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Katedra Sygnałów i Systemów WETI

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Katalog Publikacji

Rok 2023
Rok 2022
  • Adaptive identification of sparse underwater acoustic channels with a mix of static and time-varying parameters
    Publikacja

    - SIGNAL PROCESSING - Rok 2022

    We consider identification of sparse linear systems with a mix of static and time-varying parameters. Such systems are typical in underwater acoustics (UWA), for instance, in applications requiring identi- fication of the acoustic channel, such as UWA communications, navigation and continuous-wave sonar. The recently proposed fast local basis function (fLBF) algorithm provides high performance when identi- fying time-varying systems....

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  • Adaptive Identification of Underwater Acoustic Channel with a Mix of Static and Time-Varying Parameters
    Publikacja

    - Rok 2022

    We consider the problem of identification of communication channels with a mix of static and time-varying parameters. Such scenarios are typical, among others, in underwater acoustics. In this paper, we further develop adaptive algorithms built on the local basis function (LBF) principle resulting in excellent performance when identifying time-varying systems. The main drawback of an LBF algorithm is its high complexity. The subsequently...

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  • Estymacja współrzędnych kątowych w radarze trójwspółrzędnym z elektronicznym skanowaniem wiązki i obracaną anteną planarną
    Publikacja

    - Rok 2022

    W rozprawie zawarto historię radiolokacji oraz sposób obróbki sygnałów i danych radarowych przed etapem estymacji. Przedstawiono oraz przetestowano klasyczne metody estymacji współrzędnych wraz ze wskazaniem ich słabych oraz mocnych stron. Zaproponowano uodpornione warianty estymatorów największej wiarygodności, które pozwolił poprawić jakość oszacowania przy estymacji elewacji w warunkach propagacji wielodrogowej, redukując jednocześnie...

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  • Finite-window RLS algorithms
    Publikacja

    - SIGNAL PROCESSING - Rok 2022

    Two recursive least-squares (RLS) adaptive filtering algorithms are most often used in practice, the exponential and sliding (rectangular) window RLS algorithms. This popularity is mainly due to existence of low-complexity versions of these algorithms. However, these two windows are not always the best choice for identification of fast time-varying systems, when the identification performance is most important. In this paper, we...

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  • Optimally regularized local basis function approach to identification of time-varying systems
    Publikacja

    Accurate identification of stochastic systems with fast-varying parameters is a challenging task which cannot be accomplished using model-free estimation methods, such as weighted least squares, which assume only that system coefficients can be regarded as locally constant. The current state of the art solutions are based on the assumption that system parameters can be locally approximated by a linear combination of appropriately...

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Rok 2021
Rok 2020
  • A new look at the statistical identification of nonstationary systems

    The paper presents a new, two-stage approach to identification of linear time-varying stochastic systems, based on the concepts of preestimation and postfiltering. The proposed preestimated parameter trajectories are unbiased but have large variability. Hence, to obtain reliable estimates of system parameters, the preestimated trajectories must be further filtered (postfiltered). It is shown how one can design and optimize such...

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  • A New Method of Noncausal Identification of Time-varying Systems

    The paper shows that the problem of noncausal identification of a time-varying FIR (finite impulse response) sys- tem can be reformulated, and solved, as a problem of smoothing of the preestimated parameter trajectories. Characteristics of the smoothing filter should be chosen so as to provide the best trade- off between the bias and variance of the resulting estimates. It is shown that optimization of the smoothing operation can...

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  • On DoA estimation for rotating arrays using stochastic maximum likelihood approach

    The flexibility needed to construct DoA estimators that can be used with rotating arrays subject to rapid variations of the signal frequency is offered by the stochastic maximum likelihood approach. Using a combination of analytic methods and Monte Carlo simulations, we show that for low and moderate source correlations the stochastic maximum likelihood estimator that assumes noncorrelated sources has accuracy comparable to the...

