By Topic

Signal Processing, IET

Issue 2 • Date April 2011

Filter Results

Displaying Results 1 - 17 of 17
  • Analysis of space–time adaptive processing performance using K-means clustering algorithm for normalisation method in non-homogeneity detector process

    Page(s): 113 - 120
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (596 KB)  

    This study describes the performance analysis of the non-homogeneity detector (NHD) with various normalisation methods for the space-time adaptive processing (STAP) of airborne radar signals under the non-homogeneous clutter environments. The authors can calculate a threshold value from the statistical analysis of generalised inner product (GIP) using the normalisation method using mean, median and the K-means clustering algorithm of training data snapshots in the NHD process. The selected homogeneous data using the threshold value are used to recalculate covariance matrix of the total interference. To evaluate the performance of the covariance matrix, the authors calculated the eigenspectra and signal to interference noise ratio (SINR) loss. The accuracy of the recalculated covariance matrix is verified by the modified sample matrix inversion (MSMI) test statistic for the target detection. Projection statistics (PS) based on GIP is also used to compare the performance of detecting single and multiple targets. The authors- simulation results demonstrate that the K-means clustering algorithm as a normalisation method for both GIP and GIP-based PS can improve the STAP performance in the severe non-homogeneous clutter environment even under the multiple targets scenarios, compared to the other normalisation methods. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Raised cosine filter-based empirical mode decomposition

    Page(s): 121 - 129
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (581 KB)  

    The empirical mode decomposition (EMD) is a relatively new method to decompose multicomponent signals that requires no a priori knowledge about the components. In this study, a modified algorithm using raised cosine interpolation is proposed which the authors refer to as raised cosine empirical mode decomposition. The decomposition quality of this proposed technique is controllable via an adjustable parameter. This results in better performance than the original approach which produces faster convergence or lower final error under different conditions. An efficient fast Fourier transform-based implementation of the proposed technique is presented. The signal decomposition performance of the new algorithm is demonstrated by application to a variety of multicomponent signals and a comparison with EMD algorithm is presented. Computational complexity of the two techniques is compared. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Speech dereverberation in noisy environments using an adaptive minimum mean square error estimator

    Page(s): 130 - 137
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (370 KB)  

    The authors present here a novel method for reducing the late reverberation of speech signals in noisy environments. In this method, the amplitude of clean signal is obtained by an adaptive estimator that minimises the mean square error (MSE) under signal presence uncertainty. The spectral gain function, that is an adaptive variable-order minimum MSE estimator, is obtained as a weighted geometric mean of hypothetical gains associated with speech presence and absence. The order of estimator is estimated for each time frame and each frequency component individually. The authors propose the adaptation of order of estimator according to the probability of speech presence, which makes the estimation more accurate. The evaluations confirm superiority of the proposed method in dereverberation of speech signals in noisy environments. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Algorithm for Fourier coefficient estimation

    Page(s): 138 - 149
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (375 KB)  

    This study deals with the estimation of amplitude and phase of an analogue multi-harmonic band-limited signal from irregularly spaced sampling values. To this end, assuming the signal fundamental frequency is known in advance (i.e. estimated at an independent stage), a complexity-reduced algorithm for signal reconstruction in time domain is proposed. The reduction in complexity is achieved owing to completely new analytical and summarised expressions that enable a quick estimation at a low numerical error. The proposed algorithm can be applied in signal reconstruction, spectral estimation, system identification, as well as in other important signal processing problems. The proposed method of processing can be used for precise root mean square measurements (for power and energy) of a periodic signal based on the presented signal reconstruction. The authors investigate the errors related to the signal parameter estimation, and there is a computer simulation that demonstrates the accuracy of these algorithms. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Fractionalisation of an odd time odd frequency DFT matrix based on the eigenvectors of a novel nearly tridiagonal commuting matrix

    Page(s): 150 - 156
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (304 KB)  

