Kostiantyn Prokopenko

@nau.edu.ua

Faculty of Computer Science
National Aviation University



                 

https://researchid.co/kprok78

RESEARCH, TEACHING, or OTHER INTERESTS

Signal Processing

23

Scopus Publications

73

Scholar Citations

4

Scholar h-index

2

Scholar i10-index

Scopus Publications

  • Comparison of Neural Network and Statistical Approaches to the Problem of Signal Detection
    Ihor Prokopenko, Kostiantyn Prokopenko, and Anastasiia Dmytruk
    Springer Nature Switzerland

  • Application of Neural Network Technologies in Signal Detection Tasks
    Ihor Prokopenko, Kostiantyn Prokopenko, and Anastasiia Dmytruk
    IEEE
    The paper considered the problem of applying neural network technologies to detect signals in conditions of complex non-Gaussian disturbances with a priori uncertainty of probability distributions. In particular, the synthesis and comparative analysis of two approaches to the detection of a harmonic signal with a known frequency and an unknown phase against the background of correlated autoregressive interference was carried out. The first approach is based on the procedure of statistical synthesis of the adaptive signal detection algorithm. The second approach involves the use of a neural network in combination with the Fourier transform. It was noted that neural network algorithms significantly outperform optimal algorithms in modeling the action of non-Gaussian impulse disturbances, but demonstrate lower efficiency compared to the action of Gaussian correlated interferences.

  • Robust Algorithms for Random Signal Detection in Condition of Aprioristic Uncertainty
    Igor Prokopenko, Kostiantyn Prokopenko, Igor Omelchuk, and Olena Omelchuk
    IEEE
    The task of random narrowband signal detection on background of uncorrelated Gaussian noise and chaotic puls interference is considered. Three robust detection algorithms are synthesized and they efficiencies and robustness are investigated.

  • Synthesis and Effectivity Analysis of Robust Radar Signal Detection Algorithms
    Igor Prokopenko, Vitalii Vovk, and Kostiantyn Prokopenko
    IEEE
    Two robust adaptive locally-optimal algorithms for detecting pulse radar signals (with carrier frequency and random phase) on the background of mixed correlated sea clutter and ultrashort pulse (USP) noise are synthesized. Estimating parameters of USP and autoregressive clutter model are applied during the procedure of synthesis. Effectivity of suggested algorithms is investigated. These algorithms can be used for detection of high-speed targets under the condition of extremely harmful short glares of sea clutter and USP interferences when using microwave and millimeter wave radar.

  • Synthesis of detection algorithm for harmonic signal and second-order autoregressive sea clutter model
    Igor Prokopenko, Vitalii Vovk, and Kostiantyn Prokopenko
    IEEE
    A short-time autocorrelation function of reflections from sea surface can be described by exp-cosine model. It means that such reflections can be modeled as secondorder autoregressive (AR) process. We synthesize optimal algorithm for detection of harmonic signal with known frequency and unknown phase in correlated sea clutter; AR model parameters can be estimated either from clutter model or directly from measured data. This algorithm can be used for detection of high-speed targets in sea clutter by centimeter-wave radar.

  • Robust estimation of a signal source coordinates
    Igor Prokopenko, Kostiantyn Prokopenko, Igor Omelchuk, and Iurii Chyrka
    IEEE
    The improved approaches for a single source direction-of-arrival estimation in a far-field and near-field cases are proposed. In the far-field case the multichannel maximum likelihood frequency estimation along the uniform linear array is used for direct calculation of the single real spatial frequency. In the near-field case the same method is applied for short sub-arrays for retrieving a set of local spatial frequencies that allows calculation of the source position. The precision of proposed methods is analyzed via computer simulations

  • Detection of radar signals in nonstationary correlated sea clutter
    Igor Prokopenko, Vitalii Vovk, and Kostiantyn Prokopenko
    IEEE
    In this paper we synthesize optimal algorithm for detection of harmonic signal with known frequency and unknown phase in correlated sea clutter with exponential covariation function. We made analysis of efficiency of the synthesized algorithm for detection of high-speed targets by centimeter radar for different weather conditions (sea states) by statistical simulations.

