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Signal Processing, IEEE Transactions on

Issue 4 • Date April 2001

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Displaying Results 1 - 22 of 22
  • On the application of the global matched filter to DOA estimation with uniform circular arrays

    Publication Year: 2001 , Page(s): 702 - 709
    Cited by:  Papers (54)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (150 KB) |  | HTML iconHTML  

    The problem of estimating the direction of arrivals (DOA) of narrowband sources impinging on a uniform circular array is considered. We present a method that uses as input the values of a small number of uniformly spaced beams and apply a model-fitting approach taking into account the statistical properties of the beams. The approach, which is called the "global matched filter" fits simultaneously to the observations all the elements needed to explain them. It chooses, among all the representations satisfying a constraint with a sensible physical interpretation, the one with minimal energy. The method drastically improves upon the conventional beamformer and has a performance comparable with the best high-resolution (HR) techniques. It further applies when the number of sources exceeds the number of sensors: a situation that cannot be handled by standard HR techniques. View full abstract»

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  • Comments on "DCT algorithms for composite sequence lengths"

    Publication Year: 2001 , Page(s): 909
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (17 KB) |  | HTML iconHTML  

    First Page of the Article
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  • Blind source-separation using second-order cyclostationary statistics

    Publication Year: 2001 , Page(s): 694 - 701
    Cited by:  Papers (46)  |  Patents (6)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (204 KB) |  | HTML iconHTML  

    This paper studies the blind source separation (BSS) problem with the assumption that the source signals are cyclostationary. Identifiability and separability criteria based on second-order cyclostationary statistics (SOCS) alone are derived. The identifiability condition is used to define an appropriate contrast function. An iterative algorithm (ATH2) is derived to minimize this contrast function. This algorithm separates the sources even when they do not have distinct cycle frequencies View full abstract»

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  • Short-time Fourier transform receiver for nonstationary interference excision in direct sequence spread spectrum communications

    Publication Year: 2001 , Page(s): 851 - 863
    Cited by:  Papers (23)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (324 KB) |  | HTML iconHTML  

    A new adaptive excision approach for nonstationary interference excision in direct sequence spread spectrum (DS/SS) communications is introduced. The proposed excision approach is based on the attractive localization properties of the impulse responses of the multiple pole filters. These impulse responses have Gaussian-like shapes and decrease in bandwidth with higher pole multiplicities. When used as data windows, they field a large class of computationally efficient short-time Fourier transforms (STFTs). Localization measures can be applied to determine the optimum window that maximally concentrates the interference in the time-frequency (t.-f.) domain. Interference mitigation is then achieved by applying a binary excision mask to the corresponding STFT for each data bit. We show that the proposed interference excision method permits both data-dependent windowing and time-varying filtering and leads to improved BER performance of the DS/SS system. The paper also derives the general optimum receiver implementing the STFT-based interference excision system View full abstract»

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  • Adaptive lattice IIR filtering revisited: convergence issues and new algorithms with improved stability properties

    Publication Year: 2001 , Page(s): 811 - 821
    Cited by:  Papers (4)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (240 KB) |  | HTML iconHTML  

    Several algorithms for adaptive IIR filters parameterized in lattice form can be found in the literature. The salient feature of these structures when compared with the direct form is that ensuring stability is extremely easy. On the other hand, while computing the gradient signals that drive the direct form update algorithms is straightforward, it is not so for the lattice algorithms. This has led to simplified lattice algorithms using gradient approximations. Although, in general, these simplified schemes present the same stationary points as the original algorithms, whether this is also true for convergent points has remained an open problem. This also applies to nongradient-based lattice algorithms such as hyperstability based and the Steiglitz-McBride algorithms. Here, we answer this question in the negative, by showing that for several adaptive lattice algorithms, there exist settings in which the stationary point corresponding to identification of the unknown system is not convergent. In addition, new lattice algorithms with properties are derived. They are based on the cascade lattice structure, which allows the derivation of sufficient conditions for local stability View full abstract»

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  • A new class of gradient adaptive step-size LMS algorithms

    Publication Year: 2001 , Page(s): 805 - 810
    Cited by:  Papers (59)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (180 KB) |  | HTML iconHTML  

    The gradient adaptive step-size least-mean-square (LMS) algorithms [an important family of variable step-size LMS (VSLMS) algorithms] are revisited. We propose a simplification to a class of the studied algorithms and show that this leads to a new class of VSLMS algorithms with reduced complexity but with no observable loss in performance View full abstract»

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  • A new normalized relatively stable lattice structure

