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Data loss is ubiquitous in practical engineering applications due to communication delay or congestion. Data loss rate is a key metric to evaluate the reliability of state estimation. To jointly estimate system state and data loss rate, we propose a class of Gaussian-Beta filters for linear and moderate nonlinear Gaussian state-space models with unknown probability of measurement loss. In the filters, the arrival of the measurement at each time is formulated as a binary random variable, which is determined by the classical threshold technology. In addition, the hidden state and the unknown probability of measurement loss are modeled as a product of Gaussian and Beta distributions, and the form remains unchanged through recursive operations. Simulation results verify the effectiveness of the proposed Gaussian-Beta filters compared with the existing filtering algorithms.

A new high altitude propeller is analyzed and designed in this paper to be used on the stratospheric aircraft propulsion system. Two more appropriate approaches to investigate the aerodynamics characteristics of the high altitude propeller are obtained by comparison of vortex theory with the Spalart-Allmaras (S-A) model and XFOIL program, computational fluid dynamics (CFD), and wind tunnel tests, which are vortex theory with the S-A model and CFD method. In addition, the comparison results show the S-A model is more suitable than the XFOIL program to calculate lift and drag coefficients of S1223 airfoil in case of laminar flow separation and low Reynolds number. What is more, the design procedure of the new high altitude propeller is also described. The above approaches are applied to the new high altitude propeller to get the thrust coefficient, power coefficient, and efficiency. It is indicated that the design propeller can meet the cruising requirement of aircraft at the design point.