  • Slowly moving targets detection in backscatter radar data
    Igor Prokopenko, Vitalii Vovk, Kostiantyn Prokopenko, and Nadiia Babanska
    IEEE
    A problem of slowly moving targets detection arises when the velocity of tracking target is insufficient for applied detection algorithm to make fast decision about moving target presence. This work proposes an unusual statistical approach for the problem solution: to synthesize a decision making rule using comparison of high standardized moments of backscatter radar data distribution (which assumedly includes some signal from moving target in it) with distribution of normal noise or conjectural clutter. The algorithm was compared with classical MTI (moving target indication) algorithm with over period compensation and proved itself as more effective for slowly moving targets detection.

  • The use of non-Gaussian character of echo signal distribution in moving target detection systems
    Igor Prokopenko, Vitalii Vovk, Kostiantyn Prokopenko, and Nadiia Babanska
    IEEE
    In this paper we developed algorithm for detection non-Gaussianity of the signal and noise mixture. Noise at a radar receiver input has Gaussian distribution, but mixture of noise and useful signal tends to be non-Gaussian. Thus, presence of useful echo signal in the mixture can be detected with use of the proposed algorithm. Further processing in moving target detection system allows distinguishing between echo signals from stationary targets and moving ones.

  • Fast resource management algorithm for multi-position radar systems
    Igor Prokopenko, Vitalii Vovk, and Kostiantyn Prokopenko
    IEEE
    In this paper we consider the resource management task in multi-position radar systems. On the basis of hierarchical control system we consider the control level at which reallocation of an active radars is performed, depending on the operational situation in area of responsibility the system, and propose a suboptimal solution of the optimization task for minimizing the use of radar resource.

  • Moving objects recognition by micro-Doppler spectrum
    Igor Prokopenko, Kostiantyn Prokopenko, and Igor Martynchuk
    IEEE
    Doppler signals are widely used for applications in security systems, surveillance systems, radar detection and recognition of airplanes, helicopters. Also, Doppler signals recognition algorithms are widespread in automotive radar systems. There is an important task of pedestrian recognition when parking the car and when driving on the highways. Methods based on micro-Doppler spectrum, can solve the problem of objects classification by the difference in movement dynamics. Purpose of this article is to develop the algorithm for recognition of moving objects by their micro-Doppler signature.

  • CFAR rank detection and estimation of Doppler radar signals
    Igor Prokopenko, Kostiantyn Prokopenko, and Vitalii Vovk
    IEEE
    New rank algorithm for detection and estimation of radar Doppler signals is designing. The main feature is to use the ranks of after-detection samples before FFT. This non-parametric approach provides a more effective evaluation of the Doppler frequency at high noise conditions.

  • Nonparametrical rank detection and estimation of radar doppler signals
    K.I. Prokopenko
    IEEE
    New rank algorithm of detection and estimation of radar Doppler signals is designing. The main feature is to use the ranks of after-detection samples before FFT. This nonparametric approach provides a more effective evaluation of the Doppler frequency at high noise conditions.

  • Locally optimal rank CFAR signal detection algorithm
    K.I. Prokopenko, V.Iu. Vovk, and D.V. Babych
    IEEE
    Synthesis of locally optimal distribution-free decision rule was considered. A new locally optimal rank algorithm that can detect signals in different types of noise is proposed. Effectiveness of the proposed algorithm was proved.

  • Sequential target tracking based on local trajectory parameters estimation in Rayleigh clutter
    Vitalii Vovk, Igor Prokopenko, and Kostiantyn Prokopenko
    IEEE
    In this paper we propose and describe the algorithm of sequential target tracking based on local trajectory parameters estimation. The target backscattering model is Swerling III signal model, while the clutter model is Swerling I signal model. In accordance with the target and sensor models probability distribution used for modeling interference is a Rayleigh distribution, and for modeling signal the Rice distribution was used. Full target trajectory is formed by sequential joining local tracks at every scan and filtering its parameters using Kalman filter technique.

