All issues

The increased potential for jamming satellite navigation signals, which provide the highest positioning accuracy for moving objects, makes the development of alternative navigation systems comparable in accuracy but autonomous extremely important. One of the most effective such approaches is the integration of inertial and optical navigation systems (NS), as they are more resistant to artificial interference. Among NS data, one can distinguish systems that use a velocity field calculation method when processing optical flow, allowing the determination of the linear and angular velocity vectors of an object in the absence of terrain maps and reference points. However, a serious drawback of this method is the high computational cost of determining the velocity field (optical flow parameters), which is difficult to implement onboard an object. In this regard, the article considers an approach that allows for constructing a tightly coupled autonomous inertial-optical navigation scheme for objects moving along known (programmed) trajectories. This scheme utilizes a navigation algorithm that is easily implemented in onboard computers due to the discovered possibility of estimating the navigation vector without preliminary calculation of optical flow parameters, as well as by utilizing functional dependencies of navigation variables arising on analytical (orthodromic) trajectories. To illustrate the generality of the solution, cases of a rigidly mounted video camera on the object and its two-degree stabilization are studied. The navigation algorithm, providing a stochastic estimate of the full vector of linear and angular motion parameters based on measurements of an integrated tightly coupled inertial-optical NS, is built on the basis of an extended Kalman filter for correlated noise of the object and the observer. A numerical experiment illustrating the effectiveness of the proposed approach is conducted.

This article is dedicated to use of S-spline theory for solving equations in partial derivatives. For example, we consider solution of the Poisson equation. S-spline — is a piecewise-polynomial function. Its coefficients are defined by two states. The first part of coefficients are defined by smoothness of the spline. The second coefficients are determined by least-squares method. According to order of considered polynomial and number of conditions of first and second type we get S-splines with different properties. At this moment we have investigated order 3 S-splines of class C¹ and order 5 S-splines of class C² (they meet conditions of smoothness of order 1 and 2 respectively). We will consider how the order 3 S-splines of class C¹ can be applied for solving equation of Poisson on circle and other areas.

The semiclassical approximation method is applied for solution construction of the Fokker–Planck equation with quadratic nonlocal nonlinearity and various coefficients in models of asset returns estimation. Analitical expressions determining nonlinear evolution operator are obtained in semiclasical approximation.

The approach given in this work helps to organize the operative control over action intensity of pollution emissions in atmosphere. The approach allows to sequential estimate of unknown intensity of atmospheric pollution source on the base of concentration measurements of impurity in several stationary control points is offered in the work. The inverse problem was solved by means of the step-by-step regularization and the sequential function specification method. The solution is presented in the form of the digital filter in terms of Hamming. The fitting algorithm of regularization parameter r for function specification method is described.

We obtain asymptotic equalities for upper bounds of the deviations of the right-angled de la Vallee Poussin sums taken over classes of periodical functions of two variables of high smoothness. These equalities guarantee the solvability of the Kolmogorov–Nikol’skii problem for the right-angled de la Vallee Poussin sums on the specified classes of functions.

This paper covers deployable systems assembled from a set of trapezium plates. The middles lines of the plates represent a plane curve in the original position of the package. It is proved that when the package of thin plates is unwrapped, a surface approximating a shell of nearly any curvature is formed. Kinematics of the continual model is analyzed by the method of Cartan moving hedron, extending the results the authors published earlier. Various applications of rotating shells are shown. Experimental models of deployable latticed systems are demonstrated.

The solution of problems of heat conductivity by means of a method of continuous asynchronous cellular automats is considered in the article. Coordination of distribution of temperature in a sample at a given time between cellular automat model and the exact analytical solution of the equation of heattransfer is shown that speaks about expedient use of this method of modelling. Dependence between time of one cellular automatic interaction and dimension of a cellular automatic field is received.

Тhe new test-signals forming method for correlation identification of a nonlinear system based on Lee–Shetzen cross-correlation approach is developed and tested. Numerical Gauss–Newton algorithm is applied to correct autocorrelation functions of test signals. The achieved test-signals have length less than 40 000 points and allow to measure the 2nd order Wiener kernels with a linear resolution up to 32 points, the 3rd order Wiener kernels with a linear resolution up to 12 points and the 4th order Wiener kernels with a linear resolution up to 8 points.

Modification of the lattice Boltzmann method for computation of viscous Newtonian fluid flows is considered. Modified method is based on the splitting of differential operator in Navier–Stokes equation and on the idea of instantaneous Maxwellisation of distribution function. The problems for the system of lattice kinetic equations and for the system of linear diffusion equations are solved while one time step is realized. The efficiency of the method proposed in comparison with the ordinary lattice Boltzmann method is demonstrated on the solution of the problem of planar flow in cavern in wide range of Reynolds number and various grid resolution.

A new method is described for finding parameters of univariate regression model: the greatest cosine method. Implementation of the method involves division of regression model parameters into two groups. The first group of parameters responsible for the angle between the experimental data vector and the regression model vector are defined by the maximum of the cosine of the angle between these vectors. The second group includes the scale factor. It is determined by means of “straightening” the relationship between the experimental data vector and the regression model vector. The interrelation of the greatest cosine method with the method of least squares is examined. Efficiency of the method is illustrated by examples.