Energy budget and methods for determining coordinates for a radiomonitoring system based on a small spacecraft

Aitmagambetov, Altay; Butuzov, Yuri; Tikhvinskiy, Valery; Kulakayeva, Aigul; Ongenbayeva, Zhadyra

doi:10.11591/ijeecs.v21.i2.pp945-956

Cited by 4 publications

(5 citation statements)

References 12 publications

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“…In this regard, an inexpensive solution for accelerating neural computing is the use of FPGAs [27]. In general, the computing resources of FPGAs in the implementation of artificial neural networks can also be applied to the processing of other signals, especially onboard low-orbit satellites [28,29].…”

Section: Discussion Of the Results Of Evaluating The Accuracy Of Huma...mentioning

confidence: 99%

The dependence of the effectiveness of neural networks for recognizing human voice on language

Nurlankyzy,

Akhmediyarova,

Zhetpisbayeva

et al. 2024

EEJET

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This study examines the effectiveness of neural network architectures (multilayer perceptron MLP, convolutional neural network CNN, recurrent neural network RNN) for human voice recognition, with an emphasis on the Kazakh language. Problems related to language, the difference between speakers, and the influence of network architecture on recognition accuracy are considered. The methodology includes extensive training and testing, studying the accuracy of recognition in different languages, and different sets of data on speakers. Using a comparative analysis, this study evaluates the performance of three architectures trained exclusively in the Kazakh language. The testing included statements in Kazakhs and other languages, while the number of speakers varied to assess its impact on recognition accuracy. During the study, the results showed that CNN neural networks are more effective in recognizing human voice than RNN and MLP. Also, it was found that the CNN has a higher accuracy in recognizing the human voice in the Kazakh language, both for a small and for a large number of announcers. For example, for 20 speakers, the recognition error in Russian was 21.86 %, whereas in Kazakhs it was 10.6 %. A similar trend was observed for 80 speakers: 16.2 % Russians and 8.3 % Kazakhs. It can also be argued that learning one language does not guarantee high recognition accuracy in other languages. Therefore, the accuracy of human voice recognition by neural networks depends significantly on the language in which training is conducted. In addition, this study highlights the importance of different sets of speaker data to achieve optimal results. This knowledge is crucial for advancing the development of reliable human voice recognition systems that can accurately identify different human voices in different language contexts

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Section: Discussion Of the Results Of Evaluating The Accuracy Of Huma...mentioning

confidence: 99%

The dependence of the effectiveness of neural networks for recognizing human voice on language

Nurlankyzy,

Akhmediyarova,

Zhetpisbayeva

et al. 2024

EEJET

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show abstract

“…In [16], an analysis of the energy budget of radio lines was carried out, and the analysis showed the possibility of applying a low-orbiting small spacecraft to fulfil radio monitoring. The analysis of the signal level at the input of the measuring onboard receiver of the radio monitoring system showed that for most ground-borne radio-electronic means, the signal-to-interference ratio is more than 10 dB, which is acceptable for satellite radio monitoring systems.…”

Section: Methodsmentioning

confidence: 99%

“…In the framework of the existing ground-borne means of radio monitoring, it is impossible to qualitatively carry out the functions and problems of radio monitoring. One of the directions for improving the effectiveness of radio monitoring systems is to study the possibility of using loworbiting small spacecraft (SS) as radio monitoring stations [16]- [21]. Such systems possess a range of advantages, including high efficiency, a global view, and total coverage of the territory.…”