    Publication Year: 2001 , Page(s): 738 - 746
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (208 KB) |  | HTML iconHTML  

    This paper proposes a new lattice filter structure that has the following properties. When the filter is linear time invariant (LTI), it is equivalent to the celebrated Gray-Markel lattice. When the lattice parameters vary with time, it sustains arbitrary rates of time variations without sacrificing a prescribed degree of stability, provided that the lattice coefficients are magnitude bounded in a region where all LTI lattices have the same degree of stability. We also show that the resulting LTV lattice obeys an energy contraction condition. This structure thus generalizes the normalized Gray-Markel lattice, which has similar properties but only with respect to stability as opposed to relative stability View full abstract»

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  • Bounds on bearing and symbol estimation with side information

    Publication Year: 2001 , Page(s): 822 - 834
    Cited by:  Papers (21)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (344 KB) |  | HTML iconHTML  

    We develop Cramer-Rao bounds (CRBs) for bearing, symbol, and channel estimation of communications signals in flat-fading channels. We do this using the constrained CRB formulation of German and Hero (1990), and Stoica and Ng (see IEEE Signal Processing Lett., vol.5, p.177-79, 1998), with the unknown parameters treated as deterministic constants. The equality constraints may be combined arbitrarily, e.g., we may develop CRBs for bearing estimation of constant modulus (CM) signals where a subset of the symbols are known (semi-blind, CM case). The results establish the value of side information in a large variety of communications scenarios. We focus on the CM and semi-blind properties and develop closed-form CRBs for these cases. Examples are presented indicating the relative value of the training and CIM property. These show the significant amount of signal processing information provided under these two conditions. In addition, we consider the performance of the maximum-likelihood beamformer for the semi-blind case, assuming the bearings are known. This semi-blind beamformer achieves the appropriate (constrained) CRB with finite data at finite SNR. Analysis also reveals that in a semi-blind scenario with two closely spaced sources, ten or more training symbols are sufficient to achieve the asymptotic training regime. Together with previous results on angle estimation for known sources, these results indicate that relatively few training samples enable both angle estimation and closely spaced co-channel source separation that approaches the CRB with finite data and finite SNR View full abstract»

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  • Hybrid linear/quadratic time-frequency attributes

    Publication Year: 2001 , Page(s): 760 - 766
    Cited by:  Papers (4)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (200 KB) |  | HTML iconHTML  

    We present an efficient method for robustly calculating time-frequency attributes of a signal, including instantaneous mean frequency, bandwidth, kurtosis, and other moments. Most current attribute estimation techniques involve a costly intermediate step of computing a (highly oversampled) two-dimensonal (2-D) quadratic time-frequency representation (TFR), which is then collapsed to the one-dimensonal (1-D) attribute. Using the principles of hybrid linear/quadratic time-frequency analysis (time-frequency distribution series), we propose computing attributes as nonlinear combinations of the (slightly oversampled) linear Gabor coefficients of the signal. The method is both computationally efficient and accurate; it performs as well as the best techniques based on adaptive TFRs. To illustrate, we calculate an attribute of a seismic cross section View full abstract»

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  • Frequency estimation in the presence of Doppler spread: performance analysis

    Publication Year: 2001 , Page(s): 777 - 789
    Cited by:  Papers (24)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (388 KB) |  | HTML iconHTML  

    We are concerned with the estimation of the frequency of a complex sinusoid that has been corrupted by complex-valued multiplicative and additive noise. This problem is important in many applications including array processing in the case of spatially distributed sources and synchronization in the context of time-selective channels. The multiplicative noise smears the spectral line due to the sinusoid. This smearing, which is often called Doppler spreading, may significantly degrade the estimation accuracy. The goal of this paper is to analytically assess this degradation. The finite-sample Cramer-Rao bounds (CRBs) are derived, and closed-form expressions are given for the large-sample CRB. The latter gives insights into the effective coherent and noncoherent SNRs for frequency estimation. We then analyze the accuracy of frequency estimators that are based on the angles of the sample covariances. Simulations results are presented to illustrate the theoretical results View full abstract»

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  • Two-dimensional affine generalized fractional Fourier transform

    Publication Year: 2001 , Page(s): 878 - 897
    Cited by:  Papers (10)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (668 KB) |  | HTML iconHTML  

