation belts, and the dynamics of the outer magnetosphere. To reach Jupiter, the Juno spacecraft passed close to the Earth on October 9, 2013, gaining the necessary energy to get to Jupiter. The Earth flyby provided an opportunity to test Juno’s instrumentation as well as take scientific data in the terrestrial magnetosphere, in conjunction with ground-based and Earth-orbiting assets.