Igor Kravets

Indoor positioning systems have become increasingly popular due to the growing demand for location-based services in various domains. While effective outdoors, traditional Global Positioning System (GPS) technologies are often unsuitable for indoor environments due to their reliance on satellite signals, which are severely attenuated or obstructed...

The Internet of Things (IoT) relies on accurate distance estimation between devices, crucial for localization in various applications. While RSSI-based ranging lacks precision and ToF narrow band systems perform poorly, phase-based ranging emerges as the preferred choice for Bluetooth Low Energy (BLE). Infineon's BLE prototype and its performance w...

The time-difference-of-arrival method is popular for indoor tracking systems due to its simple usage, efficiency, performance, and power economy. To solve the non-linear optimization problem of tag coordinates calculation from number of measurements on synchronized anchors, often a low complexity linear least square technique or one of its more adv...

This work introduces Multi-Agent Reinforcement Learning (MARL), a decentralized algorithm for BLE mesh network configurations based on the Partially Observed Markov Decision Process. MARL efficiently manages large device networks and outperforms traditional centralized algorithms for large enough BLE mesh networks. E.g., for an average packet gener...

This chapter presents an overview of the technology behind capacitive sensing in mobile devices and beyond. Capacitive-sensing systems handle signals from the pF range down to aF. Examples to illustrate this include “single-pixel” buttons, sliders, touch screens, and “kilo-pixel” fingerprint readers.

The covariance and spectral characteristics of periodically correlated random processes (PCRP) are used to describe the state of rotary mechanical systems and in their fault detection. The methods for estimation of mean function, covariance function, instantaneous spectral density and their Fourier coefficients for a given class of non-stationary r...

The results of using methods of theory and statistics of periodically correlated random processes (PCRP) for probability structure of annual and daily variations of geophysical phenomena investigation are presented. Properties of estimators for mean function, covariance function, spectral density and their Fourier coefficients, calculated for serie...

Systems and methods and techniques are disclosed for determining the position and size of an object touching a touch-sensitive display. One embodiment may comprise a set of reference templates—where each reference template is a model and/or data associated with a reference object of a given size. The reference templates may be determined on a prior...

The results obtained by authors in the area of theory and methods of statistical analysis of periodically correlated random processes and their generalizations are presented in this article. The main methods for estimation of their correlation and spectral characteristics: coherent, component, least square method and linear filtration method are an...

The component method is applied to define estimators of the periods for Gaussian periodically correlated random processes (mathematical model of stochastic oscillations). The properties of these period estimators are obtained using some small parameter method and the rate of convergence is shown to be optimal. Specific results for the simplest mode...

The coherent estimators of probabilistic characteristics of periodically correlated random processes with unknown period have been investigated. It is shown that these estimators are asymptotically unbiased and consistent. In a first approximation formulas were obtained for the bias and dispersion of estimators defining the impact of the preliminar...

Coherent and component methods for mean and covariance function estimation are analyzed using linear filtration theory. The relationships between variances and biases of the estimates and transfer function of analogue linear filter are determined. On the basis of derived equations the comparison of both techniques are done. The method for obtaining...

Paper presents theoretical results of modeling periodically correlated random processes. We compare the known parametric models: periodic autoregression model of moving average, parametric model of coherent representation and parametric model of harmonic representation. Dependences of properties of correlation and spectral functions related to diff...

The coherent estimators of probabilistic characteristics for periodically correlated random processes in the case of unknown period are analyzed. Shown that these estimators are asymptotically unbiased and consistence.

Coherent and component methods for mean and covariance function estimation are analyzed using linear filtration theory.

The estimates of probability characteristics for periodically correlated signals that are based on harmonic series representation are analyzed. Two methods for stationary components estimations are discussed: Hilbert transform-based method and a frequency shift method. Application of frequency shift method to real and simulated data is shown.

We present the main ideas of methods for early diagnostics of mechanical rotation systems based on the theory and statistics of periodically nonstationary random processes regarded as a mathematical model of signals of vibrations. New diagnostic criteria for defects are proposed, and new possibilities that they open are shown. The application of th...

The properties of stationary components of periodically correlated random processes separated by using zonal filtering have been considered. The properties of estimates of their correlation and spectral characteristics were investigated. The latter were built by using the Blackman-Tukey method.

We construct a statistical model of vibration response of a thin body containing a crack and study the dynamics of changes in the cross-correlation links between the stationary components of the vibration signal. It is shown that the crack size affects neither the shape of correlation functions nor the width of their central maximum.

The properties of least-squares estimates of mathematical expectations and correlation function of periodically correlated random processes (mathematical model of stochastic oscillations) have been investigated. The formulas defining the statistical characteristics of estimates were analyzed. In addition, examples were presented for illustrating th...

In this paper the new approach for modeling of non-linear systems oscillations is given. The theory of periodically correlated random processes (PCRP) for estimation of probabilistic characteristics of such oscillations is proposed.

We propose a model of vibrations of complex rotary systems based on the separation of the process of vibrations into three components: deterministic, stationary, and periodically nonstationary. To separate the deterministic component of signals, we use the methods of statistics of periodically nonstationary random processes, i.e., the coherent and...

A new approach for the fault detection of the turbo-set friction bearings, based on the investigation the periodically non-stationary properties of vibration signals, is analyzed.

Method for separation of the periodically correlated random process into harmonic series representation is presented. The correlation and the spectral properties of the stationary harmonics are investigated. The expressions for precision of separated harmonics are worked out. Simulation results for the amplitude-phase modulated non-stationary signa...

Theoretical and experimental modeling results of periodically correlated random processes (PCRP) are presented. Representation through stationary random processes is used for construction of PCRP model. Dependence of PCRP modeling accuracy on parameters of correlation functions of stationary components is investigated. The offered algorithm of PCRP...

Theoretical and experimental results of time series modeling are summarized. Special attention is given to periodically correlated random processes (PCRP). It is suggested to use the parametric modeling methods on the basis of PCRP decomposition on stationary processes for construction of the process model. Proposed parametrical model is helpful fo...