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Statistical Signal and Array Processing, 1992. Conference Proceedings., IEEE Sixth SP Workshop on

Date 7-9 Oct. 1992

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Displaying Results 1 - 25 of 127
  • IEEE Sixth SP Workshop on Statistical Signal and Array Processing Conference Proceedings (Cat. No.92TH0410-1)

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    Freely Available from IEEE
  • Automatic frequency transition detection from an Lp normed model based Wigner distribution via the KLT

    Page(s): 122 - 127
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    Joint time-frequency signal representations, such as the Wigner-Ville distribution, have been applied to the analysis of signals containing transients. The authors estimate the Wigner distribution via robust linear predictive methods, followed by application of the Karhunen-Loeve transformation in order to capture frequency transients. Use of this technique may lead to reliable speech acoustic subword segmentation View full abstract»

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  • Interference suppression via orthogonal projections

    Page(s): 239 - 242
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    A technique for suppressing interference in phased array antennas, called the orthogonal projection algorithm, is described. Its performance is characterized theoretically and validated using Monte-Carlo simulations. An orthonormal basis for the interference subspace is calculated in the absence of target, and interference is suppressed by projection of the steering vector onto the orthogonal complement of the interference subspace. The mean output interference plus noise power is shown to be less than that for the sample matrix inversion algorithm for all finite sample sizes. Near convergence is attained with a number of interference snapshots that approximates the dimensionality of the interference subspace and is less than the number of elements View full abstract»

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  • Comparison of parabolic equation and adiabatic mode propagation models for matched-field processing in range-dependent environments

    Page(s): 378 - 383
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    Matched-field processing of underwater acoustic array data requires a knowledge of the environment and the use of a suitable propagation model from which field replicas can be computed. For range-dependent environment, parabolic equation or mode-based propagation modelling techniques may be used to provide these replicas. A comparison is presented for environments with sloping bottoms, using the order 3 Pade wide angle approximation for the parabolic equation to ensure precision. The numerical simulations involved generation of `measured' covariance matrices using PE fields; these were then matched with replicas computed using adiabatic modes. The results showed that for slopes up to 2°, the two techniques yield similar matches, but the adiabatic model provides up to a 100-fold speed advantage View full abstract»

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  • Quadratic time-frequency distributions: the new hyperbolic class and its intersection with the affine class

    Page(s): 26 - 29
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    The proposed new class of quadratic time-frequency distributions is based on the `hyperbolic time shift' and scale invariance properties that are important in the analysis of Doppler invariant signals used in bat and dolphin echolocation, and of `locally self-similar' signals used in fractals and fractional Brownian motion. The hyperbolic class can be characterized by 2-D kernels, and kernel constraints are derived for some desirable TFD properties. The Bertrand distribution and the Altes distribution are members of the hyperbolic class. The authors define a `localized' subclass and study the intersection between the affine class and the hyperbolic class View full abstract»

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  • Performance evaluation of certain ARMA models in power spectral density estimation

    Page(s): 424 - 427
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    For an autoregressive moving average (p, q) process the performance measures considered are the asymptotic variance of the spectral estimator and the resolution of two closely spaced sinusoids in white noise. Though the AR parameters are mainly responsible for good resolution, it is shown that proper MA parameters are also necessary in some methods. Cadzow's (Indirect) method and the singular value decomposition (SVD) method are considered for comparison. It is found that both methods have approximately the same variance of the PSD estimates in the neighborhood of the frequencies of interest. The SVD method yields a much lower model order than Cadzow's method in which the MA parameters have greater influence on resolution View full abstract»

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  • Signal resolution in low Doppler interference

    Page(s): 62 - 64
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    A new algorithm for estimating the arrival-times and Doppler-shifts of overlapping signal pulses is based on an extension of a procedure for high resolution time-delay estimation. This approach can exploit prior information from ocean acoustic propagation models about the interference structure View full abstract»

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  • Estimation of seismic wave parameters by nonlinear regression

    Page(s): 512 - 515
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    The authors model data by decaying complex sine waves. The good asymptotic properties of the estimates are verified. The application of the proposed algorithm to real seismic data is reported View full abstract»

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  • Non-parametric detection of a class of cyclo-stationary signals in stationary colored non-Gaussian noise using non-stationary higher order spectra

    Page(s): 202 - 205
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    This paper considers specifically the sum of coherently related narrowband signals of unknown frequencies and amplitudes. It employs the method of non-stationary higher order spectra (NSHOS) and develops a detection statistic based on the non-stationary bispectrum. Within the domain that excludes the stationary HOS, the NSHOS detection statistics as asymptotically zero for any type of stationary colored Gaussian or non-Gaussian noise, while within the domain of the stationary HOS they are zero for any type of stationary colored Gaussian or symmetric non-Gaussian noise. The detection performance is compared analytically and experimentally with the more traditional power spectrum method based on a periodogram detection statistic for Gaussian and nonGaussian noise View full abstract»