Section: Introductionmentioning

confidence: 99%

Improvement of Signal Reception Reliability at Satellite Spectrum Monitoring System

et al. 2022

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Extensively increasing numbers of radio electronic devices significantly complicate the electromagnetic situation under conditions of radio frequency spectrum deficiency and require improvement in the functions and mechanisms of spectrum monitoring systems. Today, in the framework of the existing ground-borne spectrum monitoring system, it is impossible to qualitatively perform the functions and problems of spectrum monitoring. Spectrum (radio) monitoring is one of the main techniques for spectrum load estimation to solve problems of perspective management of the radio frequency spectrum with the purpose of developing new radio technologies. Therefore, the problem of improving the effectiveness of spectrum monitoring does not lose relevance. When solving such problems, one of the most important factors is the extraction of an effective signal with background noise and interference. Therefore, the effectiveness of the Kalman filter application for satellite-based radio monitoring systems is considered in this study. The proposed method for detecting radio signals using Kalman filters makes it possible to make correct decisions with high accuracy. The simulation results show that Kalman filters work effectively even at a negative signal-to-noise ratio (90% and higher), adapting to the original signal at different noise dispersions in a noisy signal. It can be concluded that this method can be successfully applied to solve problems of detecting sources of radiation of a certain frequency according to the signal registered by the onboard receiver of the satellite spectrum monitoring system. The influence of the Kalman filter decisionmaking speed on the results of radio signal processing was estimated.INDEX TERMS Kalman filter, low-orbit small spacecraft, Satellite Spectrum Monitoring radio-frequency spectrum, radio monitoring.

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“…These limitations are primarily due to the fact that if it is impossible to describe mathematically the process generating the desired signal, then it becomes impossible to use the Kalman filter. Also a weak link is the similarity coefficient, which has proven itself very well for the processes described by equation (1). But in the considered process, it was assumed all the time that the amplitude of the desired signal does not change.…”

Section: Investigation Of the Dependence Of The Decision-making Speed...mentioning

confidence: 99%

“…In [1], an analysis of the signal levels at the input of the receiver of the radio monitoring system was carried out, which showed that for most of the considered ground-based radio electronic means, the SNR ratio is greater than 10 dB, which is acceptable for radio monitoring on the basis of a small satellite. However, it is noted in the work that for the effective operation of the radio monitoring system based on the small satellite it is necessary to apply special methods of processing weak signals, the use of on-board receivers with increased sensitivity and antennas with increased gain.…”

Section: Literature Review and Problem Statementmentioning

confidence: 99%

Identifying the regularities of the signal detection method using the Kalman filter

Medetov,

Kulakayeva,

Zhetpisbayeva

et al. 2023

EEJET

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Currently, it is more efficient to use LEO small spacecraft as radio control points to determine the compliance of the radiation parameters of electronic means with the relevant norms and conditions of permits for the use of the radio frequency spectrum. Such satellite radio monitoring systems make it possible to determine the parameters of signals and the location of radio-electronic means over a large area with a diverse terrain, which will increase the efficiency of radio monitoring systems. When performing such tasks, one of the most important parameters is the detection and isolation of a useful signal against the background of noise and interference. For such purposes, it is effective to use Kalman filters. It was found that the Kalman filter can detect and isolate useful signals against the background of noise and interference with very high accuracy. However, when solving such problems, problems arise related to the stability of the method to the choice of the initial state of the filter and the inevitable distortion of the frequency of the desired signal due to the presence of the Doppler effect. In the course of this study, it was found that the similarity coefficient depends on the noise level, but it does not actually depend on frequency distortion. It was also found that when the SNR ratio is greater than 0 dB, the radio signal at the input of the on-board measuring receiver will be received with a reliability of more than 90 %. Therefore, it can be concluded that the signal detection method for satellite radio monitoring based on the use of the Kalman filter is resistant to possible frequency distortions of the desired signal due to the Doppler effect and does not affect the correctness and speed of decisions made

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Energy budget and methods for determining coordinates for a radiomonitoring system based on a small spacecraft

Cited by 4 publications

References 12 publications

The dependence of the effectiveness of neural networks for recognizing human voice on language

The dependence of the effectiveness of neural networks for recognizing human voice on language

Improvement of Signal Reception Reliability at Satellite Spectrum Monitoring System

Identifying the regularities of the signal detection method using the Kalman filter

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