2024

Постійне посилання на фонд

https://ela.kpi.ua/handle/123456789/66700

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Перегляд 2024 за Ключові слова "621.3:519.2"

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  • Ескіз
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    Method for Selecting Pulsed Signals by Their Duration in Fading Channels
    (КПІ ім. Ігоря Сікорського, 2024) Buhaiov, M. V.; Zakirov, S. V.
    The duration of pulsed signals is one of the main parameters to be estimated in radio monitoring systems. When signals propagate in channels with deep fading, even at high signal-to-noise ratios, the pulse shape will be distorted. In sophisticated electronic environment, it is also may be random interference in signal processing channel, which leads to the occurrence of false pulses with random durations. Therefore, the values of the signal pulses durations will be concentrated near their true value, and the rest of the detected pulses will have a significantly random duration. That’s why, the development and study of methods for selecting pulse signals by their durations in sophisticated signal environment is actual scientific problem. The aim of the work is improving pulsed signals processing methods in fading channels by selecting its’ durations. The study found that the estimates of signal pulse durations are normally distributed. Pulse durations that are not related to signals are subjected to an exponential distribution. The input data for the proposed method is only a sample of measured pulse durations. The values of the parameters of both the exponential and normal distributions are unknown. In this case, the problem of selecting pulses by their durations is formalized to the estimation of the mean values of normal distributions. To do this, it is proposed to search for the maxima of the smoothed estimate of the probability density function. The scientific novelty of the obtained results is that a method for estimating the mean value of a normal distribution at the background of exponentially distributed values was proposed. An example of this approach is the estimation of pulsed signal durations in channels with deep fading and impulse interference. Based on the developed method, algorithms for automatic pulse selection for radio monitoring systems can be implemented.
  • Ескіз
    ДокументВідкритий доступ
    Аlgorithm for Spectrum Sensing and Signal Selection by External Parameters
    (КПІ ім. Ігоря Сікорського, 2024) Buhaiov, M. V.
    For modern radio monitoring, a panoramic view of a wide frequency band and signal selection is its most important part. The constant growth of the number of radio electronic devices and the expansion of the instantaneous bandwidth of analysis in modern radio receiving devices leads to the fact that a significant number of analog and digital signals can be observed at the same time. Automatic adaptation of radio monitoring system to further signal processing is possible due to preliminary signal selection. The goal of this research is to develop an algorithm for signals selection in panoramic radio monitoring systems by their external parameters. The essence of proposed algorithm is to detect occupied bands of radio frequency spectrum, estimate center frequency and bandwidth of each channel, noise level and signal-tonoise ratio. Creation of frequency channels allows for signal filtering and estimation of pulse durations, as well as occupancy of each channel. Estimates of parameter for each signal fragment and frequency channel are recorded in associative arrays, which simplifies further signal selection. Due to variability of noise and propagation channel, estimates of signal parameters for each signal fragment are random variables. To obtain reliable estimates of signal center frequency and bandwidth, they are further grouping. Array of data can be accessed both by frequency channel number (table rows) and by signal parameters (keys), which are table column headers. Associative relationships between data provide flexible signals filtering by any combination of parameters. To test developed algorithm, we analyzed frequency band of 933-953 MHz and used the DataFrame Multi Index data container of Pandas package of Python programming language. This structure provides multi-level indexing, flexible access to data, and a wide range of tools for their processing and modifying. Developed algorithm can be used in existing and future radio monitoring systems for radio electronic devices identification and databases creation.