A. Hanssen

Universitetet i Tromsø, Tromsø, Troms Fylke, Norway

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Publications (67)57.17 Total impact

  • Charlotte Sanchis, Alfred Hanssen
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    ABSTRACT: Stacking is a common technique to improve the signal-to-noise ratio (S/N) and the imaging quality of seismic data. Conventional stacking that averages equally a collection of normal moveout corrected or migrated shot gathers with a common reflection point is not always satisfactory. Instead, we propose a novel time-dependent weighted average stacking method that utilizes local correlation between each individual trace and a chosen reference trace as a measure of weight and a new weight normalization scheme that ensures meaningful amplitudes of the output. Three different reference traces have been proposed. These are based on conventional stacking, S/N estimation, and Kalman filtering. The outputs of the enhanced stacking methods, as well as their reference traces, were compared on both synthetic data and real marine migrated subsalt data. We conclude that both S/N estimation and Kalman reference stacking methods as well as the output of the enhanced stacking method yield consistently better results th
    Geophysics 05/2011; 76:V33-V45. · 1.72 Impact Factor
  • Charlotte Sanchis, Alfred Hanssen
    Geophysics 01/2011; 76(6):139-. · 1.72 Impact Factor
  • Charlotte Sanchis, Alfred Hanssen
    Geophysics 01/2011; 76(6):151-. · 1.72 Impact Factor
  • Yngve Birkelund, Alfred Hanssen
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    ABSTRACT: The classical bispectrum based tests for linearity of time series are based on Gaussian asymptotics and a suboptimal smoothing in the bispectral domain. We show that the resulting classical tests may lead to vastly incorrect significance levels for non-Gaussian time series. This implies that a non-Gaussian linear time series may incorrectly be classified as non-linear. The purpose of this paper is to propose simple yet accurate tests for Gaussianity and linearity. The improved tests are derived through: (1) an optimal hexagonal smoothing in the bispectral domain, (2) the construction of simple and intuitive bispectrum based test statistics, and (3) determination of correct significance levels through a new skewness preserving scheme for linear surrogate data. The superiority of the proposed tests is demonstrated through extensive Monte Carlo simulations using relevant synthetic data.
    Signal Processing. 01/2009;
  • H. Hindberg, A. Hanssen, S.C. Olhede
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    ABSTRACT: In this paper we propose a new method for estimating the ambiguity function (AF) of a random process with limited spreading support. The observed process is modelled as the aggregation of a non-stationary signal of interest and noise. As the AF has limited spreading, thresholding is a suitable estimation procedure. Some key stochastic properties of the empirical ambiguity function are derived to obtain a suitable threshold. Based on a median absolute deviation estimator for the variance, we derive a suitable threshold, which forms the basis for our proposed estimator. The estimator is tested on both artificial and real signals, and our results demonstrate a remarkably high resolution and reduced variance.
    Acoustics, Speech and Signal Processing, 2008. ICASSP 2008. IEEE International Conference on; 05/2008
  • T.O. Saebo, R.E. Hansen, A. Hanssen
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    ABSTRACT: The relative height of the seafloor can be estimated by using two vertically displaced receivers. In this paper, we propose techniques to improve the accuracy of the estimated height. Our results are based on the use of synthetic aperture sonar (SAS) imaging, which implies coherent addition of complex images acquired from a moving platform. The SAS processing improves the along-track (or azimuth) resolution, as well as the signal-to-noise ratio (SNR), which in turn improves the estimated height accuracy. We show that the shift of the effective center frequency induced by coherent, frequency-dependent scattering affect the time-delay estimates from complex cross correlations, and we propose a correction technique for broadband signals with uneven magnitude spectra. To reduce the effect of geometrical decorrelation and increase the coherence between the images, we beamform the sonar images onto an a priori estimate of the seafloor height before correlating. We develop a mathematical model for the imaging geometry. Finally, we demonstrate our proposed estimators by providing relative seafloor height estimates from real aperture and SAS images, obtained during the InSAS-2000 experiment at Elba Island in Italy. In particular, we demonstrate that the SAS image quality is significantly improved by inclusion of the height estimates as a priori information.
    IEEE Journal of Oceanic Engineering 11/2007; · 1.16 Impact Factor
  • H. Hindberg, A. Hanssen
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    ABSTRACT: Complex-valued nonstationary random processes have nonvanishing complementary second-order moment functions. In this paper, we propose generalized dual-frequency and time-frequency coherence functions for harmonizable processes. The proposed generalized spectral coherences are based on widely linear estimators, and they result in coherence measures that combine Hermitian and complementary moment functions. We show that for analytic processes, and more surprisingly also for real-valued processes, additional second-order information becomes available through the generalized coherences. We offer illuminating geometrical interpretations of the proposed coherences through Hilbert space inner product formulations. Finally, we extend the theory to generalized cross-coherences between pairs of harmonizable processes
