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Compound precoding: a pre-equalisation technique for the bandlimited Gaussian channel

IET COMMUNICATIONS 2009年第8期3卷 1432-1441页

作者： Flanagan, M. F. McLaughlin, M. Fagan, A. D. Univ Coll Dublin Dept Elect & Elect Engn Dublin 4 Ireland DecaWave Ltd Digital Depot Dublin 8 Ireland

Compound precoding is a state-of-the-art technique for combining trellis coding and decision-feedback equalisation (DFE) prior to upstream transmission on the telephone-line channel, and is an option in the International Telecommunications Union (ITU)-T V. 92 standard. In this paper, we provide a detailed overview of this technique. We demonstrate that compound precoding combines in a straightforward manner with most practical trellis codes. We show that compound precoding exhibits a signal-to-noise ratio (SNR) gain with respect to other schemes which combine with trellis coding, and quantify this gain. We also show that, for stability of the compound precoder, the precoder feedforward filter must be decomposed into its constituent minimum phase (MP) and all pass (AP) components. Finally, a simulation study of V. 92 upstream transmission demonstrates the shaping advantage of compound precoding over competitor techniques for pre-equalisation in this setting.

关键词： precoding channel coding decision-feedback equalisation filtering methods in signal processing bandlimited Gaussian channel trellis code telephone-line channel Gaussian channels state-of-the-art technique trellis codes feedforward filter pre-equalisation technique Communication channel equalisation and identification filtering theory International Telecommunications Union decision feedback equalisers Codes

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Design of a robust and secure digital signature scheme for image authentication over wireless channels

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IET INFORMATION SECURITY 2009年第1期3卷 1-8页

作者： Saad, S. M. Univ Alexandria Dept Informat Technol Inst Grad Studies & Res Alexandria Egypt

The introduction of 3G wireless communication systems, together with the invasive distribution of digital images and the growing concern on their originality triggers an emergent need of authenticating images received by unreliable channels, such as public Internet and wireless networks. To meet this need, a content-based image authentication scheme that is suitable for an insecure network and robust to transmission errors is proposed. The proposed scheme exploits the scalability of a structural digital signature in order to achieve a good trade off between security and image transfer for networked image applications. In this scheme, multi-scale features are used to make digital signatures robust to image degradations and key-dependent parametric wavelet filters are employed to improve the security against forgery attacks. This scheme is also able to distinguish tampering areas in the attacked image. Experimental results show the robustness and validity of the proposed scheme.

关键词： wireless channels multiscale features filtering methods in signal processing networked image application 3G wireless communication system telecommunication security Computer vision and image processing techniques Image and video coding image coding Integral transforms digital signatures secure digital signature scheme wavelet transforms feature extraction key-dependent parametric wavelet filter filtering theory forgery attack wireless channel Data security content-based image authentication scheme 3G mobile communication Mobile radio systems

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Information fusion Wiener filter for the multisensor multichannel ARMA signals with time-delayed measurements

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IET signal processing 2009年第5期3卷 403-415页

作者： Sun, X. -J. Deng, Z. -L. Heilongjiang Univ Dept Automat Harbin 150080 Peoples R China

For the multisensor multichannel autoregressive moving average (ARMA) signals with time-delayed measurements, a measurement transformation approach is presented, which transforms the equivalent state space model with measurement delays into the state space model without measurement delays, and then using the Kalman filtering method, under the linear minimum variance optimal weighted fusion rules, three distributed optimal fusion Wiener filters weighted by matrices, diagonal matrices and scalars are presented, respectively, which can handle the fused filtering, prediction and smoothing problems. They are locally optimal and globally suboptimal. The accuracy of the fuser is higher than that of each local signal estimator. In order to compute the optimal weights, the formulae of computing the cross-covariances among local signal estimation errors are given. A Monte Carlo simulation example for the three-sensor target tracking system with time-delayed measurements shows their effectiveness.

关键词： information fusion Wiener filter Wiener filters autoregressive moving average processes linear minimum variance optimal weighted fusion rule matrix algebra time-delayed measurement Algebra prediction problem delays filtering methods in signal processing multisensor multichannel ARMA signal measurement transformation approach Kalman filters signal processing theory prediction theory state space model signal estimation error diagonal matrix sensor fusion autoregressive moving average signal distributed optimal fusion Wiener filter Kalman filtering method Other topics in statistics

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Active power measurement algorithm for power system signals under non-sinusoidal conditions and wide-range frequency deviations

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IET GENERATION TRANSMISSION & DISTRIBUTION 2009年第1期3卷 57-65页

作者： Kusljevic, M. D. Tomic, J. J. Marcetic, D. P. Termoelektro Enel AD Belgrade 11060 9 Uralska Serbia Univ Novi Sad Novi Sad 21000 Serbia