    As the one-dimensional (1-D) Fourier transform can be extended into the 1-D fractional Fourier transform (FRFT), we can also generalize the two-dimensional (2-D) Fourier transform. Sahin et al. (see Appl. Opt., vol.37, no. 11, p.2130-41, 1998) have generalized the 2-D Fourier transform into the 2-D separable FRFT (which replaces each variable 1-D Fourier transform by the 1-D FRFT, respectively) and the 2-D separable canonical transform (further replaces FRFT by the canonical transform). Sahin et al., (see Appl. Opt., vol.31, no.23, p.5444-53, 1998), have also generalized it into the 2-D unseparable FRFT with four parameters. In this paper, we introduce the 1-D affine generalized fractional Fourier transform (AGFFT). It has even further extended the 2-D transforms described above. It is unseparable, and has, in total, ten degrees of freedom. We show that the 2-D AGFFT has many wonderful properties, such as the relations with the Wigner distribution, shifting-modulation operation, and the differentiation-multiplication operation. Although the 2-D AGFFT form seems very complex, in fact, the complexity of the implementation will not be more than the implementation of the 2-D separable FRFT. Besides, we also show that the 2-D AGFFT extends many of the applications for the 1-D FRFT, such as the filter design, optical system analysis, image processing, and pattern recognition and will be a very useful tool for 2-D signal processing View full abstract»

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  • TST-MUSIC for joint DOA-delay estimation

    Publication Year: 2001 , Page(s): 721 - 729
    Cited by:  Papers (44)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (204 KB) |  | HTML iconHTML  

    A multiple signal classification (MUSIC)-based approach known as the time-space-time MUSIC (TST-MUSIC) is proposed to jointly estimate the directions of arrival (DOAs) and the propagation delays of a wireless multiray channel. The MUSIC algorithm for the DOA estimation is referred to as the spatial-MUSIC (S-MUSIC) algorithm. On the other hand, the temporal-MUSIC (T-MUSIC), which estimates the propagation delays, is introduced as well. Making use of the space-time characteristics of the multiray channel, the proposed algorithm-in a tree structure-combines the techniques of temporal filtering and of spatial beamforming with three one-dimensional (1-D) MUSIC algorithms, i.e., one S-MUSIC and two T-MUSIC algorithms. The incoming rays are thus grouped, isolated, and estimated. At the same time, the pairing of the estimated DOAs and delays is automatically determined. Furthermore, the proposed approach can resolve the incoming rays with very close DOAs or delays, and the number of antennas required by the TST-MUSIC algorithm can be made less than that of the incoming rays View full abstract»

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  • Robust filtering for a class of stochastic uncertain nonlinear time-delay systems via exponential state estimation

    Publication Year: 2001 , Page(s): 794 - 804
    Cited by:  Papers (46)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (272 KB) |  | HTML iconHTML  

    We investigate the robust filter design problem for a class of nonlinear time-delay stochastic systems. The system under study involves stochastics, unknown state time-delay, parameter uncertainties, and unknown nonlinear disturbances, which are all often encountered in practice and the sources of instability. The aim of this problem is to design a linear, delayless, uncertainty-independent state estimator such that for all admissible uncertainties as well as nonlinear disturbances, the dynamics of the estimation error is stochastically exponentially stable in the mean square, independent of the time delay. Sufficient conditions are proposed to guarantee the existence of desired robust exponential filters, which are derived in terms of the solutions to algebraic Riccati inequalities. The developed theory is illustrated by numerical simulation View full abstract»

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  • Optimum diversity detection over fading dispersive channels with non-Gaussian noise

    Publication Year: 2001 , Page(s): 767 - 776
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (216 KB) |  | HTML iconHTML  

    We consider the problem of M-ary signal detection over a single-input-multiple-output (SIMO) channel affected by frequency-dispersive Rayleigh-distributed fading and corrupted by additive non-Gaussian noise, modeled as a spherically invariant random process. We derive both the optimum detection structure and a suboptimal, reduced-complexity receiver, based on the low-energy-coherence approach. Interestingly, both detection structures are canonical, i.e., they are independent of the actual noise statistics. We also carry out a performance analysis of both receivers, with reference to the case that the channel is affected by a frequency-selective fading and for a binary frequency-shift-keying signaling format. The results obtained through both a Chernoff-bounding technique and Monte Carlo simulations reveal that the adoption of diversity also represents a suitable means to restore performance in the presence of dispersive fading and impulsive non-Gaussian noise. Interestingly, it is also shown that the suboptimal receiver incurs a limited loss with respect to the optimum (unrealizable) receiving structure View full abstract»

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  • Subspace analysis of spatial time-frequency distribution matrices

    Publication Year: 2001 , Page(s): 747 - 759
    Cited by:  Papers (44)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (368 KB) |  | HTML iconHTML  

