Radioelectronics and Communications Systems

Application of predictability index for process classification in information and communication systems

Mon, 27 May 2024 00:00:00 +0300

The modern development of information and communication systems (ICS) in the context of the widespread use of radio signals with statistical and dynamic characteristics close to those of white noise requires new approaches to the correct decision-making on the natural or artificial character of the process observed during the electronic intelligence.

In this paper, we propose to use the SG (Savit and Green) predictability index to classify the processes used in ICS. With the help of the proposed identification scale, which uses SG index as a parameter, the processes are analyzed and conventionally divided into three classes: IID-processes, chaotic processes with a destructured image in pseudo-phase space (IPPS), chaotic processes with a structured IPPS, and periodic processes. For each process, a histogram of the distribution of SG values on the identification scale is plotted.

Based on the conducted analysis, it was established that the identification scale based on the SG value effectively distinguishes not only classes of processes (for example, random, chaotic, and deterministic), but also processes within individual classes, for example, it distinguishes chaotic processes with destructured and structured IPPS. The results demonstrate statistical significance and reliability of the new classification method, making it promising for use in real ICS.

Formation of quadrature components with error estimation for I/Q-demodulators

Vadym Slyusar, Nataliia Bihun — Mon, 27 May 2024 00:00:00 +0300

The paper investigates the influence of the choice of weighting coefficients on the formation of quadrature components in I/Q demodulators. It proposes methods to improve the accuracy of I/Q demodulation and minimize quadrature errors. Different configurations of 8- and 10-sample I/Q demodulators with open sets of weighting coefficients are considered. Using simulation, it has been shown that certain sets of coefficients can significantly improve the amplitude-frequency characteristics, achieving a bandwidth narrowing of 1.5–1.7 times and better suppression of out-of-band interference. The synthesis of new sets of coefficients for 10-sample I/Q demodulators is also investigated, which leads to improved amplitude-frequency characteristics and reduced phase errors. The equivalence between combinations of two-stage demodulators and their single-stage counterparts is established, providing potential computational efficiency advantages. The proposed 13- and 15-sample equivalent filters demonstrate a high frequency filtering efficiency and zero orthogonalization error, making them a promising alternative to 16-sample demodulators. The obtained results emphasize the importance of choosing weighting coefficients to optimize the performance of I/Q demodulators and contribute to developing more accurate and efficient digital communication systems with increased noise immunity.

Selection justification of thermal image system lens characteristics for unmanned aerial vehicle

Valentin Kolobrodov, Volodymyr Mykytenko, Grygorij Tymchik — Mon, 27 May 2024 00:00:00 +0300

The necessity to increase kamikaze drones’ efficiency and to reduce their cost is caused by their significant prevalence. In this sense, it is necessary to equip such unmanned aerial vehicles (UAV) with inexpensive thermal image cameras. The target detection range and recognition with a given probability are principal consumer evaluations for remote surveillance thermal image systems. Currently, in this case, using microbolometric matrix detectors with inexpensive infrared lenses is the best technical solution. The calculation method is advisable to justify the lens parameters compatible with the selected detector and ensure maximum operational efficiency. The article is devoted to the simplified synthesis method for developing the main parameters of the UAV thermal image system lens for the chosen type of microbolometric matrix detector. The methodology is based on the noise equivalent temperature difference. Based on the proposed method, a calculation example of a lens for an inexpensive on-board thermal imager of a kamikaze drone is given.

Compact filter-rotator of polarization plane with uniform angular response

Anatoly Kirilenko, Sergiy Steshenko, Yevhenii Ostryzhnyi — Mon, 27 May 2024 00:00:00 +0300

The paper proposes a narrow-band polarization plane filter-rotator in a circular waveguide with minimal longitudinal dimensions (~λ/30) and a 2–3% bandwidth at a return loss level of 20 dB in the center of a double-humped passband. The rotator consists of two closely spaced irises, each with a single centered rectangular slot. In contrast to rotators with rotational symmetry C_n of order n > 2, which rotate an incoming linearly polarized wave by the same angle irrespective of its polarization direction, the proposed device allows us to rotate a wave polarized orthogonally to the wide wall of the rectangular slot of the first iris. The possibility of rotation at any angle slightly less than 90° is demonstrated. The polarization plane’s rotation angle differs from the second iris’s rotation angle by fractions of a degree. Therefore, the design of the device allows us to use an intuitive synthesis algorithm. The mutual influence and permutation of the complex eigenfrequencies of the meta-cell from a pair of single-slot irises explain the double-humped AFC. The device can provide a smooth mechanical adjustment of the polarization plane within ±14° with good matching by rotating the second iris around its axis. We used our implementation of the mode-matching techniques and the method of generalized scattering matrices for the calculations.

Transformative advancements in fetal cardiac health on BiLSTM networks for FPCG classification

Yojana Sharma, Shashwati Ray, Om Prakash Yadav — Thu, 22 May 2025 00:00:00 +0300

This article unveils a cutting-edge methodology for Fetal Phonocardiogram (FPCG) classification employing Bidirectional Long Short-Term Memory (BiLSTM) networks. Acknowledging the pivotal role of fetal heart monitoring in early anomaly detection, the research delves into the profound insights offered by FPCG signals concerning fetal cardiac activity. The innovative approach encompasses preprocessing FPCG signals using Mel-Frequency Cepstral Coefficients (MFCC) and spectrogram features, coupled with the strategic application of BiLSTM networks, ensuring a resilient classification framework. The bidirectional nature of the LSTM architecture elevates the model’s ability to capture temporal dependencies in both forward and backward directions, facilitating the discernment of intricate patterns in fetal heart sounds. Experimental findings demonstrate a 98% accuracy, reaffirming the effectiveness and precision of the BiLSTM approach in FPCG classification. This research significantly advances automated methods for evaluating fetal cardiac health, promising transformative enhancements in prenatal care.