Prof. Vyacheslav P. Tuzlukov Profile

Prof. Vyacheslav P. Tuzlukov

Invited Professor at Kyungpook National Univ

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Publications (20)

Proceedings Article | 18 May 2012 Paper

Detection of slow-moving targets in sea clutter by HRR generalized detector

Vyacheslav Tuzlukov

Proceedings Volume 8392, 83921L (2012) https://doi.org/10.1117/12.919844

KEYWORDS: Target detection, Atrial fibrillation, Radar, Signal detection, Signal processing, Sensors, Data modeling, Interference (communication), Laser range finders, Gadolinium

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Proceedings Article | 15 May 2012 Paper

Multichannel adaptive generalized detector based on parametric Rao test

Vyacheslav Tuzlukov

Proceedings Volume 8393, 839307 (2012) https://doi.org/10.1117/12.919843

KEYWORDS: Sensors, Autoregressive models, Signal processing, Signal detection, Atrial fibrillation, Systems modeling, Statistical analysis, Interference (communication), Filtering (signal processing), Electronic filtering

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Proceedings Article | 4 May 2012 Paper

Quadriphase DS-CDMA wireless communication systems employing the generalized detector

Vyacheslav Tuzlukov

Proceedings Volume 8404, 84040G (2012) https://doi.org/10.1117/12.920351

KEYWORDS: Atrial fibrillation, Pulse shaping, Signal processing, Wireless communications, Telecommunications, Receivers, Sensors, Interference (communication), Systems modeling, Monte Carlo methods

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Proceedings Article | 4 May 2012 Paper

Implementation of generalized detector for distributed sources using sensor arrays

Vyacheslav Tuzlukov

Proceedings Volume 8361, 83610V (2012) https://doi.org/10.1117/12.919579

KEYWORDS: Phased arrays, Signal to noise ratio, Sensors, Atrial fibrillation, Interference (communication), Remote sensing, Signal processing, Signal detection, Computer simulations, Fermium

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Proceedings Article | 21 June 2011 Paper

Adaptive detection of range-spread targets by the generalized detector

Vyacheslav Tuzlukov

Proceedings Volume 8021, 802112 (2011) https://doi.org/10.1117/12.883759

KEYWORDS: Atrial fibrillation, Target detection, Sensors, Radar, Signal processing, Signal to noise ratio, Scattering, Signal detection, Interference (communication), Environmental sensing

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Proceedings Article | 5 May 2011 Paper

Diversity detection in non-Gaussian noise employing the generalized approach to signal processing in noise with fading diversity channels

Vyacheslav Tuzlukov

Proceedings Volume 8050, 80501O (2011) https://doi.org/10.1117/12.883763

KEYWORDS: Atrial fibrillation, Interference (communication), Signal processing, Receivers, Signal detection, Sensors, Statistical analysis, Monte Carlo methods, Signal to noise ratio, Signal attenuation

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Proceedings Article | 28 April 2010 Paper

Optimal waveforms for MIMO radar systems employing the generalized detector

Vyacheslav Tuzlukov

Proceedings Volume 7697, 76971G (2010) https://doi.org/10.1117/12.850858

KEYWORDS: Radar, Atrial fibrillation, Sensors, Antennas, Target detection, Signal processing, Americium, Interference (communication), Detection and tracking algorithms, Scattering

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Proceedings Article | 16 April 2010 Paper

MIMO radar systems based on the generalized detector and space-time coding

Vyacheslav Tuzlukov

Proceedings Volume 7698, 769805 (2010) https://doi.org/10.1117/12.850668

KEYWORDS: Radar, Atrial fibrillation, Signal processing, Sensors, Interference (communication), Antennas, Target detection, Receivers, Systems modeling, Matrices

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Proceedings Article | 25 May 2004 Paper

Network-assisted diversity for random-access wireless sensor networks under the use of the generalized approach to signal processing

