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Katalog Publikacji
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Sprzęganie w inteligentnych sterownikach mikroprocesorowych
PublikacjaPrzedstawiono ideę realizacji wymiany informacji pomiędzy systemem komputerowym i obiektem sterowania. Opisano metodę sprzężenia bezpośredniego i z wymianą potwierdzeń. Zaprezentowano ideę sprzęgania mikrokontrolera z obiektami o działaniu ciągłym z zastosowaniem układów konwerterów A/C i C/A. Szczególny nacisk położono na dobór częstotliwości próbkowania i warianty stosowanych filtrów analogowych i cyfrowych. Opisano techniki...
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On adaptive selection of estimation bandwidth for analysis of locally stationary multivariate processes
PublikacjaWhen 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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On joint order and bandwidth selection for identification of nonstationary autoregressive processes
PublikacjaWhen 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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Automated Detection of Sleep Apnea and Hypopnea Events Based on Robust Airflow Envelope Tracking in the Presence of Breathing Artifacts. - [IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS]
PublikacjaThe paper presents a new approach to detection of apnea/hypopnea events, in the presence of artifacts and breathing irregularities, from a single channel airflow record. The proposed algorithm, based on a robust envelope detector , identifies segments of signal affected by a high amplitude mo d- ulation corresponding to apnea/hypopnea events. It is show n that a robust airflow envelope - free of breathing artifacts - improves effectiveness...
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Wstępna lokalizacja otworów w wizyjnym systemie spawania wymienników ciepła
PublikacjaCoraz częściej systemy wizyjne wykorzystywane są w robotyce przemysłowej do nadzorowania przebiegu procesu technologicznego. W przypadku zrobotyzowanych stanowisk spawalniczych, wygenerowanie trajektorii głowicy spawalniczej wymaga prawidłowej lokalizacji w obrazie testowanego obiektu. W tym celu wykorzystuje się standardowe techniki przetwarzania sygnału wizyjnego, polegające na progowaniu i segmentacji obrazu. Następnie oceniane...
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Optimally regularized local basis function approach to identification of time-varying systems
PublikacjaAccurate 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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Karhunen-Loeve-based approach to tracking of rapidly fading wireless communication channels
PublikacjaWhen parameters of wireless communication channels vary at a fast rate, simple estimation algorithms, such as weighted least squares (WLS) or least mean squares (LMS) algorithms, cannot estimate them with the accuracy needed to secure the reliable operation of the underlying communication systems. In cases like this, the local basis function (LBF) estimation technique can be used instead, significantly increasing the achievable...
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Estymacja współrzędnych kątowych w radarze trójwspółrzędnym z elektronicznym skanowaniem wiązki i obracaną anteną planarną
PublikacjaW 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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On bidirectional preestimates and their application to identification of fast time-varying systems
PublikacjaWhen applied to the identification of time-varying systems, such as rapidly fading telecommunication channels, adaptive estimation algorithms built on the local basis function (LBF) principle yield excellent tracking performance but are computationally demanding. The subsequently proposed fast LBF (fLBF) algorithms, based on the preestimation principle, allow a substantial reduction in complexity without significant performance...
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Regularized identification of fast time-varying systems - comparison of two regularization strategies
PublikacjaThe problem of identification of a time-varying FIR system is considered and solved using the local basis function approach. It is shown that the estimation (tracking) results can be improved by means of regularization. Two variants of regularization are proposed and compared: the classical L2 (ridge) regularization and a new, reweighted L2 one. It is shown that the new approach can outperform the classical one and is computationally...
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On Radar DoA Estimation and Tilted Rotating Electronically Scanned Arrays
PublikacjaWe 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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Regularized Identification of Time-Varying FIR Systems Based on Generalized Cross-Validation
PublikacjaA new regularization method is proposed and applied to identification of time-varying finite impulse response systems. We show, that by a careful design of the regularization constraint, one can improve estimation results, especially in the presence of strong measurement noise. We also show that the the most appropriate regularization gain can be found by direct optimization of the generalized cross-validation criterion.