    The discrete equivalent of Hermite-Gaussian functions (HGFs) plays a critical role in the definition of a discrete fractional Fourier transform (DFRFT). The discrete equivalents are typically calculated through the eigendecomposition of a commutator matrix. In this study, the authors mainly focus on the fractionalisation of an odd time odd frequency discrete Fourier transform (O-ODFT) matrix. First, the authors propose a novel nearly tridiagonal matrix, which commutes with the O-ODFT matrix. It does not have multiple eigenvalues. The authors can determine a unique orthonormal eigenvector set based on block diagonalisation of a new commuting matrix. The eigenvectors of the new nearly tridiagonal matrix are shown to be O-ODFT eigenvectors, which are similar to the continuous HGFs. Then, the result of the eigendecomposition of the transform matrix is used in order to define the fractionalisation of O-ODFT (O-ODFRFT). The definition is exactly unitary, index additive and reduces to the O-ODFT for unit order. Finally, numerical examples are illustrated to demonstrate that the proposed O-ODFRFT is approximated to the continuous fractional Fourier transform. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Improved parametric families of intersymbol interference-free Nyquist pulses using inner and outer functions

    Page(s): 157 - 163
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (370 KB)  

    In this article, the authors introduce and study the performance of two novel parametric families of Nyquist intersymbol interference-free pulses. Using only two design parameters, the proposed pulses yield an enhanced performance compared to the sophisticated flipped-inverse hyperbolic secant (asech) filter, which was recently documented in the literature. Although the construction of parametric families originates from the work of Beaulieu and Damen, the authors' approach is based on the concept of 'inner' and 'outer' functions and for this reason a higher flexibility in the choice of the family members is achieved. The proposed pulses may decay slower than the original raised-cosine (RC) pulse outside the pulse interval, but exhibit a more pronounced decrease in the amplitudes of the two largest sidelobes and this accounts for their improved robustness to error probabilities. It is clearly shown, via simulation results, that a lower bit error rate (BER), compared to the existing pulses, can be achieved for different values of the roll-off factor and timing jitter. Moreover, a smaller maximum distortion as well as a more open-eye diagram are attained which further demonstrate the superiority of the proposed pulse shaping filters. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Intra- and inter-frame prediction in bandwidth scalable coding of wideband speech

    Page(s): 164 - 170
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (266 KB)  

    This study discusses a predictive coding scheme that utilises both the intra-frame correlation (here referred to as redundancy between frequency bands) and inter-frame correlation in bandwidth scalable coding of wideband speech. Prediction error filters that combine intra-frame prediction with inter-frame prediction in a cascade connection are examined. Three representative intra-frame functions that have been developed in the area of bandwidth extension (BWE) are considered to see how well they exploit the intra-frame correlation. In addition, some resulting changes are investigated when they are combined with the predictive vector quantiser that exploits the inter-frame correlation. The performances of the Gaussian mixture model-based and hidden Markov model-based BWE functions are similar in the context of intra-frame coding, but both of them significantly outperform the linear BWE function in the same context. However, it is also observed that the linear function is the most promising in the context of the joint predictive coding of intra-frame and inter-frame. These results are supported by some statistical tests. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Optimal look-up table-based data hiding

    Page(s): 171 - 179
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (962 KB)  

    In this study, the authors present a novel data hiding scheme using the minimum distortion look-up table (LUT) embedding that achieves good distortion-robustness performance. LUT-based data hiding is a simple and efficient way to embed information into multimedia content for various applications, such as transaction tracking and database annotation. The authors find it possible to optimally reduce the data hiding-introduced distortion by designing the LUT according to the distribution of the host at a given robustness level. The authors first analyse the distortion introduced by LUT embedding and formulate its relationship with run constraints of LUT to construct an optimal coding problem. Subsequently, a Viterbi algorithm is presented to find the minimum distortion LUT. Then a new practical data hiding scheme using the optimal LUT is applied in the wavelet domain. Theoretical analysis and numerical results show that the new LUT design achieves not only less distortion but also more robustness than the traditional LUT-based data embedding schemes under common attacks such as Gaussian noise and JPEG compression. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Efficient detection algorithms for multi-input/multi-output systems by exploiting the non-circularity of transmitted signal source