    Spatial time-frequency distributions (STFDs) have been previously introduced as the natural means to deal with source signals that are localizable in the time-frequency domain. Previous work in the area has not provided the eigenanalysis of STFD matrices, which is key to understanding their role in solving direction finding and blind source separation problems in multisensor array receivers. The aim of this paper is to examine the eigenstructure of the STFD matrices. We develop the analysis and statistical properties of the subspace estimates based on STFDs for frequency modulated (FM) sources. It is shown that improved estimates are achieved by constructing the subspaces from the time-frequency signatures of the signal arrivals rather than from the data covariance matrices, which are commonly used in conventional subspace estimation methods. This improvement is evident in a low signal-to-noise ratio (SNR) environment and in the cases of closely spaced sources. The paper considers the MUSIC technique to demonstrate the advantages of STFDs and uses it as grounds for comparison between time-frequency and conventional subspace estimates View full abstract»

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  • Simple and accurate direction of arrival estimator in the case of imperfect spatial coherence

    Publication Year: 2001 , Page(s): 730 - 737
    Cited by:  Papers (18)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (220 KB) |  | HTML iconHTML  

    We consider the direction-finding problem in the imperfect spatial coherence case, i.e., when the amplitude and phase of the wavefront vary randomly along the array aperture. This phenomenon can originate from propagation through an inhomogeneous medium. It is also encountered in the case of spatially dispersed sources. We derive a fast and accurate estimator for the direction of arrival of a single source using a uniform linear array (ULA) of sensors. The estimator is based on a reduced statistic obtained from the subdiagonals of the covariance matrix of the array output. It only entails computing the Fourier transform of an (m-1)-length sequence where m is the number of array sensors. A theoretical analysis is carried out, and an expression for the asymptotic variance of the estimator is derived. Numerical simulations validate the theoretical results and show that the estimator has an accuracy very close to the Cramer-Rao bound View full abstract»

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  • Two-dimensional frequency-domain blind system identification using higher order statistics with application to texture synthesis

    Publication Year: 2001 , Page(s): 864 - 877
    Cited by:  Papers (4)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (500 KB) |  | HTML iconHTML  

    In this paper, Shalvi and Weinstein's (1993) super-exponential (SE) algorithm using higher order statistics for blind deconvolution of one-dimensional (1-D) linear time-invariant systems is extended to a two-dimensional (2-D) SE algorithm. Then, a 2-D frequency-domain blind system identification (BSI) algorithm for 2-D linear shift-invariant (LSI) systems using the computationally efficient 2-D SE algorithm and the 2-D linear prediction error filter is proposed. In addition to the LSI system estimate, the proposed BSI algorithm also provides a minimum mean square error (MMSE) equalizer estimate and an MMSE signal enhancement filter estimate. Then, a texture synthesis method (TSM) using the proposed BSI algorithm is presented. Some simulation results to support the efficacy of the proposed BSI algorithm and some experimental results to support the efficacy of the proposed TSM are presented. Finally, some conclusions are drawn View full abstract»

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  • Conditional maximum likelihood timing recovery: estimators and bounds

    Publication Year: 2001 , Page(s): 835 - 850
    Cited by:  Papers (27)  |  Patents (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (480 KB) |  | HTML iconHTML  

    This paper is concerned with the derivation of new estimators and performance bounds for the problem of timing estimation of (linearly) digitally modulated signals. The conditional maximum likelihood (CML) method is adopted, in contrast to the classical low-SNR unconditional ML (UML) formulation that is systematically applied in the literature for the derivation of non-data-aided (NDA) timing-error-detectors (TEDs). A new CML TED is derived and proved to be self-noise free, in contrast to the conventional low-SNR-UML TED. In addition, the paper provides a derivation of the conditional Cramer-Rao bound (CRBc), which is higher (less optimistic) than the modified CRB (MCRB) [which is only reached by decision-directed (DD) methods]. It is shown that the CRB, is a lower bound on the asymptotic statistical accuracy of the set of consistent estimators that are quadratic with respect to the received signal. Although the obtained bound is not general, it applies to most NDA synchronizers proposed in the literature. A closed-form expression of the conditional CRB is obtained, and numerical results confirm that the CML TED attains the new bound for moderate to high Es/N o View full abstract»

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  • On orthonormal Muntz-Laguerre filters

    Publication Year: 2001 , Page(s): 790 - 793
    Cited by:  Papers (8)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (116 KB) |  | HTML iconHTML  