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  • Single sensor detection and classification of multiple sources by higher-order spectra

    Page(s): 181 - 184
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    A method to detect the number of nonGaussian sources is distinguished by its ability to perform detection with single sensor data, and is blind to Gaussian observation noise. After the detection procedure, the authors propose an algorithm for classification of sources employing a prior knowledge of their spectra. Simulation results indicate the performance of the algorithms View full abstract»

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  • Wideband spatial processing with wavelet transforms

    Page(s): 235 - 238
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    For a nearfield sensor array, wideband signals, and moving scatterers or sensors, beamforming may not be valid. The signals received at different sensors may no longer be delayed versions of one another. To localize wideband, nearfield, and/or moving sources, a wideband spatial processor is presented. Applicable to both active and passive processing, it relies on a new relation that expresses the wideband correlation receiver output as an affine convolution of two wavelet transforms; the wideband spreading function is convolved with an auto ambiguity function. This new expression is then deconvolved to obtain a high resolution estimate of the wideband spreading function View full abstract»

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  • Localization of intra-cerebral sources of electrical activity via linearly constrained minimum variance spatial filtering

    Page(s): 526 - 529
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    Measurements of electrical field potentials at the scalp are used to localize sources of electrical activity within the brain. Neuronal sources are modeled as current dipoles. The medum (brain, skull scalp) is linear so that the potential at the scalp is the superposition of the potentials from many active neurons. These properties are used to develop a mathematical model relating neural activity to the spatial distribution of the scalp potential. Linearly constrained minimum variance spatial filters are based on this model to estimate power as a function of position within the brain. Simulations illustrate the effectiveness of this approach for localizing an unknown number of sources View full abstract»

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  • Detection of multiple chirp signals based on a slice of the instantaneous higher-order moments

    Page(s): 30 - 33
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    A time-frequency (T-F) representation is defined which forces the contribution of the auto terms to appear at fixed positions on the T-F plane, while the cross terms appear at positions that vary depending on the particular slice. The choice of the moment slice is not unique as long as it satisfies certain conditions. Considering different moment slices yields different T-F representations. Summing the distributions corresponding to different moment slices, causes only the parts due to the auto terms to add up, since their positions depend only on the signal parameters View full abstract»

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  • Near-field plane wave generation using a minimum mean square error approach

    Page(s): 516 - 521
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    Holographic techniques are being developed to obtain near-field target strength measurements. This concept requires a projector array in the near-field to produce approximate plane waves in the volume occupied by the target. A method has been developed to generate complex weights that are applied to the elements in the projector array as amplitude shadings and time delays. This paper shows how a rectangular volume surrounding the target is a Hilbert space, and uses the classical projection theorem to obtain the optimum weights in the mean square error sense. Performance curves indicate the usefulness of this method View full abstract»

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  • A new iterative weighted norm minimization algorithm and its applications

    Page(s): 412 - 415
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    A general class of linear inverse problems in which the solutions are sparse and localized is considered. The proposed algorithm is a nonparametric approach that finds sparse and localized solutions without prior information on the constraints. Each step of the iterative procedure consists in solving a weighted least squares problem wherein the weighting matrix is determined by the solution from the previous iteration. Some properties of the algorithm along with its applications to problems in direction of arrival and spectrum estimation are presented View full abstract»

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  • Spectral-temporal decomposition of multicomponent signals

    Page(s): 206 - 209
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    The method is based on autoregressive modeling of the composite signal with an adaptive filter bank. An illustrative example is given for a speech signal View full abstract»

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  • Exploitation of higher-order cyclostationarity for weak-signal detection and time-delay estimation

    Page(s): 197 - 201
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    The cumulant theory of cyclostationary time-series is applied to several types of problems that arise in the area of signal interception and to the problem of estimating the relative time-delay of a heavily corrupted signal received at two locations. The theory characterizes the additive sine waves present in the output of nonlinear transformations of such time-series. The detection and time-delay estimation problems posed are difficult to solve because the signal is weak, the noise and interference are nonstationary and non-Gaussian, and the signal does not exhibit second-order cyclostationarity View full abstract»

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  • Decomposing the alpha rhythms: comparative performance evaluation of parametric bispectral algorithms for EEG