    Page(s): 180 - 186
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (303 KB)  

    In this study, several new detection algorithms are proposed for multi-input/multi-output (MIMO) communication systems transmitting non-circular signals. Unlike the conventional receivers, the proposed detectors estimate the transmitted signal from both the received signal and its complex conjugate version. Analytical results quantifying the performance improvement are provided. As a typical example, extended zero-forcing (EZF) detector and extended minimum mean square error (EMMSE) detector are derived for the real signals. Computational complexity of the proposed algorithms remains the same order as that of the conventional zero-forcing (ZF). Simulation results show that both EZF and EMMSE detectors significantly outperform the conventional minimum mean square error (MMSE) detector, and that the ordered-successive-interference-cancelling (OSIC) version of the EZF (or EMMSE) detector has a quasi-optimal performance in terms of bit error rate (BER). View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Rao-Blackwellised unscented particle filtering for jump Markov non-linear systems: an H approach

    Page(s): 187 - 193
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (263 KB)  

    In this study, a robust Rao-Blackwellised particle filter (RBPF) is proposed for jump Markov non-linear systems (JMNLSs) with unknown noise statistics. A non-linear filter is presented by applying the unscented transform technique in the H setting, which is used to update the continuous-state particles in the RBPF framework. Moreover, a way to adaptively adjust the disturbance tolerance level for performance requirement is presented. Simulation results using the proposed approach are also presented. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Maximum likelihood and suboptimal schemes for micro-Doppler estimation using carrier diverse Doppler radars

    Page(s): 194 - 208
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (902 KB)  

    Carrier diverse radars, known as dual-frequency radars, employ two different frequencies, and can be effective in determining the moving target range in urban sensing and through-the-wall radar applications. The authors derive the maximum likelihood (ML) estimator for the micro-Doppler motion parameters from the dual-frequency radar returns. Micro-Doppler signatures, which are commonly associated with vibrating, oscillating and rotating objects, have emerged to be an important tool in target detection and classification. Unlike linear models, the respective ML estimator does not assume a closed-form expression. The authors solve the ML estimator for dual-frequency radar operations by applying an iteratively reweighted non-linear least squares algorithm (IRNLS), which is initiated using suboptimal solutions. The ML-IRNLS algorithm is applied to both simulated and experimental radar returns for estimating the range and the motion parameters of indoor targets. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • On the robustness of Hurst estimators

    Page(s): 209 - 225
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (2169 KB)  

    The presence and the nature of long-range dependent (LRD) are usually characterised by the Hurst parameter. In order to meet the requirements of analysing the LRD processes, a number of practical estimation methods have been proposed in the literature. Furthermore, some efforts have been made to evaluate the accuracy and validity of the Hurst estimators for LRD processes. In practice, however, many signals measured are corrupted with various types of noises, and sometimes even the concerned signal itself has infinite variance. In such cases, which estimator has the best robustness to the LRD property of the signal and its noise involved, and how robust it is are still unresolved. The aim of this paper is to make a quantitative analysis of the robustness of twelve commonly used Hurst parameter estimators. In this paper, we considered four types of LRD signals with possible noises. They are 1) LRD process alone; 2) LRD process corrupted by 30 dB signal to noise ratio (SNR) white Gaussian noise; 3) LRD process corrupted by 30 dB SNR stable noise; 4) fractional autoregressive moving average (FARIMA) time series with stable innovations. Moreover, the standard errors of each estimator are provided. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Comparative study of methods for human performance prediction using electro-encephalographic data

    Page(s): 226 - 234
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (508 KB)  

