Online ISSN
1751-9683
Print ISSN
1751-9675
IET Signal Processing
Volume 5, Issue 1, February 2011
Volumes & issues:
Volume 5, Issue 1
February 2011
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- Author(s): X. Yang ; J. Min ; Y. Shi
- Source: IET Signal Processing, Volume 5, Issue 1, p. 1 –15
- DOI: 10.1049/iet-spr.2009.0294
- Type: Article
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In this study, the authors propose a novel construction frame of lifting scheme, which includes corresponding filters design, theory analysis and application. By applying the presented frame, they can realise the lifting scheme of biorthogonal wavelets with prediction and updating filters that are of arbitrary odd or even length. The prediction and updating filters are built based on Bernstein bases and generalised Bernstein bases, which possess transforming characters of symmetry, required vanishing moments and flatness of passbands of frequency response. The authors further obtain a new family of biorthogonal wavelets and the related library of biorthogonal symmetric waveforms. By using the parametric filters, they can achieve the best transform possible aiming at image compression by adjusting the coefficients of the filters. The authors explore the applicability of the proposed transforms for image compression with high compression rates, and the results of the experiments show that the performance is comparable with CDF9/7. - Author(s): J. Xu and J.X. Li
- Source: IET Signal Processing, Volume 5, Issue 1, p. 16 –26
- DOI: 10.1049/iet-spr.2009.0284
- Type: Article
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The problem of state estimation with quantised measurements is considered for general vector state-vector observation model in wireless sensor networks (WSNs), which broadens the scope of sign of innovations Kalman filtering (SOI-KF) and multiple-level quantised innovations Kalman filter (MLQIKF). Adhering to the limited power and bandwidth resources WSNs must operate with, this paper introduces a novel decentralised unscented Kalman filtering (UKF) estimators based on quantised measurement innovations. In the quantisation approach, the region of a measurement innovation is partitioned into L contiguous, non-overlapping intervals. After quantised, the measurement information is broadcasted by using a variable number of bytes coding method. A filtering algorithm for general vector state-vector observation case is developed based on the quantised measurement information. Performance analysis and Monte Carlo simulations reveal that under the same bandwidth constraint condition, the performance of novel quantised UKF tracker, indeed better than those of SOI-KF and MLQIKF in error covariance matrix (ECM) and root mean-square error (RMSE) and almost identical to these of an UKF based on analogue-amplitude observations. - Author(s): M. Saravi and M.H. Kahaei
- Source: IET Signal Processing, Volume 5, Issue 1, p. 27 –32
- DOI: 10.1049/iet-spr.2009.0121
- Type: Article
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This study deals with maximising the sensing coverage in the wireless mobile sensor network. The authors present Distance Constrained Deployment (DCD) and Adaptive Distance Constrained Deployment (ADCD) algorithms to deploy sensors for the maximum coverage with the minimum average moving distance. The ADCD algorithm is applied for unplanned deployment of sensors in bounded areas with obstacles. The simulation results show that the ADCD algorithm achieves a smaller average moving distance compared to the existing algorithms and thus increases the sensor battery life. - Author(s): R.C. de Lamare and R. Sampaio-Neto
- Source: IET Signal Processing, Volume 5, Issue 1, p. 33 –39
- DOI: 10.1049/iet-spr.2008.0105
- Type: Article
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A blind space–time joint channel and direction of arrival (DoA) estimation method is proposed for DS-CDMA systems. The new method employs a linear antenna array and requires only the signature sequence and timing of the desired user to blindly estimate the channel and the DoA parameters. Two blind algorithms that exploit antenna arrays are also proposed for enhancing the channel estimates. Simulations show the improvements for channel estimation of the method and algorithms over existing techniques and the accuracy achieved for DoA computation as compared to recently reported DoA estimators for DS-CDMA systems. - Author(s): D.B.H. Tay
- Source: IET Signal Processing, Volume 5, Issue 1, p. 40 –48
- DOI: 10.1049/iet-spr.2009.0147
- Type: Article