Vyacheslav Tuzlukov, Wong-Sik Yoon, Yong Deak Kim

Proceedings Volume 5473, (2004) https://doi.org/10.1117/12.546823

KEYWORDS: Sensors, Sensor networks, Signal processing, Interference (communication), Receivers, Active sensors, Signal to noise ratio, Environmental sensing, Antennas, Filtering (signal processing)

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A novel viewpoint based on the generalized approach to signal processing in the presence of noise and devoted to the collision resolution problem is introduced in this paper for wireless slotted random access sensor networks. Signal separation principles borrowed from signal processing problems are used. The received collided packets are not discarded in this approach but are exploited to extract each individual sensor node packet information. In particular, if k sensor nodes collide in a given time slot, they repeat their transmission for a total of k times so that k copies of the collided packets are received. Then the receiver has to resolve a k x k source-mixing problem and separate each individual sensor node. The generalized receiver does not introduce throughput penalties since it requires only k slots to transmit k colliding packets. In the course of analysis, we consider four channels models: ideal additive white Gaussian noise channel, in which the i-th sensor node’s gain is a deterministic but unknown constant; non-fading channel with power control but arbitrary phase, in which the amplitude of the i-th sensor node’s gain is constant (may be unknown), whereas the phase is random and uniformly distributed within the limits of the interval [0,2π]; Rayleigh fading channel, in which the phase is uniformly distributed within the limits of the interval [0,2π], whereas the amplitude is distributed with the parameter, σ_A and the amplitude and phase are independent; Rician fading channel, in which the phase is uniformly distributed within the limits of the interval [0,2π], whereas the amplitude is Rician distributed with the parameter A and σ_A and the amplitude and phase are independent. Performance issues that are related to the implementation of the collision detection algorithm based on the generalized approach to signal processing in the presence of noise demonstrate a great superiority in comparison with well-known methods. The protocol’s parameters are optimized to maximize the system throughput. Under the use of the generalized approach to signal processing in the presence of noise, the system throughput is higher in comparison with modern methods and algorithms.

Proceedings Article | 18 October 2001 Paper

Probability of detection of mines and minelike targets in deep water using generalized detector with digital threshold device

Vyacheslav Tuzlukov

Proceedings Volume 4394, (2001) https://doi.org/10.1117/12.445457

KEYWORDS: Sensors, Target detection, Signal detection, Signal to noise ratio, Radar, Analog electronics, Signal attenuation, Land mines, Interference (communication), Quantum efficiency

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This article is devoted to a study of the power signal-to- noise ratio at the output of the generalized detector with the digital threshold device during radar scanning with the purpose of detecting the mines and minelike targets in deep water. The miens and minelike targets in deep water are considered as the targets with fluctuating parameters. Theoretical and experimental investigations of the generalized detector with the digital threshold device used in mine and minelike target detection system allows us to make the statement that the fluctuating parameters of the mines and minelike targets do not lead to power signal-to- noise ratio loses at the output of the generalized detector with the digital threshold device, if the number of target return signals within the limits of the beamwidth during radar scanning is very high. Whenthe number of the target return signals within the limits of the beamwidth during radar scanning is varied from 10 to 100, the power signal- to-noise ratio losses at the output of the generalized detector with the digital threshold device are approximately equal to 0.5 dB in comparison with the case of nonfluctuating parameters of the target return signals. These power signal-to-noise ratio loses at the output of the generalized detector with the digital threshold device are caused by fluctuations of parameters of the target return signals from target return signal to target return signal during radar scanning. The optimal value of the digital threshold of the generalized detector depends on the number of target return signals within the limits of the beam width during radar scanning. If the fluctuations of the parameters of the target return signals form target return signal to target return signal during radar scanning exist, the optimal value of the digital threshold is less than that in the case of nonfluctuating parameters of the target return signals. The use of the generalized detector with the digital threshold device in the mine and minelike target detection system allows us to obtain a larger number of better detection performances of the mines and minelike targets in deep water in comparison with modern optimal signal processing algorithms.