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  • On Radar DoA Estimation and Tilted Rotating Electronically Scanned Arrays
    Publikacja

    We consider DoA estimation in a monopulse radar system employing a tilted rotating array. We investigate the case of nonzero steering angles, in which case the mapping between the target’s azimuth and elevation in the global coordinate system and their counterparts in the array local coordinate system becomes increasingly nonlinear and coupled. Since estimating the azimuth using coherently integrated signals might be difficult because...

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  • On the preestimation technique and its application to identification of nonstationary systems
    Publikacja

    The problem of noncausal identification of a nonstationary stochastic FIR (finite impulse response) sys- tem is reformulated, and solved, as a problem of smoothing of preestimated parameter trajectories. Three approaches to preestimation are critically analyzed and compared. It is shown that optimization of the smoothing operation can be performed adaptively using the parallel estimation technique. The new approach is computationally...

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Rok 2019
Rok 2018
Rok 2017
  • Akaike's final prediction error criterion revisited
    Publikacja

    When local identification of a nonstationary ARX system is carried out, two important decisions must be taken. First, one should decide upon the number of estimated parameters, i.e., on the model order. Second, one should choose the appropriate estimation bandwidth, related to the (effective) number of input-output data samples that will be used for identification/ tracking purposes. Failure to make the right decisions results...

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  • Azimuth estimator for a rotating array radar with wide beam
    Publikacja

    - Rok 2017

    The problem of estimating azimuth in rotating array radar with a beam, wide in the azimuth plane, is considered. Under such setup the echo signal usually has a very low signal to noise ratio, but the number of observations is large, because of long dwell times. The proposed solution is based on the maximum likelihood approach, but it employs simplifications which facilitate its implementation in real time systems. Results, obtained...

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  • Detection of impulsive disturbances in archive audio signals
    Publikacja

    In this paper the problem of detection of impulsive disturbances in archive audio signals is considered. It is shown that semi-causal/noncausal solutions based on joint evaluation of signal prediction errors and leave-one-out signal interpolation errors, allow one to noticeably improve detection results compared to the prediction-only based solutions. The proposed approaches are evaluated on a set of clean audio signals contaminated...

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  • Estymacja azymutu w radarze z obracaną anteną i szeroką wiązką
    Publikacja

    - Rok 2017

    Rozważono problem estymacji azymutu w radarze z obracaną anteną, w którym zastosowano wiązkę o dużej szerokości w płaszczyźnie azymutu. Radary tego typu zwykle charakteryzują się niskim stosunkiem sygnału do szumu i dużą liczbą dostępnych obserwacji echa. Zaproponowane rozwiązanie jest oparte na metodzie największej wiarygodności, zmodyfikowanej w sposób, który pozwala na implementację estymatora w systemach czasu rzeczywistego....

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  • Lattice filter based autoregressive spectrum estimation with joint model order and estimation bandwidth adaptation
    Publikacja

    The problem of parametric, autoregressive model based estimation of a time-varying spectral density function of a nonstationary process is considered. It is shown that estimation results can be considerably improved if identification of the autoregressive model is carried out using the two-sided doubly exponentially weighted lattice algorithm which combines results yielded by two one-sided lattice algorithms running forward in...

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  • New semi-causal and noncausal techniques for detection of impulsive disturbances in multivariate signals with audio applications

    This paper deals with the problem of localization of impulsive disturbances in nonstationary multivariate signals. Both unidirectional and bidirectional (noncausal) detection schemes are proposed. It is shown that the strengthened pulse detection rule, which combines analysis of one-step-ahead signal prediction errors with critical evaluation of leave-one-out signal interpolation errors, allows one to noticeably improve detection results...

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  • On adaptive covariance and spectrum estimation of locally stationary multivariate processes
    Publikacja

    - AUTOMATICA - Rok 2017

    When estimating the correlation/spectral structure of a locally stationary process, one has to make two important decisions. First, one should choose the so-called estimation bandwidth, inversely proportional to the effective width of the local analysis window, in the way that complies with the degree of signal nonstationarity. Too small bandwidth may result in an excessive estimation bias, while too large bandwidth may cause excessive...