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The design of halfband filters for orthonormal wavelet with a prescribed number of vanishing moment and prescribed ripple amplitudes is described. The technique is an extension of the zero-pinning (ZP) technique and is called ripple-pinning (RP). In ZP, the positions of stopband minima (of a Bernstein polynomial) are specified explicitly and the stopband maxima (position and amplitude) depend implicitly on the minima. In RP, the amplitude of the ripples is explicitly specified and this leads to a set of non-linear (polynomial) equations with the position of both the minima and maxima as unknowns. An iterative algorithm is proposed to solve the equations and design examples will be presented. Two variations of the RP technique, which allow for the transition band sharpness to be explicitly specified, are also presented. - Author(s): J.M. Blackaby ; B.D. Rigling ; P.M. Hanna
- Source: IET Signal Processing, Volume 5, Issue 1, p. 49 –57
- DOI: 10.1049/iet-spr.2009.0006
- Type: Article
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This study discusses the fusion of radar frequency (RF) data and electro-optical (EO) data for tracking and characterisation of dismounts (i.e. humans). Each of these sensor modalities provides unique information about the location, structure and movement of a dismount. The person's location is tracked on the 2D ground plane using RF data for range measurements and EO data for angle measurements. Using this information, measurements are made on the structure and dynamic motion (gait) of the person. An imaging approach is used to create spatio-temporal activity maps along with a three-dimensional reconstruction of the dismount. - Author(s): G. Deng
- Source: IET Signal Processing, Volume 5, Issue 1, p. 58 –65
- DOI: 10.1049/iet-spr.2009.0236
- Type: Article
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The authors study an iterative algorithm for learning a linear Gaussian observation model with an exponential power scale mixture prior (EPSM). This is a generalisation of previous study based on the Gaussian scale mixture prior. The authors use the principle of majorisation minimisation to derive the general iterative algorithm which is related to a reweighted lp-minimisation algorithm. The authors then show that the Gaussian and Laplacian scale mixtures are two special cases of the EPSM and the corresponding learning algorithms are related to the reweighted l2-and l1-minimisation algorithms, respectively. The authors also study a particular case of the EPSM which is a Pareto distribution and discuss Bayesian methods for parameter estimation. - Author(s): X.H. Zhang ; L.F. Liu ; J.Y. Cai ; Y.W. Yang
- Source: IET Signal Processing, Volume 5, Issue 1, p. 66 –74
- DOI: 10.1049/iet-spr.2010.0029
- Type: Article
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In this correspondence, a linear transform called polynomial to Hermite polynomial transform (PHPT) is proposed, and the PHPT-based method for parameter estimation of polynomial phase signals (PPS) embedded in additive white Gaussian noise is addressed. The first advantage is the low computational complexity. If the number of samples is N, the computational complexity is O(3N log2N) regardless of the order or the component number of PPS. The second advantage is that there is no non-linear operation in PHPT algorithm; therefore there is no cross-term interference in between the various components. In addition, the proposed method can well process the PPS with unknown order phase. Simulations illustrate that the proposed algorithm is more effective as compared with the existing ones. - Author(s): W. Kong ; Y. Lei ; Y. Lei ; X. Ni
- Source: IET Signal Processing, Volume 5, Issue 1, p. 75 –80
- DOI: 10.1049/iet-spr.2009.0263
- Type: Article
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An adaptive fusion technique based on non-subsampled contourlet transform (NSCT) and intensity–hue–saturation (IHS) transform is presented. First, the grey-scale visible light image is colourised by utilising a reference image, and then, the values of components I, H and S can be obtained via IHS transform, which can separate intensity information from spectrum information of the image. Second, multi-scale and multi-directional decompositions of the infrared image and the component I of the grey-scale visible light image are performed by NSCT. By adopting certain fusion rules, the low-frequency and high-frequency components of the fused image can be achieved. Third, being the component I of the final fused image, the grey-scale fused image can be gained by the use of inverse NSCT. Finally, the red–green–blue colourised fused image is reconstructed by the inverse IHS. Experimental results show that the technique is effective. - Author(s): S. Qin ; Q. Wan ; Z.-X. Chen ; A.-M. Huang
- Source: IET Signal Processing, Volume 5, Issue 1, p. 81 –84
- DOI: 10.1049/iet-spr.2009.0296
- Type: Article
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81