Proceedings Article | 4 October 1999 Paper

Experimental study and functioning principles of generalized detector

Vyacheslav Tuzlukov

Proceedings Volume 3809, (1999) https://doi.org/10.1117/12.364051

KEYWORDS: Signal detection, Sensors, Signal processing, Interference (communication), Statistical modeling, Signal to noise ratio, Statistical analysis, Systems modeling, Switches, Detection theory

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Proceedings Article | 2 August 1999 Paper

Detection of deep water mines and minelike targets using the polarity coincidence generalized detector

Vyacheslav Tuzlukov

Proceedings Volume 3710, (1999) https://doi.org/10.1117/12.357025

KEYWORDS: Sensors, Signal to noise ratio, Signal detection, Signal processing, Signal attenuation, Analog electronics, Interference (communication), Quantization, Land mines, Target detection

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Proceedings Article | 4 September 1998 Paper

Signal fidelity in radar processing by employment of generalized algorithm under detection of mines and minelike targets

Vyacheslav Tuzlukov

Proceedings Volume 3392, (1998) https://doi.org/10.1117/12.324171

KEYWORDS: Receivers, Interference (communication), Signal processing, Signal to noise ratio, Signal detection, Target detection, Radar, Land mines, Radar signal processing, Signal attenuation

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Proceedings Article | 3 September 1998 Paper

Method of correlation function estimation of process at the generalized detector output

Vyacheslav Tuzlukov

Proceedings Volume 3373, (1998) https://doi.org/10.1117/12.324654

KEYWORDS: Sensors, Correlation function, Signal detection, Stochastic processes, Interference (communication), Signal processing, Statistical analysis, Signal generators, Holmium, Filtering (signal processing)

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Proceedings Article | 29 October 1997 Paper

Detection of signals with random initial phase by employment of the generalized algorithm

Vyacheslav Tuzlukov

Proceedings Volume 3163, (1997) https://doi.org/10.1117/12.279546

KEYWORDS: Signal detection, Sensors, Detection and tracking algorithms, Signal processing

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Proceedings Article | 22 July 1997 Paper

Detection of signals with stochastic parameters by employment of generalized algorithm

Vyacheslav Tuzlukov

Proceedings Volume 3079, (1997) https://doi.org/10.1117/12.280861

KEYWORDS: Statistical analysis, Signal detection, Stochastic processes, Detection and tracking algorithms, Signal processing, Sensors, Interference (communication), Signal to noise ratio, Amplifiers, Correlation function

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Proceedings Article | 31 May 1996 Paper

Digital signal processing by employment of generalized algorithm in detection systems for mines and minelike targets

Vyacheslav Tuzlukov

Proceedings Volume 2765, (1996) https://doi.org/10.1117/12.241255

KEYWORDS: Sensors, Signal processing, Signal detection, Stochastic processes, Interference (communication), Detection and tracking algorithms, Signal to noise ratio, Signal generators, Land mines, Target detection

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Proceedings Article | 1 September 1995 Paper

Signal-to-noise improvement by employment of generalized signal detection algorithm

Vyacheslav Tuzlukov

Proceedings Volume 2561, (1995) https://doi.org/10.1117/12.217723

KEYWORDS: Signal processing, Signal detection, Sensors, Interference (communication), Detection and tracking algorithms, Visualization, Statistical modeling, Visual process modeling, Signal to noise ratio, Signal generators

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Proceedings Article | 20 June 1995 Paper

Signal-to-noise improvement by employment of a generalized signal detection algorithm

Vyacheslav Tuzlukov

Proceedings Volume 2496, (1995) https://doi.org/10.1117/12.211376

KEYWORDS: Signal processing, Signal detection, Detection and tracking algorithms, Sensors, Algorithms, Detection theory, Interference (communication), Neodymium, Statistical analysis, Signal generators

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Proceedings Article | 4 November 1993 Paper

Signal-to-noise improvement in video signal processing

Vyacheslav Tuzlukov

Proceedings Volume 1976, (1993) https://doi.org/10.1117/12.161487

KEYWORDS: Signal processing, Interference (communication), Signal detection, Sensors, Signal to noise ratio, Detection and tracking algorithms, Video, Ions, Video processing, Electronic filtering

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