A simple approach in the design of digital algorithms for active power under non-sinusoidal conditions and wide-range frequency deviations is presented. In order to accurately estimate the fundamental component of the active power, the pure sinusoidal voltage model was assumed. Adaptive finite-impulse-response (FIR) filters are used to decompose out the fundamental components of the input voltage and current signals and to minimise the noise effects. The total active power estimation was carried out by applying adaptive low-pass FIR filters for averaging of the instantaneous power. A simple algorithm for simultaneous frequency and both fundamental and total active power estimation, in a wide range of frequency changes, with benefits in a reduced complexity and computational efforts is obtained. To demonstrate the performance of the developed algorithms, the results of computer simulations and laboratory testing are presented. The algorithm shows a very high level of robustness, as well as high measurement accuracy over a wide range of frequency changes. The algorithm convergence provided fast response and adaptability, thus, this technique provides an accurate active power estimates in about one period. It has been found that the proposed algorithm really meets the needs of online applications.

关键词： power system measurement wide-range frequency deviations adaptive low-pass FIR filters adaptive finite-impulse-response filters adaptive filters low-pass filters nonsinusoidal conditions Power system measurement and metering power system signals FIR filters filtering methods in signal processing active power measurement

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Modified input estimation technique for tracking manoeuvring targets

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IET RADAR SONAR AND NAVIGATION 2009年第1期3卷 30-41页

作者： Khaloozadeh, H. Karsaz, A. KN Toosi Univ Technol Fac Elect Engn Tehran Iran Ferdowsi Univ Mashhad Dept Elect Engn Mashhad Iran

A new input estimation (IE) model for problems in tracking manoeuvring targets is proposed. The proposed model is constructed by combining the two models of uncertainties, Bayesian and Fisher. The conventional model, which describes targets with manoeuvre, is based on the state vector of target position and velocity. The acceleration is treated as an additive input term in the corresponding state equation. The proposed method is a Kalman filter-based tracking scheme with the IE approach. The proposed model is a special augmentation in the state-space model which considers both the state vector and the unknown input vector as a new augmented state vector. In the proposed scheme, the original state and acceleration vectors are estimated simultaneously with a standard Kalman filter. The proposed tracking algorithm operates in both the non-manoeuvring and the manoeuvring modes and the manoeuvre detection procedure is eliminated. The theoretical development is verified by simulation results, which also contain some examples of tracking typical target manoeuvres. The results are compared with a traditional IE method. A comparison based on the Monte-Carlo simulation is also made to evaluate the performances of the proposed method in three scenarios: low, medium and high manoeuvring target.

关键词： Kalman filter-based tracking scheme manoeuvring target tracking Digital signal processing Bayesian models filtering methods in signal processing Bayes methods manoeuvre detection procedure modified input estimation technique Monte-Carlo simulation state-space model target tracking Kalman filters Monte Carlo methods Fisher models IE approach augmented state vector

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Range sidelobes blanking by comparing outputs of contrasting mismatched filters

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IET RADAR SONAR AND NAVIGATION 2009年第3期3卷 265-277页

作者： Levanon, N. Scharf, A. Tel Aviv Univ Dept Elect Engn Syst IL-69978 Tel Aviv Israel

Range sidelobes, a major shortcoming of radar pulse compression, are often reduced through the use of mismatched filters. The authors propose to blank the remaining sidelobes by using two or more mismatched filters, whose sidelobes are designed to peak at different delays. The authors show how to design such filters and present promising simulation results with two or more mismatched filters.

关键词： radar signal processing filtering methods in signal processing pulse compression mismatched filters range sidelobes blanking Radar equipment, systems and applications radar pulse compression filtering theory

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Adaptive detectors with diagonal loading for airborne multi-input multi-output radar

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IET RADAR SONAR AND NAVIGATION 2009年第5期3卷 493-501页

作者： Wang, J. Jiang, S. He, J. Liu, Z. Nanjing Univ Sci & Technol Dept Elect Engn Nanjing 210014 Jiangsu Peoples R China

The problem of adaptive target detection for airborne multi-input multi-output (MIMO) radars with space-time receivers in the presence of Gaussian interference (including clutter and noise) is studied. Previous work has assumed the interference covariance matrix to be known. The case with unknown covariance matrix is investigated here. By exploiting the low rank property of clutter subspace, generalised likelihood ratio test detector and adaptive matched filter detector with diagonal loading are suggested to improve the detection performance of MIMO radars in limited secondary data case. The closed-form detection probabilities and false alarm probabilities of the two proposed detectors are derived and numerically evaluated. Theoretical analysis and numerical results show the advantages of the proposed detectors.