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The problem of locating and tracking a mobile station (MS) in which real-time computation is needed has received considerable attentions. In this letter, a fast and computationally simple subspace-based algorithm for mobile positioning with the use of time-of-arrival (TOA) measurements of three base stations (BSs) is derived and analysed. Since the Lagrange multiplier is introduced to avoid eigendecomposition of multidimensional similarity matrix, the proposed algorithm offers very competitive performance at low computational complexity. - Author(s): L. Kong ; G. Cui ; X. Yang ; J. Yang
- Source: IET Signal Processing, Volume 5, Issue 1, p. 85 –96
- DOI: 10.1049/iet-spr.2009.0271
- Type: Article
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In high–resolution radars or at low gazing angles, the clutter is more satisfied in the compound-Gaussian model. Meanwhile, the polarisation diversity can be exploited to enhance the detection performance. Motivated by extending the detection problem of multiple-input multiple-output radar to such cases, this study mainly addresses the adaptive detectors design with an unknown covariance matrix based on Rao and Wald criterions. The two-step design strategy is adopted. Three estimation strategies of covariance with secondary data, such as sampled covariance matrix (SCM), normalised sampled covariance matrix (NSCM) and fixed point estimation (FPE) matrix, are introduced to make derived receivers fully adaptive. A thorough performance assessment is given by several numerical examples, the results of which show that Rao and Wald tests can provide good detection performance in even spikier clutter, and the polarimetric diversity can also be exploited to improve the detection performance. Meanwhile, the FPE strategy is more suitable to implement the adaptive detection algorithms, and the adaptive loss is completely acceptable in practical applications. - Author(s): N. Madhu and R. Martin
- Source: IET Signal Processing, Volume 5, Issue 1, p. 97 –103
- DOI: 10.1049/iet-spr.2009.0164
- Type: Article
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97
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This study details a simple method for the detection of sensor degradation in microphone arrays and equalisation of the microphone gains. The described method is online in nature and based upon the long-term power spectra of the microphone signals of each array. The close proximity of the microphones within an array is essential for the application of the proposed detection and calibration method. The approach is tested on three sample degradation scenarios: complete sensor failure, non-linearity in the input and parasitic harmonic injection. While these scenarios are by no means exhaustive, they represent the most typical degradations in many applications. The results indicate that the developed approach is capable of detecting such failures. Further, the calibration factors computed using the proposed approach are similar to that obtained by established methods. - Author(s): G. Wang ; Q. Chen ; Z. Ren
- Source: IET Signal Processing, Volume 5, Issue 1, p. 104 –112
- DOI: 10.1049/iet-spr.2008.0071
- Type: Article
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104
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A theory to analyse linear time-varying (LTV) discrete-time systems from the point of digital signal processing of view is established here. The LTV discrete-time system is changing with time slowly in comparison with the sampling frequency of the input signal is supposed. Three models were set up to simulate and analyse the LTV system. Models 1 and 2 can be used to design and analyse the LTV system, while the filter bank representation relates the LTV system with the time-varying filter bank. Based on the established models, the input–output relationship of a time-varying system in the frequency-domain was analysed in detail.
Parametrisation construction frame of lifting scheme
State estimation with quantised sensor information in wireless sensor networks
Adaptive Distance Constrained Deployment algorithm for mobile sensor networks
Blind space–time joint channel and direction of arrival estimation for DS-CDMA systems
Design of halfband filters for orthonormal wavelets using ripple-pinning
Simultaneous radar frequency/electro-optical tracking and characterisation of dismounts
Iterative algorithms for learning a linear Gaussian observation model with an exponential power scale mixture prior
New method for parameter estimation of polynomial phase signals
Fusion technique for grey-scale visible light and infrared images based on non-subsampled contourlet transform and intensity–hue–saturation transform
Fast multidimensional scaling analysis for mobile positioning
Rao and Wald tests design of polarimetric multiple-input multiple-output radar in compound-Gaussian clutter
Low-complexity, robust algorithm for sensor anomaly detection and self-calibration of microphone arrays
Modelling of time-varying discrete-time systems
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