    IEEE Transactions on Signal Processing 07/2007; · 2.81 Impact Factor
  • Source
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    ABSTRACT: We propose and design two classes of robust subspace classifiers for classification of multidimensional signals. Our classifiers are based on robust M-estimators and the least-median-of-squares principle, and we show that they may be unified as iterated reweighted oblique subspace classifiers. The performance of the proposed classifiers are demonstrated by two examples: noncoherent detection of space-time frequency-shift keying signals, and shape classification of partially occluded two-dimensional (2-D)_ objects. In both cases, the proposed robust subspace classifiers outperform the conventional subspace classifiers
    IEEE Transactions on Signal Processing 04/2007; · 2.81 Impact Factor
  • IEEE Transactions on Signal Processing. 01/2007; 55:873-880.
  • Heidi Hindberg, Alfred Hanssen
    IEEE Transactions on Signal Processing. 01/2007; 55:2407-2413.
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    ABSTRACT: Fractional Brownian motion (fBm) is a ubiquitous nonstationary model for many physical processes with power-law time-averaged spectra. In this paper, we exploit the nonstationarity to derive the full spectral correlation structure of fBm. Starting from the time-varying correlation function, we derive two different time-frequency spectral correlation functions (the ambiguity function and the Kirkwood-Rihaczek spectrum), and one dual-frequency spectral correlation function. The dual-frequency spectral correlation has a surprisingly simple structure, with spectral support on three discrete lines. The theoretical predictions are verified by spectrum estimates of Monte Carlo simulations and of a time series of earthquakes with a magnitude of 7 and higher.
    Physical Review E 10/2006; 74(3 Pt 1):031114. · 2.31 Impact Factor
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    P.J. Schreier, L.L. Scharf, A. Hanssen
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    ABSTRACT: A complex random vector is called improper if it is correlated with its complex conjugate. We present a hypothesis test for impropriety based on a generalized likelihood ratio (GLR). This GLR is invariant to linear transformations on the data, including rotation and scaling, because propriety is preserved by linear transformations. More specifically, we show that the GLR is a function of the squared canonical correlations between the data and their complex conjugate. These canonical correlations make up a complete, or maximal, set of invariants for the Hermitian and complementary covariance matrices under linear, but not widely linear, transformation
    IEEE Signal Processing Letters 08/2006; · 1.67 Impact Factor
  • P.J. Schreier, L.L. Scharf, A. Hanssen
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    ABSTRACT: A complex random vector is called improper if it is correlated with its complex conjugate. In this paper, we present a generalized likelihood ratio test (GLRT) for impropriety. This test is compelling because it displays the right invariances: The proposed GLR is invariant to linear transformations on the data, including rotation and scaling, just as propriety is preserved by linear transformations. Because canonical correlations make up a complete, or maximal, set of invariants for the Hermitian and complementary covariance matrices under linear transformations, the GLR can be shown to be a function of the squared canonical correlations between the data and its complex conjugate. This validates our intuition that the internal coordinate system should not matter for this hypothesis test
    Acoustics, Speech and Signal Processing, 2006. ICASSP 2006 Proceedings. 2006 IEEE International Conference on; 06/2006
  • A.-B. Salberg, A. Hanssen
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    ABSTRACT: In this brief, we introduce a subspace theory for differential chaos-shift keying (DCSK) systems. We show that DCSK systems operate by transmission of chaotic signals residing in a low-dimensional subspace. The subspace formalism of DCSK schemes leads to the derivation of useful subspace detectors that can be applied to decode the DCSK signal for various types of channels. Closed form expressions for the bit error rate is derived for an M-ary FM-version of DCSK, under the assumption of orthogonal subspace generating vectors. Numerical simulations demonstrate that the proposed subspace detector in general outperforms the conventional correlation detector for DCSK
    Circuits and Systems II: Express Briefs, IEEE Transactions on 02/2006; · 1.33 Impact Factor
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    ABSTRACT: In order to gather information about the physics of the complex plasma crystals from the experimental data, particles have to be tracked through a sequence of images. An application of the Kalman filter for that purpose is presented, using a one-dimensional approximation of the particle dynamics as a model for the filter. It is shown that Kalman filter is capable of tracking dust particles even with high levels of measurement noise. An inherent part of the Kalman filter, the innovation process, can be used to estimate values of the physical system parameters from the experimental data. The method is shown to be able to estimate the characteristic oscillation frequency from noisy data.
    Physics of Plasmas 01/2006; 13. · 2.38 Impact Factor