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Usuwanie zakłóceń impulsowych z archiwalnych nagrań fonicznych
PublikacjaWniniejszej 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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On Noncausal Identification of Nonstationary Multivariate Autoregressive Processes
PublikacjaThe problem of identification of nonstationary multivariate autoregressive processes using noncausal local estimation schemes is considered and a new approach to joint selection of the model order and the estimation bandwidth is proposed. The new selection rule, based on evaluation of pseudoprediction errors, is compared with the previously proposed one, based on the modified Akaike’s final prediction error criterion.
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Soft-decision schemes for radar estimation of elevation at low grazing angles
PublikacjaIn modern radars, the problem of estimating elevation angle at low grazing angles is typically solved using superresolution techniques. These techniques often require one to provide an estimate of the number of waveforms impinging the array, which one can accomplish using model selection techniques. In this paper, we investigate the performance of an alternative approach, based on the Bayesian-like model averaging. The Bayesian...
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Local basis function estimators for identification of nonstationary systems
PublikacjaThe problem of identification of a nonstationary stochastic system is considered and solved using local basis function approximation of system parameter trajectories. Unlike the classical basis function approach, which yields parameter estimates in the entire analysis interval, the proposed new identification procedure is operated in a sliding window mode and provides a sequence of point (rather than interval) estimates. It is...
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On Adaptive Spectrum Estimation of Multivariate Autoregressive Locally Stationary Processes
PublikacjaAutoregressive modeling is a widespread parametricspectrum estimation method. It is well known that, in the caseof stationary processes with unknown order, its accuracy canbe improved by averaging models of different complexity usingsuitably chosen weights. The paper proposes an extension of thistechnique to the case of multivariate locally stationary processes.The proposed solution is based on local autoregressive...
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Fast Basis Function Estimators for Identification of Nonstationary Stochastic Processes
PublikacjaThe problem of identification of a linear nonsta-tionary stochastic process is considered and solved using theapproach based on functional series approximation of time-varying parameter trajectories. The proposed fast basis func-tion estimators are computationally attractive and yield resultsthat are better than those provided by the local least squaresalgorithms. It is shown that two...
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Two-Stage Identification of Locally Stationary Autoregressive Processes and its Application to the Parametric Spectrum Estimation
PublikacjaThe problem of identification of a nonstationary autoregressive process with unknown, and possibly time-varying, rate of parameter changes, is considered and solved using the parallel estimation approach. The proposed two-stage estimation scheme, which combines the local estimation approach with the basis function one, offers both quantitative and qualitative improvements compared with the currently used single-stage methods.
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Identification of nonstationary processes using noncausal bidirectional lattice filtering
PublikacjaThe problem of off-line identification of a nonstationary autoregressive process with a time-varying order and a time-varying degree of nonstationarity is considered and solved using the parallel estimation approach. The proposed parallel estimation scheme is made up of several bidirectional (noncausal) exponentially weighted lattice algorithms with different estimation memory and order settings. It is shown that optimization of...
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A concept of software extension of 3D low-PRF radar systems to 4D semi-medium-PRF radar systems
PublikacjaWe present a concept of software modification of three-dimensional (3D) radar systems, designed to work in the low pulse repetition frequency mode, that equips them with the ability to estimate the radial velocity and to properly measure the range of targets that are detected outside the radar’s instrumented range. Despite the fact that the proposed modifications are designed so as to require only minor changes in software, they...
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Adaptation of radar software to work with ambiguous distance measurement
PublikacjaA software extension for radar stations designed to work in the low-PRF mode that allows them to correctly measure range to targets outside of their instrumented range, is proposed. The solution does not require substantial modifications of the radar software. Additionally, we describe tools that allow one to simulate the output of a low-PRF radar observing targets that are outside its instrumented range. The proposed approach...
