Adaptive Multistate Markov Channel Modeling Method for Reentry Dynamic Plasma Sheaths

Channel modeling of a plasma sheath for hypersonic reentry vehicles is important in addressing reentry communication blackout issues. Given that the time-varying property of the transmission medium is caused by physical factors such as large-scale flight conditions variation, especially angle of attack, and small-scale fluid turbulence, a new adaptive multistate Markov channel modeling method is proposed to present the dynamic effects of reentry plasma sheaths on wireless channels. First, a quasi-Gaussian function mathematical model for the electron density of a dynamic plasma sheath is established according to the variation frequency of the dynamic physical factors. Then, the time-varying attenuation is calculated by combining the quasi-static Monte Carlo and uniform hierarchical analytical methods for nonuniform electronic density distribution. Finally, a hidden Markov model is employed to model the channel characteristics of the dynamic plasma sheath, and a reversible-jump Markov chain Monte Carlo algorithm is used to adaptively estimate the channel parameters of the multistate Markov channel. Simulation results show that the first-order statistical properties of the proposed channel are in good agreement with the calculated variable attenuation of radio waves, and this method has the adaptive capacity to estimate the number of multiple states and the channel parameters in each state without a need for manual setting.

[1]  W. L. Jones,et al.  Electrostatic-probe measurements of plasma parameters for two reentry flight experiments at 25000 feet per second , 1972 .

[2]  B. Jiang,et al.  A matching approach to communicate through the plasma sheath surrounding a hypersonic vehicle , 2015 .

[3]  Bin Wu,et al.  Channel Characterization and Finite-State Markov Channel Modeling for Time-Varying Plasma Sheath Surrounding Hypersonic Vehicles , 2014 .

[4]  L. Xiaoping,et al.  Influence of Plasma Pressure Fluctuation on RF Wave Propagation , 2016 .

[5]  Harald Ernst,et al.  A novel approach to model the land mobile satellite channel through reversible jump markov chain monte carlo technique , 2008, IEEE Transactions on Wireless Communications.

[6]  M. Lontano,et al.  Density-modulation effects on the propagation of an electromagnetic wave in a plasma , 1992, Journal of Plasma Physics.

[7]  Xiaoli Xi,et al.  FDTD Simulation for Wave Propagation in Anisotropic Dispersive Material Based on Bilinear Transform , 2015, IEEE Transactions on Antennas and Propagation.

[8]  L. Duan,et al.  Numerical Study of Pressure Fluctuations due to a Mach 6 Turbulent Boundary Layer , 2013 .

[9]  Yang Min,et al.  A large volume uniform plasma generator for the experiments of electromagnetic wave propagation in plasma , 2013 .

[10]  James P. Rybak,et al.  Progress in Reentry Communications , 1971, IEEE Transactions on Aerospace and Electronic Systems.

[11]  B. Bai,et al.  Effects of Reentry Plasma Sheath on the Polarization Properties of Obliquely Incident EM Waves , 2014, IEEE Transactions on Plasma Science.

[12]  S. Mudaliar,et al.  Scattering of Electromagnetic Waves in the Presence of Wave Turbulence Excited by a Flow With Velocity Shear , 2010, IEEE Transactions on Plasma Science.

[13]  Guolong He,et al.  Adaptive Transmission Method for Alleviating the Radio Blackout Problem , 2015 .

[14]  A. Demetriades.  Electron fluctuations in an equilibrium turbulent plasma , 1964 .

[15]  Ryan P. Starkey,et al.  Hypersonic Vehicle Telemetry Blackout Analysis , 2015 .

[16]  C. Robert,et al.  Bayesian inference in hidden Markov models through the reversible jump Markov chain Monte Carlo method , 2000 .

[17]  Lawrence R. Rabiner,et al.  A tutorial on hidden Markov models and selected applications in speech recognition , 1989, Proc. IEEE.

[18]  Isaiah M. Blankson,et al.  Review of Leading Approaches for Mitigating Hypersonic Vehicle Communications Blackout and a Method of Ceramic Particulate Injection Via Cathode Spot Arcs for Blackout Mitigation , 2010 .

[19]  Jiangfan Liu,et al.  Plasma sheath multipath analysis and its effect on GNSS navigation , 2015 .

[20]  P. Green,et al.  On Bayesian Analysis of Mixtures with an Unknown Number of Components (with discussion) , 1997 .

[21]  D. Buttsworth,et al.  Deduction of temperature fluctuations in transient compression wind tunnels using incompressible turbulent flow data , 2009, 2009 3rd International Conference on Energy and Environment (ICEE).

[22]  Yanming Liu,et al.  Parasitic modulation of electromagnetic signals caused by time-varying plasma , 2015 .

[23]  Bowen Bai,et al.  Navigation antenna performance degradation caused by plasma sheath , 2013 .

[24]  Subrata Roy,et al.  Blackout Analysis of Small Reentry Vehicles , 2015 .

[25]  Donald L. Potter.  Introduction of the PIRATE Program for Parametric Reentry Vehicle Plasma Effects Studies , 2006 .

[26]  E. Krämer,et al.  Fluctuation Measurements in the Turbulent Boundary Layer of a Supersonic Flow , 2010 .

[27]  Hailong Li,et al.  Propagation Matrix Method Study on THz Waves Propagation in a Dusty Plasma Sheath , 2016, IEEE Transactions on Antennas and Propagation.

[28]  M. Schubert,et al.  Reconstruction of the turbulence radial profile from reflectometry phase root mean square measurements , 2012 .

[29]  J. Simpson,et al.  An Efficient 3-D FDTD Model of Electromagnetic Wave Propagation in Magnetized Plasma , 2015, IEEE Transactions on Antennas and Propagation.

[30]  P. Green.  Reversible jump Markov chain Monte Carlo computation and Bayesian model determination , 1995 .

[31]  Bin Wu,et al.  Measuring the Time-Varying Channel Characteristics of the Plasma Sheath From the Reflected Signal , 2014, IEEE Transactions on Plasma Science.

[32]  T. Lin,et al.  Influence of reentry turbulent plasma fluctuation on EM wave propagation , 2002 .

[33]  Anthony Demetriades,et al.  Mean and Fluctuating Electron Density in Equilibrium Turbulent Boundary Layers , 1971 .

[34]  S. Kobayashi,et al.  Observation of Edge Plasma Fluctuations with a Fast Camera in Heliotron J , 2013 .

[35]  B. Bai,et al.  Effects of Pressure Variation on Polarization Properties of Obliquely Incident RF Waves in Re-Entry Plasma Sheath , 2015, IEEE Transactions on Plasma Science.