    When the Muntz-Szasz (1953) condition holds, the Muntz-Laguerre filters form a uniformly bounded orthonormal basis in Hardy space. This has consequences in terms of optimal pole-cancellation schemes, and it also allows for a generalization of Lerch's theorem View full abstract»

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  • On the automated recognition of seriously distorted musical recordings

    Publication Year: 2001 , Page(s): 898 - 908
    Cited by:  Papers (16)  |  Patents (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (208 KB) |  | HTML iconHTML  

    A new methodology is presented for the automated recognition-identification of musical recordings that have suffered from a high degree of playing speed and frequency band distortion. The procedure of recognition is essentially based on the comparison between an unknown musical recording and a set of model ones, according to some predefined specific characteristics of the signals. In order to extract these characteristics from a musical recording, novel feature extraction algorithms are employed. This procedure is applied to the whole set of model musical recordings, thus creating a model characteristic database. Each time we want an unknown musical recording to be identified, the same procedure is applied to it, and subsequently, the derived characteristics are compared with the database contents via an introduced set of criteria. The proposed methodology led to the development of a system whose performance was extensively tested with various types of broadcasted musical recordings. The system performed successful recognition for the 94% of the tested recordings. It should be noted that the presented system is parallelizable and can operate in real time View full abstract»

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  • Cepstral coefficients, covariance lags, and pole-zero models for finite data strings

    Publication Year: 2001 , Page(s): 677 - 693
    Cited by:  Papers (15)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (416 KB)  

    One of the most widely used methods of spectral estimation in signal and speech processing is linear predictive coding (LPC), LPC has some attractive features, which account for its popularity, including the properties that the resulting modeling filter (i) matches a finite window of n+1 covariance lags, (ii) is rational of degree at most n, and (iii) has stable zeros and poles. The only limiting factor of this methodology is that the modeling filter is “all-pole,” i.e., an autoregressive (AR) model. In this paper, we present a systematic description of all autoregressive moving-average (ARMA) models of processes that have properties (i)-(iii) in the context of cepstral analysis and homomorphic filtering. We show that each such an ARMA model determines and is completely determined by its finite windows of cepstral coefficients and covariance lags. We show that these nth-order windows form local coordinates for all ARMA models of degree n and that the pole-zero model can be determined from the windows as the unique minimum of a convex objective function. We refine this optimization method by first noting that the maximum entropy design of an LPC filter is obtained by maximizing the zeroth cepstral coefficient, subject to the constraint (i). More generally, we modify this scheme to a more well-posed optimization problem where the covariance data enter as a constraint and the linear weights of the cepstral coefficients are “positive”-in a sense that a certain pseudo-polynomial is positive-rather succinctly generalizing the maximum entropy method. This new problem is a homomorphic filter generalization of the maximum entropy method. providing a procedure for the design of any stable, minimum-phase modeling filter of degree less or equal to n that interpolates the given covariance window. We present an algorithm for realizing these filters in a lattice-ladder form, given the covariance window and the moving average part of the model, While we also show how to determine the moving average part using cepstral smoothing, one can make use of any good a priori estimate for the system zeros to initialize the algorithm. We conclude the paper with an example of this method, incorporating an example from the literature on ARMA modeling View full abstract»

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  • Linear prediction approach to direction estimation of cyclostationary signals in multipath environment

    Publication Year: 2001 , Page(s): 710 - 720
    Cited by:  Papers (9)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (316 KB) |  | HTML iconHTML  

    We investigate the estimation of the directions-of-arrival (DOA) of closely spaced narrowband cyclostationary signals in the presence of multipath propagation. By exploiting the spatial and temporal properties of most communication signals, we propose a new cyclic forward-backward linear prediction (FBLP) approach for coherent signals impinging on a uniform linear array (ULA). In the proposed algorithm, the evaluation of the cyclic array covariance matrix is avoided, and the difficulty of choosing the optimal time lag parameter is alleviated. As a result, the proposed approach has two advantages: (1) the computational load is relatively reduced, and (2) the robustness of estimation is significantly improved. The performance of the proposed approach is confirmed through numerical examples, and it is shown that this approach is superior in resolving the closely spaced coherent signals with a small length of array data and at relatively low signal-to-noise ratio (SNR) View full abstract»

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Aims & Scope

IEEE Transactions on Signal Processing covers novel theory, algorithms, performance analyses and applications of techniques for the processing, understanding, learning, retrieval, mining, and extraction of information from signals

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Editor-in-Chief
Sergios Theodoridis
University of Athens