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On autoregressive spectrum estimation using the model averaging technique
PublikacjaThe 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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Estymacja azymutu w radarze z obracaną anteną i szeroką wiązką
PublikacjaRozważono 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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On the preestimation technique and its application to identification of nonstationary systems
PublikacjaThe 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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A New Method of Noncausal Identification of Time-varying Systems
PublikacjaThe 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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RENOVATION OF ARCHIVE AUDIO RECORDINGS USING SPARSE AUTOREGRESSIVE MODELING AND BIDIRECTIONAL PROCESSING
PublikacjaThe paper presents a new approach to elimination of broadband noise and impulsive disturbances from archive audio recordings. The proposed adaptive Kalman-like algorithm, based on a sparse autoregressive model of the audio signal, simultaneously detects noise pulses, interpolates the irrevocably distorted samples and performs signal smoothing. It is shown that bidirectional (forward-backward) processing of the archive signal improves...
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New approach to noncausal identification of nonstationary stochastic systems subject to both smooth and abrupt parameter changes
PublikacjaIn this paper we consider the problem of finiteintervalparameter smoothing for a class of nonstationary linearstochastic systems subject to both smooth and abrupt parameterchanges. The proposed parallel estimation scheme combines theestimates yielded by several exponentially weighted basis functionalgorithms. The resulting smoother automatically adjustsits smoothing bandwidth to the type and rate of nonstationarityof the identified...
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Multichannel self-optimizing active noise control scheme
PublikacjaThe problem of cancellation of a nonstationary sinusoidal interference, acting at the output of an unknown multivariable linear stable plant, is considered. The proposed cancellation scheme is a nontrivial extension of the SONIC (self-optimizing narrowband interference canceller) algorithm, developed earlier for single-input, single-output plants. In the important benchmark case - for disturbances with randomwalk-type amplitude...
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From the multiple frequency tracker to the multiple frequency smoother
PublikacjaThe problem of extraction/elimination of nonstationary sinusoidalsignals from noisy measurements is considered. This problem is usually solved using adaptive notch filtering (ANF)algorithms. It is shown that the accuracy of frequency estimates can be significantly increased if the results obtained from ANF are backward-time filtered by an appropriately designed lowpass filter. The resulting adaptive notch smoothing (ANS)algorithm...
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Multiple-channel frequency-adaptive active vibration control using SONIC
PublikacjaSONIC (self-optimizing narrowband interference canceller) is an acronym of a new approach to rejection of sinusoidal disturbances acting at the output of a discretetime stable linear plant with unknown and possibly timevarying dynamics. The paper presents two frequency-adaptive extensions of the multivariate SONIC algorithm. The efficacy of the proposed solutions is tested using our laboratory-scale active vibration control plant.
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Localization of impulsive disturbances in archive audio signals using predictive matched filtering
PublikacjaThe problem of elimination of impulsive disturbances from archive audio signals is considered and its new solution, called predictive matched filtering, is proposed. The new approach is based on the observation that a large percentage of noise pulses corrupting archive audio recordings have highly repetitive shapes that match several typical “patterns”, called click templates. To localize noise pulses, click templates can be correlated...
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Active feedback noise control in the presence of impulsive disturbances
PublikacjaThe 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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Adaptive Identification of Underwater Acoustic Channel with a Mix of Static and Time-Varying Parameters
PublikacjaWe 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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Identification of Fast Time-varying Communication Channels Using the Preestimation Technique
PublikacjaAccurate 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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Active Suppression of Nonstationary Narrowband Acoustic Disturbances
PublikacjaIn this chapter, a new approach to active narrowband noise control is presented. Narrowband acoustic noise may be generated, among others, by rotating parts of electro-mechanical devices, such as motors, turbines, compressors, or fans. Active noise control involves the generation of “antinoise”, i.e., the generation of a sound that has the same amplitude, but the opposite phase, as the unwanted noise, which causes them to interfere...
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New results on estimation bandwidth adaptation
PublikacjaThe problem of identification of a nonstationary autoregressive signal using non-causal estimation schemes is considered. Noncausal estimators can be used in applications that are not time-critical, i.e., do not require real-time processing. A new adaptive estimation bandwidth selection rule based on evaluation of pseudoprediction errors is proposed, allowing one to adjust tracking characteristics of noncausal estimators to unknown...