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    ABSTRACT: In this paper, we examine kernel-based estimators for the Kirkwood-Rihaczek time-frequency spectrum of harmoniz-able, nonstationary processes. Based on an inner product consideration, we propose and implement an estimator for the Kirkwood-Rihaczek spectrum. The estimator is con-structed from a combination of the complex demodulate with a short-time Fourier transform. Our proposed estimator is less computationally intensive than a theoretically equiva-lent, known estimator. We compare and test the results of the proposed estimator with an existing estimator from a Mat-lab time-frequency toolbox on simulated and real-world data. We demonstrate that the proposed estimator is less sensitive to unwanted cross-terms, and less affected by edge effects than the Matlab time-frequency toolbox estimator.
    01/2006;
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    ABSTRACT: In this paper, we present an analysis of recordings of a transversal flute made from the dried stem of the Heracleum laciniatum (Tromsoe Palm or Hogweed). While the lower octave exhibits conventional harmonic spectra, the upper octave surprisingly includes subharmonic components. We believe that the subharmonic contributions are due to nonlinear oscillations of the flute material. A time-frequency analysis of the onset of the sound, shows that the subharmonic oscillators are present from the very beginning, as opposed to the higher harmonics. A bispectral analysis indicates that triplets of frequency components are phase locked
    01/2006;
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    A. Hanssen, T.A. Oigard, Y. Birkelund
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    ABSTRACT: We have analyzed the sound of an electric guitar that has been amplified by a high-quality all-tube amplifier, and emitted by means of a speaker cabinet. We re-amplified a recording of a clean guitar through a state-of-the-art all-tube amplifier at three different preamplifier gain settings: one clean, one half-distorted, and one massively distorted. Spectral analysis of recordings of the three signals exhibited a remarkably rich overtone spectrum, and we observed that only the high frequency part of the spectrum was boosted by an increase in the distortion levels. A bispectral analysis of the amplified guitar sound showed that quadratic nonlinearities are responsible for coherent phase coupling among the partials, and that the fraction of the total power which is due to quadratic nonlinearities is larger for the clean sound than for the distorted sound. Finally, a dual-frequency analysis showed that the sound, even for the sustained part of a single string pluck, is in fact a nonstationary random process. Our analysis showed that the guitar tone should be classified as an (almost) cyclostationary random process.
    Applications of Signal Processing to Audio and Acoustics, 2005. IEEE Workshop on; 11/2005
  • P.J. Schreier, L.L. Scharf, A. Hanssen
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    ABSTRACT: Based on the Cramer-Loeve spectral representation for a harmonizable random process, the Rihaczek distribution is a time- and frequency-shift covariant, bilinear time-frequency distribution. It can be expressed as a complex Hilbert space inner product between the time series and its infinitesimal stochastic Fourier generator. We show that we may attach an illuminating geometry to this inner product, wherein the cosine-squared of the angle between the time series and its infinitesimal stochastic Fourier generator is given by the Rihaczek distribution. We propose to construct estimators of the Rihaczek distribution using a factored kernel in Cohen's class of bilinear time-frequency distributions
    Information Theory, 2005. ISIT 2005. Proceedings. International Symposium on; 10/2005
  • T.A. Oigard, L.L. Scharf, A. Hanssen
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    ABSTRACT: Fractional Brownian motion (fBm) is a useful non-stationary model for certain fractal and long-range dependent processes of interest in telecommunications, physics, biology, and finance. Conventionally, the power spectrum of fBm is claimed to be a fractional power-law. However, fBm is not a wide-sense stationary process, so the precise meaning of this spectrum is unclear. In this paper, we model and analyze fBm in the context of harmonizable random processes. We derive and interpret exact expressions for novel useful complex valued second-order moment functions for fBm. These moment functions are time-frequency and dual-frequency correlation functions, connecting the random process to its infinitesimal random Fourier generator. In particular, we derive and discuss the time-frequency Rihaczek spectrum, and the dual-frequency Loeve spectrum. Our main finding is that the dual-frequency spectrum of fBm has its spectral support confined to three discrete lines. This leads to the surprising conclusion that for fBm, the DC component of the infinitesimal Fourier generator is correlated with ail other frequencies of the Fourier generator. We propose and apply multitaper based estimators for the moment functions, and numerical estimates based on synthetic fBm data and real world earthquake data confirm our theoretical results
    Statistical Signal Processing, 2005 IEEE/SP 13th Workshop on; 08/2005

Publication Stats

261 Citations
57.17 Total Impact Points

Institutions

  • 1997–2009
    • Universitetet i Tromsø
      • • Department of Physics and Technology
      • • Department of Mathematics and Statistics
      Tromsø, Troms Fylke, Norway
  • 2005–2006
    • University of Newcastle
      • School of Electrical Engineering and Computer Science
      Newcastle, New South Wales, Australia
  • 2001–2005
    • Colorado State University
      • Electrical & Computer Engineering
      Fort Collins, CO, United States
  • 2003
    • University of Texas at Austin
      • Department of Electrical & Computer Engineering
      Austin, TX, United States