The three-dimensional ionospheric electron density imaging in Japan using the approximate kalman filter algorithm

2021 ◽  
pp. 105628
Author(s):  
Rui Song ◽  
Katsumi Hattori ◽  
Xuemin Zhang ◽  
Chie Yoshino
Keyword(s):  
Kalman Filter ◽  
Electron Density ◽  
Three Dimensional ◽  
Ionospheric Electron Density ◽  
Kalman Filter Algorithm

scholarly journals Numerical simulation of oblique ionospheric heating by powerful radio waves

2018 ◽  
Vol 36 (3) ◽  
pp. 855-866
Author(s):  
Moran Liu ◽  
Chen Zhou ◽  
Xiang Wang ◽  
Bin Bin Ni ◽  
Zhengyu Zhao
Keyword(s):  
Ray Tracing ◽  
Electron Density ◽  
Oblique Incidence ◽  
Three Dimensional ◽  
Radio Waves ◽  
Powerful Radio ◽  
Ionospheric Electron Density ◽  
Ionospheric Heating ◽  
Tracing Algorithm ◽  
Electron Density And Temperature

<p><strong>Abstract.</strong> In this paper, we investigate the ionospheric heating by oblique incidence of powerful high-frequency (HF) radio waves using three-dimensional numerical simulations. The ionospheric electron density and temperature perturbations are examined by incorporating the ionospheric electron transport equations and ray-tracing algorithm. The energy distribution of oblique incidence heating waves in the ionosphere is calculated by the three-dimensional ray-tracing algorithm. The calculation takes into consideration the electric field of heating waves in the caustic region by the plane wave spectral integral method. The simulation results show that the ionospheric electron density and temperature can be disturbed by oblique incidence of powerful radio waves, especially in the caustic region of heating waves. The oblique ionospheric heating with wave incidence parallel and perpendicular to the geomagnetic field in the mid-latitude ionosphere is explored by simulations, results of which indicate that the ionospheric modulation is more effective when the heating wave propagates along the magnetic field line. Ionospheric density and temperature striations in the caustic region due to thermal self-focusing instability are demonstrated, as well as the time evolution of the corresponding fluctuation spectra.</p>

scholarly journals Instrumental Variable Based Kalman Filter Algorithm for Three-Dimensional AOA Target Tracking

2018 ◽  
Vol 25 (10) ◽  
pp. 1605-1609 ◽  
Author(s):  
Ngoc Hung Nguyen ◽  
Kutluyil Dogancay
Keyword(s):  
Kalman Filter ◽  
Target Tracking ◽  
Instrumental Variable ◽  
Three Dimensional ◽  
Kalman Filter Algorithm

scholarly journals Three-dimensional ionospheric electron density structure of the Weddell Sea Anomaly

2009 ◽  
Vol 114 (A2) ◽  
pp. n/a-n/a ◽  
Author(s):  
C. H. Lin ◽  
J. Y. Liu ◽  
C. Z. Cheng ◽  
C. H. Chen ◽  
C. H. Liu ◽  
...  
Keyword(s):  
Electron Density ◽  
Three Dimensional ◽  
Weddell Sea ◽  
Density Structure ◽  
Ionospheric Electron Density ◽  
Weddell Sea Anomaly

Pushing the Envelope

2018 ◽  
Author(s):  
Eaton E. Lattman ◽  
Thomas D. Grant ◽  
Edward H. Snell
Keyword(s):  
High Resolution ◽  
Electron Density ◽  
Structural Information ◽  
Hydration Shell ◽  
Three Dimensional ◽  
Scattering Data ◽  
Saxs Data ◽  
Electron Density Function ◽  
Angle Scattering ◽  
Iterative Structure

Direct electron density determination from SAXS data opens up new opportunities. The ability to model density at high resolution and the implicit direct estimation of solvent terms such as the hydration shell may enable high-resolution wide angle scattering data to be used to calculate density when combined with additional structural information. Other diffraction methods that do not measure three-dimensional intensities, such as fiber diffraction, may also be able to take advantage of iterative structure factor retrieval. While the ability to reconstruct electron density ab initio is a major breakthrough in the field of solution scattering, the potential of the technique has yet to be fully uncovered. Additional structural information from techniques such as crystallography, NMR, and electron microscopy and density modification procedures can now be integrated to perform advanced modeling of the electron density function at high resolution, pushing the boundaries of solution scattering further than ever before.

scholarly journals Acceleration Feature Extraction of Human Body Based on Wearable Devices

Energies ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 924
Author(s):  
Zhenzhen Huang ◽  
Qiang Niu ◽  
Ilsun You ◽  
Giovanni Pau
Keyword(s):  
Genetic Algorithm ◽  
Feature Extraction ◽  
Kalman Filter ◽  
Human Body ◽  
Wearable Devices ◽  
Human Motion ◽  
Data Set ◽  
Feature Extraction Method ◽  
Motion Data ◽  
Kalman Filter Algorithm

Wearable devices used for human body monitoring has broad applications in smart home, sports, security and other fields. Wearable devices provide an extremely convenient way to collect a large amount of human motion data. In this paper, the human body acceleration feature extraction method based on wearable devices is studied. Firstly, Butterworth filter is used to filter the data. Then, in order to ensure the extracted feature value more accurately, it is necessary to remove the abnormal data in the source. This paper combines Kalman filter algorithm with a genetic algorithm and use the genetic algorithm to code the parameters of the Kalman filter algorithm. We use Standard Deviation (SD), Interval of Peaks (IoP) and Difference between Adjacent Peaks and Troughs (DAPT) to analyze seven kinds of acceleration. At last, SisFall data set, which is a globally available data set for study and experiments, is used for experiments to verify the effectiveness of our method. Based on simulation results, we can conclude that our method can distinguish different activity clearly.

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