  • Signal modeling for the efficient target detection tasks


  • Adaptive algorithm for moving target detection and velocity estimation
    Igor G. Prokopenko, Felix J. Yanovsky, and Kostantin I. Prokopenko
    IEEE
    This paper presents new radar algorithm for detecting moving targets and measuring target velocities. The algorithm is based on calculating spectrum estimates by using the signals reflected from the adjacent range bins. Statistical hypothesis checking is fulfilled on the difference between the adjacent spectra. The decision-making on distinction between different spectral components is used for estimating velocity of the target. Efficiency of the algorithm is investigated by using statistical modeling. The algorithm is checked by processing a real radar data containing a signal on the background of reflections from rain.

  • Adaptive algorithm for moving target detection and velocity estimation
    Igor G. Prokopenko, Felix J. Yanovsky, and Kostantin I. Prokopenko
    IEEE
    This paper presents new radar algorithm for detecting moving targets and measuring target velocities. The algorithm is based on calculating spectrum estimates by using the signals reflected from the adjacent range bins. Statistical hypothesis checking is fulfilled on the difference between the adjacent spectra. The decision-making on distinction between different spectral components is used for estimating velocity of the target. Efficiency of the algorithm is investigated by using statistical modeling. The algorithm is checked by processing a real radar data containing a signal on the background of reflections from rain.

  • Nonparametric algorithm for radar detection of moving target
    I. Prokopenko and K. Prokopenko
    IEEE
    New nonparametric algorithm of radar signal disorder detection has been considered. The algorithm is based on spectral estimation of a few signal samples of some close windows and nonparametric rank test application to compare them. The algorithm can be used for radar signal detection specifically in the tasks of turbulence detection in clouds and precipitation as well as for moving target detection. The efficiency of new algorithm is analyzed.

  • Adaptive algorithms for doppler weather radar
    I.G. Prokopenko, K.I. Prokopenko, F.J. Yanovsky, and L.P. Ligthart
    IEEE
    New complex adaptive algorithms of detection and measurement of turbulence intensity in weather formations are proposed. Algorithms are based on calculation of spectrum estimations by using the signals reflected from the adjacent range bins. Statistical hypothesis about the difference between the adjacent or next spectra are checked. The decision-making on distinction of spectra is done by the estimation of RMS velocities of Doppler spectra. Serviceability and efficiency of new algorithms proves to be true by using statistical modeling as well as by processing real signals of weather radar

  • Adaptive algorithms for doppler weather radar
    I.G. Prokopenko, K.I. Prokopenko, F.J. Yanovsky, and L.P. Ligthart
    IEEE
    New complex adaptive algorithms of detection and measurement of turbulence intensity in weather formations are proposed. Algorithms are based on calculation of spectrum estimations by using the signals reflected from the adjacent range bins. Statistical hypothesis about the difference between the adjacent or next spectra are checked. The decision-making on distinction of spectra is done by the estimation of RMS velocities of Doppler spectra. Serviceability and efficiency of new algorithms proves to be true by using statistical modeling as well as by processing real signals of weather radar.

  • Nonparametric algorithm for a detection of random process disorder in the signals of radar remote sensing
    I. Prokopenko and K. Prokopenko
    IEEE
    A new nonparametric algorithm of radar signal disorder detection is considered. The algorithm is based on spectral estimation of a few signal samples of some close windows and application of a nonparametric Wilkockson's test to compare them. The algorithm can be used for radar signal detection specifically in the tasks of turbulence detection in clouds and precipitation as well as for moving target detection. The efficiency of the new algorithm is analyzed.