    Page(s): 522 - 525
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    The alpha wave is often harmonically related or coupled to frequencies in other EEG bands. Several autoregressive and eigenstructure-based bispectral algorithms have proven to be effective in the detection and estimation of alpha coupling. The authors extend the triple Kronecker product method of Swindlehurst and Kailath (1989) to estimation of biphases through a generalized eigenvalue approach. As a major concentration of significant bispectral peaks lie in the alpha-alpha coupling region, low model order can be used for accurate results with these methods View full abstract»

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  • A unitary transformation algorithm for wideband array processing

    Page(s): 300 - 303
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    The authors apply a two-sided transformation on the cross-correlation matrices of the array. It is shown that the two-sided correlation transformation (TCT) generates unbiased estimates of the directions of arrival regardless of the bandwidth of the signals. The capability of the method for resolving two closely spaced sources is compared with that of the coherent signal-subspace method. The resolution threshold for the new technique is smaller View full abstract»

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  • Detection of active linear FM sonar signals using the bispectrum

    Page(s): 177 - 180
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    The paper focuses on the problem of a returning active sonar signal masked by environmental background noise. According to theory, if the original signal is sufficiently non-Gaussian the bispectrum of the received signal-plus-noise will contain only information due to the signal, and the white Gaussian noise will be suppressed. A bispectrum detector has been developed which utilizes the a priori knowledge of the input active sonar signal by selecting regions of the bispectral domain where the magnitude exceeds a significance test threshold. The presence of the returning sonar signal in noise is then detected by measuring bispectral content in those regions. Linear FM (chirp) signals of several frequencies and sweep ranges are generated to simulate active sonar input, and corrupted by additive white Gaussian noise to produce various signal-to-noise ratios. Receiver Operating Characteristic curves for these signals demonstrate that this new detector provides gain over a bispectrum detection method previously presented in the literature. Detection results are presented for the original signals with additional multipath returns View full abstract»

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  • Signal processing applied to ultrasonic imaging

    Page(s): 225 - 228
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    This paper describes a noncoherent ultrasonic array used to form three-dimensional images of defects in metal. The problem developed in terms of deconvolution in multiple dimensions to improve resolution of images blurred by the measuring system and degraded by noise is reduced to solution of a linear equation of the form y=Hx, where H is called the imaging operator H may be separated into the Kronecker product of smaller banded-Toeplitz matrices VSP. This structure is used to develop an algorithm to solve for X using least squares and singular value decomposition View full abstract»

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  • Time-domain analysis of cross-correlation for multitarget/multipath time delay estimation

    Page(s): 485 - 488
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    This paper analyzes the effect of source separation on the estimation accuracy of the TDOA of multiple exponentially autocorrelated signals at two sensors in white noise. The analysis is carried out for uncorrelated signals (separate sources) as well as unity correlated signals, as in multipath propagation from a single source. The estimates are obtained from cross-correlations based on moving average samples of the noisy signals from the two sensors. The effect of the source separation on the degradation ratio is evaluated and compared with the optimal processor. The theoretical performance is verified through simulations for different SNRs and time-bandwidth products. Another advantage of the technique is that it avoids ambiguities in the cross-correlation View full abstract»

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  • The effect of normalization and quantization on long-term spectral integration

    Page(s): 229 - 234
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    It is found that performance loss due to the normalization is small, less than 0.2 dB for an example. The loss due to quantization depends on the number of bits used. For one-bit (two-level) quantization, the loss is approximately 1 dB. This can be reduced to less than 0.1 dB by the use of three bits (8 levels) in the quantizer View full abstract»

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  • Simultaneous CFAR detection and frequency estimation of a sinusoidal signal in noise

    Page(s): 78 - 81
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    A periodogram-based method is presented for simultaneously detecting and estimating an unknown sinusoidal signal. For additive white Gaussian noise, the scheme can achieve constant-false-alarm-rate detection and provide the maximum likelihood frequency estimate. For more general colored noise, the detection performance is derived approximately, and some numerical examples show that the scheme can nominally maintain the CFAR property, thus exhibiting some degree of robustness. It can be implemented easily by VLSI hardware and is suited to real-time applications View full abstract»

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  • Performance analysis of eigenstructure based DOA estimators employing conjugate symmetric beamformers

    Page(s): 384 - 387
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    If one employs conjugate centro-symmetric beamforming weight vectors in conjunction with a uniformly-spaced linear array, the noise eigenvectors in Beamspace MUSIC may be computed as the `smallest' eigenvectors of the real part of the beamspace sample covariance matrix. Through theoretical performance analysis and verification via Monte Carlo simulations, this paper shows that taking the real part offers significant performance gains in addition to computational gains, particularly for correlated sources View full abstract»

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