TELEMETRY CHANNEL DATA ESTIMATION EXPOSED TO CHAOTIC IMPULSE-PULSE DISTURBANCES - Volovyk, А. Yu.; Kychak, V. M.; Savytskyi, A. Yu.; Makohon, V. I. (Systems and Technologies, 2025)
The paper is devoted to the problem of devices synthesis for estimating the linear stationary dynamic systems state operating under conditions of noise and perturbations in the observation channel. The paper considers the joint influence of Gaussian noise and chaotic pulse disturbance on the accuracy of message filtering in a digital telemetry channel. The problem of many telemetry systems is the disparity between high data rate and reliability of their reception under the influence of impulse noise, which is typical for various medium information transmission. Since, due to the rapid development of technology, telemetry has become crucial to ensure the proper level of reliability and guarantee a given degree of safety of complex technological facilities and systems, such discrepancy is becoming more and more critical.The aim of the study is to improve the accuracy of message estimation in a telemetry channel exposed to chaotic-pulse disturbances against the background of a moderate increase in computational cost.In general, the efficiency of using methods for synthesizing optimal estimation devices depends on the completeness of a priori information about the processes mathematical model occurring in the control object, statistical information about the existing disturbances properties and the initial data formation mechanism. For problems of this class, the standard solution is the optimal Kalman filter demonstrating the highest quality of convergence of estimates to true values. If data on the current state of the observation system is missing, unreliable, or does not correspond to the accepted models, then the synthesis problem becomes incorrectly formulated. To resolve this contradiction, the presented work proposes a correction of the telemetry observation channel mathematical model, taking into account the appearance of differently accurate initial data, including anomalous ones.Based on the adjusted model, a pseudo-Bayesian algorithm for multi-hypothesis estimation is synthesized. It includes a mechanism for calculating the posterior probability of chaotic impulse noise and proportional weighting of the initial estimates based on it. Based on the results of digital statistical modeling, a comparative analysis of the accuracy of the considered evaluation algorithms was carried out. The residual of the signal generated as a difference between the telemetry reference signal and the estimate of the affected chaotic pulse interference obtained with the help of appropriate filters was chosen as a source of information for the relative accuracy estimation. The source of information for assessing the relative accuracy was the signal residual.It was generated as the difference between the reference telemetry signal and the estimate of the affected chaotic impulse disturbances obtained using the appropriate filters. Numerical simulation results confirm the effectiveness of the proposed approach.