  • Radar estimation of turbulence eddy dissipation rate in rain


RECENT SCHOLAR PUBLICATIONS

  • Comparison of Neural Network and Statistical Approaches to the Problem of Signal Detection
    I Prokopenko, K Prokopenko, A Dmytruk
    International Workshop on Advances in Civil Aviation Systems Development 2024

  • Application of Neural Network Technologies in Signal Detection Tasks
    I Prokopenko, K Prokopenko, A Dmytruk
    2023 IEEE International Conference on Information and Telecommunication 2023

  • ВИКОРИСТАННЯ СТІЙКИХ АЛГОРИТМІВ В ЗАДАЧІ ВИЯВЛЕННЯ РУХОМИХ ЦІЛЕЙ НА ТЛІ НЕГАУСІВСЬКИХ ЗАВАД
    І Прокопенко, А Дмитрук, К Прокопенко
    Наукоємні технології 57 (1), 58-66 2023

  • Robust Algorithms for Random Signal Detection in Condition of Aprioristic Uncertainty
    I Prokopenko, K Prokopenko, I Omelchuk, O Omelchuk
    2019 IEEE 5th International Conference Actual Problems of Unmanned Aerial 2019

  • Synthesis and Effectivity Analysis of Robust Algorithms for Random Signal Detection in Non-Gaussian Interferences
    IG Prokopenko, IP Omelchuk, KI Prokopenko, AA Osipchuk
    Electronics and control systems., 9-17 2019

  • Synthesis and Effectivity Analysis of Robust Radar Signal Detection Algorithms
    I Prokopenko, V Vovk, K Prokopenko
    2018 9th International Conference on Ultrawideband and Ultrashort Impulse 2018

  • Synthesis of Detection Algorithm for Harmonic Signal and Second-Order Autoregressive Sea Clutter Model
    I Prokopenko, V Vovk, K Prokopenko
    2018 19th International Radar Symposium (IRS), 1-4 2018

  • Robust estimation of a signal source coordinates
    I Prokopenko, K Prokopenko, I Omelchuk, I Chyrka
    2017 18th International Radar Symposium (IRS), 1-8 2017

  • Detection of radar signals in nonstationary correlated sea clutter
    I Prokopenko, V Vovk, K Prokopenko
    2017 18th International Radar Symposium (IRS), 1-6 2017

  • Slowly moving targets detection in backscatter radar data
    I Prokopenko, V Vovk, K Prokopenko, N Babanska
    2016 IEEE Radar Methods and Systems Workshop (RMSW), 22-26 2016

  • The use of non-Gaussian character of echo signal distribution in moving target detection systems
    I Prokopenko, V Vovk, K Prokopenko, N Babanska
    2016 17th International Radar Symposium (IRS), 1-5 2016

  • CFAR rank detection and estimation of Doppler radar signals
    I Prokopenko, K Prokopenko, V Vovk
    2015 16th International Radar Symposium (IRS), 1064-1069 2015

  • Fast resource management algorithm for multi-position radar systems
    I Prokopenko, V Vovk, K Prokopenko
    2015 16th International Radar Symposium (IRS), 1045-1051 2015

  • Moving objects recognition by micro-Doppler spectrum
    I Prokopenko, K Prokopenko, I Martynchuk
    2015 16th International Radar Symposium (IRS), 186-190 2015

  • Nonparametrical rank detection and estimation of radar doppler signals
    KI Prokopenko
    2014 IEEE Microwaves, Radar and Remote Sensing Symposium (MRRS), 84-87 2014

  • Sequential target tracking based on local trajectory parameters estimation in Rayleigh clutter
    V Vovk, I Prokopenko, K Prokopenko
    2014 15th International Radar Symposium (IRS), 1-5 2014

  • Locally optimal rank CFAR signal detection algorithm
    KI Prokopenko, VI Vovk, DV Babych
    2014 15th International Radar Symposium (IRS), 1-4 2014

  • Fast frequency synchronization systems
    IG Prokopenko, IP Omelchuk, YD Chyrka, KI Prokopenko
    Electronics and control systems, 19-23 2014

  • Local trajectory parameters estimation and detection of moving targets in rayleigh noise
    IG Prokopenko, VI Vovk, IP Omelchuk, YD Chirka, KI Prokopenko
    Технология и конструирование в электронной аппаратуре, 23-35 2014