关键词： MIMO radars adaptive filters diagonal loading airborne multi-input multi-output radar generalised likelihood ratio test detector Linear algebra (numerical analysis) adaptive detectors matched filters Radar equipment, systems and applications clutter subspace filtering methods in signal processing covariance matrices adaptive matched filter Gaussian processes Gaussian interference interference covariance matrix radar clutter radar detection airborne radar MIMO communication space-time receivers

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Computationally efficient PCRLB for tracking in cluttered environments: measurement existence conditioning approach

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IET signal processing 2009年第2期3卷 133-149页

作者： Meng, H. Hernandez, M. L. Liu, Y. Wang, X. Tsinghua Univ Dept Elect Engn Beijing 100084 Peoples R China QinetiQ Ltd ICS Dept Malvern WR14 3PS Worcs England

In this paper, we consider the problem of calculating the posterior Cramer-Rao lower bound (PCRLB) for tracking in cluttered domains in which there can be both missed detections and false alarms. We introduce a novel approach, whereby we condition on the 'existence sequence', which is a sequence of zeros and ones depending on whether at least one measurement exists at each sampling time. An existing Riccati-like recursion then provides a PCRLB conditional on each existence sequence, and an unconditional PCRLB is calculated as a weighted average of these conditional bounds. This new approach is referred to as 'measurement existence sequence conditioning' (MESC). The MESC approach is compared with both the information reduction factor (IRF) approach and measurement sequence conditioning (MSC) approach. It is proved that the MESC approach provides a less optimistic bound than the IRF approach. This is a desirable property, as it shows that the MESC bound is more realistic than the IRF bound. It is also shown that the MESC bound provides a more optimistic bound than the MSC approach. Although this is undesirable, in the simulations differences between the MESC and MSC bounds are very small (typically less than 5%). This suggests that the key reason for the over-optimism of the IRF bound is the fact that it does not take into account the effect of missed detections. Although the MESC approach treats cases with one or more detection differently to the MSC approach, the similarity between these two bounds suggests that discriminating between such cases is of less importance. However, the greatest value of the new MESC approach is that the bound can be enumerated precisely, without the need for inefficient and computationally expensive sampling. In case studies, we show that the MESC bound can be calculated 10-100 times more quickly than the MSC bound. It is concluded that the novel MESC formulation introduced herein represents an exciting development in the determination o

关键词： nonlinear filters Riccati-like recursion cluttered domain tracking filtering methods in signal processing information reduction factor approach nonlinear filtering target tracking posterior Cramer-Rao lower bound measurement existence sequence conditioning signal processing theory clutter

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Time-varying discrete-time signal expansions as time-varying filter banks

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IET signal processing 2009年第5期3卷 353-367页

作者： Wang, G. Chongqing Univ Posts & Telecommun Chongqing 400065 Peoples R China

The time-varying discrete-time signal expansion was analysed based on the theory of time-varying filter banks in detail. A general definition of time-varying discrete-time wavelet transforms is provided. Usually, a time-varying discrete-time signal expansion can be implemented using a time-varying filter bank. Using the time-varying filter bank theory, the authors developed a useful algorithm to calculate the dual basis function in a biorthogonal time-varying discrete-time signal expansion. Example is given to show the usage of the algorithm. In the last part, the authors provide a detailed analysis of the general time-varying discrete-time wavelet transform. Some useful properties of the time-varying discrete-time wavelet transform including their proofs are given. The relationship between the tree-structured implementation and the non-uniform filter bank implementation is discussed.

关键词： Integral transforms filtering methods in signal processing dual basis function wavelet transform wavelet transforms discrete time filters biorthogonal time-varying discrete-time signal expansion time-varying filter bank signal processing theory time-varying filters

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Digital fractional order operators for R-wave detection in electrocardiogram signal

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IET signal processing 2009年第5期3卷 381-391页

作者： Benmalek, M. Charef, A. Dept Elect Univ Traitement Signal Lab Constantine 25000 Algeria

In this study, we present an effective R-wave detection method in the QRS complex of the electrocardiogram (ECG) based on digital differentiation and integration of fractional order. The detection algorithm is performed in two steps. The pre-processing step is based on a fractional order digital band-pass filter whose fractional order is obtained by maximising the signal to noise ratio of the ECG signal, followed by a five points differentiator of fractional order 1.5 then the squaring transformation and the smoothing are used to generate peaks corresponding to the ECG parts with high slopes. The detection step is a new and simple strategy which is also based on fractional order operators for the localisation of the R waves. The MIT/BIH arrhythmia database is used to test the effectiveness of the proposed method. The algorithm has provided very good performance and has achieved about 99.86% of the detection rate for the standard database. The results obtained are presented, discussed and compared to the most recent and efficient R-wave detection algorithms.

关键词： medical signal detection database management systems electrocardiography digital fractional order operator Biology and medical computing R-wave detection method Bioelectric signals signal to noise ratio Digital signal processing ECG signal electrocardiogram signal detection fractional order digital bandpass filter fractional order integration signal detection filtering methods in signal processing Database management systems (DBMS) Electrodiagnostics and other electrical measurement techniques band-pass filters digital differentiator digital filters MIT-BIH arrhythmia database

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