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Fully Adaptive Savitzky-Golay Type Smoothers
PublikacjaThe problem of adaptive signal smoothing is consid-ered and solved using the weighted basis function approach. Inthe special case of polynomial basis and uniform weighting theproposed method reduces down to the celebrated Savitzky-Golaysmoother. Data adaptiveness is achieved via parallel estimation.It is shown that for the polynomial and harmonic bases andcosinusoidal weighting sequences, the competing signal estimatescan be computed...
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Robust algorithm for active feedback control of narrowband noise
PublikacjaThe problem of active control of narrowband acoustic noise is considered. It is shown that the proposed earlier feedback control algorithm called SONIC (self-optimizing narrowband interference canceller), based on minimization of the L2-norm performance measure, can be re-derived using the L1 approach. The resulting robust SONIC algorithm is more robust to heavy-tailed measurement noise, such as the αlpha-stable noise, than the...
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Sparse vector autoregressive modeling of audio signals and its application to the elimination of impulsive disturbances
PublikacjaArchive audio files are often corrupted by impulsive disturbances, such as clicks, pops and record scratches. This paper presents a new method for elimination of impulsive disturbances from stereo audio signals. The proposed approach is based on a sparse vector autoregressive signal model, made up of two components: one taking care of short-term signal correlations, and the other one taking care of long-term correlations. The method...
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Lattice filter based autoregressive spectrum estimation with joint model order and estimation bandwidth adaptation
PublikacjaThe 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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Finite-window RLS algorithms
PublikacjaTwo 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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Decoupled Kalman filter based identification of time-varying FIR systems
PublikacjaWhen system parameters vary at a fast rate, identification schemes based on model-free local estimation approaches do not yield satisfactory results. In cases like this, more sophisticated parameter tracking procedures must be used, based on explicit models of parameter variation (often referred to as hypermodels), either deterministic or stochastic. Kalman filter trackers, which belong to the second category, are seldom used in...
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Generalized adaptive notch filters with frequency debiasing for tracking of polynomial phase systems
PublikacjaGeneralized adaptive notch filters are used for identification/tracking of quasi-periodically varying dynamic systems and can be considered an extension, to the system case, of classical adaptive notch filters. For general patterns of frequency variation the generalized adaptive notch filtering algorithms yield biased frequency estimates. We show that when system frequencies change slowly in a smooth way, the estimation bias can...
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Parallel frequency tracking with built-in performance evaluation
PublikacjaThe problem of estimation of instantaneous frequency of a nonstationary complex sinusoid (cisoid) buried in wideband noise is considered. The proposed approach employs a bank of adaptive notch filters, extended with a nontrivial performance assessment mechanism which automatically chooses the best performing filter in the bank. Additionally, a computationally attractive method of implementing the bank is proposed. The new structure...
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Regularized Local Basis Function Approach to Identification of Nonstationary Processes
PublikacjaThe problem of identification of nonstationary stochastic processes (systems or signals) is considered and a new class of identification algorithms, combining the basis functions approach with local estimation technique, is described. Unlike the classical basis function estimation schemes, the proposed regularized local basis function estimators are not used to obtain interval approximations of the parameter trajectory, but provide...
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New semi-causal and noncausal techniques for detection of impulsive disturbances in multivariate signals with audio applications
PublikacjaThis 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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Capon-like DoA estimator for rotating arrays
PublikacjaWe propose a nonparametric superresolution DoA estimator that is suitable for use with rotating arrays. The proposed method can be regarded as an extension of the Capon approach. We investigate its properties using computer simulations and present results obtained by processing of real world data.
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Azimuth estimator for a rotating array radar with wide beam
PublikacjaThe 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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Multichannel self-optimizing narrowband interference canceller
PublikacjaThe problem of cancellation of a nonstationary sinusoidal interference, acting at the output of an unknown multivariable linear stable plant, is considered. No reference signal is assumed to be available. The proposed feedback controller is a nontrivial extension of the SONIC (self-optimizing narrowband interference canceller) algorithm, developed earlier for single-input, single-output plants. The algorithm consists of two loops:...