    The authors present here a comparative study of methods tackling the problem of predicting a person's quick or late response in an oddball experiment using their EEG data. The methods studied come from the related area of human performance monitoring (HPM) and rely on the use of kernel principal component analysis (KPCA), linear principal component analysis (LPCA), or time features combined with a support vector machine (SVM) or a Gaussian classifier. The results show the consistent superiority of the kernel PCA features, whereas SVM is marginally better than the Gaussian classifier. The classification rates produced with this combination of type of feature and classifier are moderate but they are significantly better than random for all subjects. This is important because it indicates that prediction of a person's performance using their EEG data is up to a certain extent feasible. This is a strong indication that early event related potential (ERP) components are related to brain's discrimination processes and are correlated with the reaction time in an oddball experiment. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Adaptive grid risk-sensitive filter for non-linear problems

    Page(s): 235 - 241
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (223 KB)  

    A novel adaptive grid-based method has been proposed for risk-sensitive state estimation in non-linear non-Gaussian problems. The algorithm, which is based on point-mass approximation, is called the adaptive grid risk-sensitive filter (AGRSF). Although risk-sensitive estimators have been known to be robust compared to their risk-neutral counterparts, the implementation of risk-sensitive filters (RSFs) is almost impossible except for very trivial systems like linear Gaussian systems. The existing extended risk-sensitive filter (ERSF) fails to take care of non-Gaussian problems or severe non-linearities. Recently, other variants of RSFs have been proposed for extending the range of applications of risk-sensitive techniques. The AGRSF has been formulated to act as a benchmark and aid in the validation of other RSFs. The algorithm uses a modified form of information state-based recursive relation and provides guidelines for the adaptive choice of grid points to improve the numerical efficiency. The developed filter has been applied to a single-dimensional non-linear poorly observable system and a non-linear two-dimensional bearing only tracking problem. The convergence of the algorithm has been shown by simulation. The estimation efficiency and computational load of AGRSF has been compared with other RSFs. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Coding mode determination using fuzzy reasoning in H.264 motion estimation

    Page(s): 242 - 250
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (380 KB)  

    Exhaustively searching over all possible partition modes using rate distortion comparison in H.264/AVC motion estimation to choose the best coding mode for each macroblock has much better coding efficiency than other existing standards. However, exhaustive searching has high computational complexity. This study analyses the statistics of coding mode distribution to determine the need of motion estimation for a current macroblock according to its previous corresponding macroblock information. A fast algorithm based on fuzzy reasoning with temporal and texture correlation of coding block information is proposed to reduce the computation time effectively. The fuzzy reasoning technique is used to determine the most appropriate mode quickly for motion estimation in H.264/AVC video coding. Simulation results show that the proposed algorithm has an encoding time 55.7-70- less than that of taken by searching for all coding modes exhaustively, while retaining the almost same coded picture quality and bit rate. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Class of digital integrators and differentiators

    Page(s): 251 - 260
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (647 KB)  

    A novel class of infinite impulse response digital integrators and differentiators is developed. A class of digital integrators is first derived from a class of numerical integration rules. A class of digital differentiators is then obtained by inverting the transfer functions of the obtained integrators and stabilising the resulting transfer functions together with magnitude compensation if necessary. Simulated annealing is applied to optimise some of the obtained integrators and differentiators. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Logic operation-based template matching algorithm for one-dimensional signals

    Page(s): 261 - 269
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (662 KB)  

    The normalised form of cross-correlation is a key technique used in template matching problems related to locating and recognising a signal pattern. Since it does not have a simple frequency-domain expression, the computation of the normalised cross-correlation (NCC) is performed in the spatial domain. However, the traditional NCC operation cannot cope with the growing speed requirements of recent time-critical applications. A new NCC-based template matching technique is presented in order to replace expensive multiplications with simpler logic operations. This algorithm is effective in cases where the signal-to-noise-ratio (SNR) is known or in those in which a direct SNR estimation is available. Although the algorithm requires SNR information, it encompasses a wide range of scaling factors and is robust to errors in SNR estimation. Experimental results show that the new template matching method can be used to determine the degree of similarity between test and reference signals with significant improvements over those of traditional methods. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.

Aims & Scope

IET Signal Processing publishes novel contributions in signal processing.

Full Aims & Scope

Meet Our Editors

IET Research Journals
iet_spr@theiet.org