  • Адаптивний алгоритм сегментації мовних сигналів
    KI Prokopenko
    Електронiка та системи управлiння 2 (40), 29-32 2014

MOST CITED SCHOLAR PUBLICATIONS

  • Signal modeling for the efficient target detection tasks
    IG Prokopenko, SV Migel, KI Prokopenko
    2013 14th International Radar Symposium (IRS) 2, 976-982 2013
    Citations: 21

  • Fast resource management algorithm for multi-position radar systems
    I Prokopenko, V Vovk, K Prokopenko
    2015 16th International Radar Symposium (IRS), 1045-1051 2015
    Citations: 17

  • Moving objects recognition by micro-Doppler spectrum
    I Prokopenko, K Prokopenko, I Martynchuk
    2015 16th International Radar Symposium (IRS), 186-190 2015
    Citations: 7

  • Robust estimation of a signal source coordinates
    I Prokopenko, K Prokopenko, I Omelchuk, I Chyrka
    2017 18th International Radar Symposium (IRS), 1-8 2017
    Citations: 4

  • Detection of radar signals in nonstationary correlated sea clutter
    I Prokopenko, V Vovk, K Prokopenko
    2017 18th International Radar Symposium (IRS), 1-6 2017
    Citations: 4

  • Slowly moving targets detection in backscatter radar data
    I Prokopenko, V Vovk, K Prokopenko, N Babanska
    2016 IEEE Radar Methods and Systems Workshop (RMSW), 22-26 2016
    Citations: 3

  • The use of non-Gaussian character of echo signal distribution in moving target detection systems
    I Prokopenko, V Vovk, K Prokopenko, N Babanska
    2016 17th International Radar Symposium (IRS), 1-5 2016
    Citations: 3

  • Sequential target tracking based on local trajectory parameters estimation in Rayleigh clutter
    V Vovk, I Prokopenko, K Prokopenko
    2014 15th International Radar Symposium (IRS), 1-5 2014
    Citations: 3

  • Synthesis and Effectivity Analysis of Robust Algorithms for Random Signal Detection in Non-Gaussian Interferences
    IG Prokopenko, IP Omelchuk, KI Prokopenko, AA Osipchuk
    Electronics and control systems., 9-17 2019
    Citations: 2

  • Locally optimal rank CFAR signal detection algorithm
    KI Prokopenko, VI Vovk, DV Babych
    2014 15th International Radar Symposium (IRS), 1-4 2014
    Citations: 2

  • Local trajectory parameters estimation and detection of moving targets in rayleigh noise
    IG Prokopenko, VI Vovk, IP Omelchuk, YD Chirka, KI Prokopenko
    Технология и конструирование в электронной аппаратуре, 23-35 2014
    Citations: 2

  • Comparison of Neural Network and Statistical Approaches to the Problem of Signal Detection
    I Prokopenko, K Prokopenko, A Dmytruk
    International Workshop on Advances in Civil Aviation Systems Development 2024
    Citations: 1

  • Application of Neural Network Technologies in Signal Detection Tasks
    I Prokopenko, K Prokopenko, A Dmytruk
    2023 IEEE International Conference on Information and Telecommunication 2023
    Citations: 1

  • Robust Algorithms for Random Signal Detection in Condition of Aprioristic Uncertainty
    I Prokopenko, K Prokopenko, I Omelchuk, O Omelchuk
    2019 IEEE 5th International Conference Actual Problems of Unmanned Aerial 2019
    Citations: 1

  • CFAR rank detection and estimation of Doppler radar signals
    I Prokopenko, K Prokopenko, V Vovk
    2015 16th International Radar Symposium (IRS), 1064-1069 2015
    Citations: 1

  • Fast frequency synchronization systems
    IG Prokopenko, IP Omelchuk, YD Chyrka, KI Prokopenko
    Electronics and control systems, 19-23 2014
    Citations: 1