SIGNAL PROCESSING AND CYBERSECURITY IN SOME CHAOTIC OPTICAL COMMUNICTAION SYSTEMS

A chaos –geometric approach to investigation of complex chaotic dynamical systems is applied to an analysis, modeling and processing the time series of emission intensities of chaotic transmitter/receiver systems (two unidirectionally coupled semiconductor laser systems in the all-optical scheme) suited for encoding at rates of GBit/s. the problem of a signal processing is directly connected with the corresponding cybersecurity in some optical chaos communictaion systems. The estimated values for the dynamic and topologic invariants such as the correlation and Kaplan-York dimensions, Lyapunov indicators, Kolmogorov entropy etc for investigated chaotic signal time series of two unidirectionally coupled semiconductor laser systems in the all-optical scheme.

Radio signal time delay estimation performance of TDOA/SSR-based source localization systems

The work is devoted to the development of an algorithm for the optimal Radio Signal Time Delay Estimation Performance in passive location systems of stationary targets based on the TDOA method in two-dimensional space. A realistic model of the radio signal at the input of sensors (base station receivers) is considered, considering the random power value as a function of the distance to the source. The optimal estimate is based on the strategy of maximum posterior probability density. The calculation of the statistical characteristics of the obtained estimate of the radio signal delay time is carried out. The Bayesian Cramér - Rao lower bound (BCRLB) of the latency estimate is calculated. It is shown that the use of a priori statistical information on the path loss of a radio signal model can improve the accuracy of estimating the propagation delay time of a radio signal in TDOA/SSR-Based Source Localization Systems.

Methodology for Designing Hardware for Measuring Parameters of a Digital Signal

In the production of various devices, various problems can arise, leading to the appearance of defects, both explicit and latent. This may be due to both poor quality materials and imperfect technology. To identify defects, devices are tested. If the device uses a digital signal transmission at high frequencies, it is usually considered sufficient to check the functioning of the individual components using technological programs. But at high transmission frequencies, or due to defects, the digital signal is distorted, and in devices where there is no error control, violations of the signal integrity during transmission can lead to failures and failures. Moreover, under normal conditions, the signal can meet the requirements, and in difficult conditions, go beyond the permissible limits. If an individual instance of a device can be susceptible to such failures, this can be identified in more detail by examining the signals flowing through its circuits. The most obvious way requires an oscilloscope, on the screen of which a person looks at the parameters of such a signal, time and amplitude characteristics. This is a very slow operation, so optimization might be the next step. For example, the use of flying probes, or probes with commutation, recording and automatic comparison of oscillograms with the exemplary one. In any case, these tests require equipment operating at frequencies much higher than the circuit itself, which means that at high baud rates, such equipment starts to be expensive.

Correlating Time Series Signals and Event Logs in Embedded Systems

In many embedded systems, we face the problem of correlating signals characterising device operation (e.g., performance parameters, anomalies) with events describing internal device activities. This leads to the investigation of two types of data: time series, representing signal periodic samples in a background of noise, and sporadic event logs. The correlation process must take into account clock inconsistencies between the data acquisition and monitored devices, which provide time series signals and event logs, respectively. The idea of the presented solution is to classify event logs based on the introduced similarity metric and deriving their distribution in time. The identified event log sequences are matched with time intervals corresponding to specified sample patterns (objects) in the registered signal time series. The matching (correlation) process involves iterative time offset adjustment. The paper presents original algorithms to investigate correlation problems using the object-oriented data models corresponding to two monitoring sources. The effectiveness of this approach has been verified in power consumption analysis using real data collected from the developed Holter device. It is quite universal and can be easily adapted to other device optimisation problems.

Application of Ultra Narrow Band Modulation in Enhanced Loran System

The Enhanced Loran (eLoran) system is valued for its important role in the positioning, navigation, and timing fields; however, with its current modulation methods, low data rate restricts its development. Ultra narrow band (UNB) modulation is a modulation method with extremely high spectrum utilization. If UNB modulation can be applied to the eLoran system, it will be very helpful. The extended binary phase shift keying modulation in UNB modulation is selected for a detailed study, parameters and application model are designed according to its unique characteristics of signal time and frequency domains, and it is verified through simulation that the application of this modulation not only meets the design constraints of the eLoran system but also does not affect the reception of the respective signals of both parties. Several feasible schemes are compared, analyzed, and selected. Studies have revealed that application of UNB modulation in the eLoran system is feasible, and it will increase the data rate of the system by dozens of times.