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  • On autoregressive spectrum estimation using the model averaging technique

    The problem of estimating spectral density of a nonstationary process satisfying local stationarity conditions is considered. The proposed solution is a two step procedure based on local autoregressive (AR) modeling. In the first step Bayesian-like averaging of AR models, differing in order, is performed. The main contribution of the paper is development of a new final-prediction-error-like statistic, which can be used to select...

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  • On joint order and bandwidth selection for identification of nonstationary autoregressive processes
    Publikacja

    When identifying a nonstationary autoregressive process, e.g. for the purpose of signal prediction or parametric spectrum estimation, two important decisions must be taken. First, one should choose the appropriate order of the autoregressive model, i.e., the number of autoregressive coefficients that will be estimated. Second, if identification is carried out using the local estimation technique, such as the localized version of...

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  • Usuwanie zakłóceń impulsowych z archiwalnych nagrań fonicznych
    Publikacja

    - Rok 2017

    Wniniejszej pracy doktorskiej opisano nowe metody usuwania zakłóceń impulsowych z archiwalnych nagrań dźwiękowych odtworzonych z płyt gramofonowych. Przedstawione w rozprawie rozwiązania, takie jak analiza dwukierunkowa, dwuzakresowe modelowanie autoregresyjne oraz modelowanie wektorowe umożliwiają przetwarzanie zarówno sygnałów muzycznych jak sygnałów mowy przy zachowaniu wysokiej jakości dźwięku po obróbce. Testy odsłuchowe przeprowadzone...

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Rok 2016
  • Central heating temperature control algorithm for systems with condensing boilers
    Publikacja

    - Rok 2016

    The problem of control of a central heating system in a small residence is considered. It is assumed that the system is based on a condensing boiler. Since the boiler efficiency depends on a returning water temperature, the proposed control goal is to provide proper air temperature in the residence as well as the lowest possible water temperature. The proposed algorithm is applied to two buildings. Both of them have the same heating...

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  • High-Precision FIR-Model-Based Dynamic Weighing System

    Conveyor belt-type checkweighers are increasingly popular components of modern production lines. They are used to assess the weight of the produced items in motion, i.e., without stopping them on the weighing platform. The main challenge one faces when designing a dynamic weighing system is providing high measurement accuracy, especially at high conveyor belt speeds. The approach proposed in this paper can be characterized as a...

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  • On adaptive selection of estimation bandwidth for analysis of locally stationary multivariate processes
    Publikacja

    - Rok 2016

    When estimating the correlation/spectral structure of a locally stationary process, one should choose the so-called estimation bandwidth, related to the effective width of the local analysis window. The choice should comply with the degree of signal nonstationarity. Too small bandwidth may result in an excessive estimation bias, while too large bandwidth may cause excessive estimation variance. The paper presents a novel method...

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  • Systemidentificationbasedapproachtodynamicweighing revisited

    Dynamicweighing,i.e.,weighingofobjectsinmotion,withoutstoppingthemonthe weighing platform,allowsonetoincreasetherateofoperationofautomaticweighing systems, usedinindustrialproductionprocesses,withoutcompromisingtheiraccuracy. Sincetheclassicalidentification-basedapproachtodynamicweighing,basedonthe second-ordermass–spring–dampermodeloftheweighingsystem,doesnotyieldsa- tisfactoryresultswhenappliedtoconveyorbelttypecheckweighers,severalextensionsof thistechniqueareexamined.Experimentsconfirmthatwhenappropriatelymodifiedthe identification-basedapproachbecomesareliabletoolfordynamicmassmeasurementin checkweighers.

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Rok 2015
  • Active feedback noise control in the presence of impulsive disturbances
    Publikacja

    The problem of active feedback control of a narrowband acoustic noise in the presence of impulsive disturbances is considered. It is shown that, when integrated with appropriately designed outlier detector, the proposed earlier feedback control algorithm called SONIC is capable of isolating and rejecting noise pulses. According to our tests this guarantees stable and reliable operation of the closed-loop noise cancelling...

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