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Träfflista för sökning "LAR1:cth ;pers:(Viberg Mats 1961);conttype:(refereed);lar1:(cth);mspu:(conferencepaper)"

Sökning: LAR1:cth > Viberg Mats 1961 > Refereegranskat > Chalmers tekniska högskola > Konferensbidrag

  • Resultat 11-20 av 105
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16.
  • Feng, S, et al. (författare)
  • 3D Face Recognition Using Affine Integral Invariants
  • 2006
  • Ingår i: IEEE international conf. on ASSP (ICASSP-06). ; II, s. 189-192
  • Konferensbidrag (refereegranskat)abstract
    • A new 3D face representation and recognition approach is presented in this paper. Two sets of facial curves are extracted from a face range image, and a novel facial feature representation, the affine integral invariant, is introduced to mitigate the effect of pose on the facial curves. A human face is shown to be representable by a smallsubset of those affine integral invariant curves. A recognition procedure based on the Discriminant Analysis and Jensen-Shannon Divergence analysis is proposed. Substantiating examples are provided with an achieved classification accuracy of 92.57%.
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17.
  • Ferreol, A., et al. (författare)
  • A New Expression of the Asymptotic Performances of Maximum Likelihood DOA Estimation Method With Modeling Errors
  • 2004
  • Ingår i: Proceeding EURASIP 2004, Vienna, Austria.. - 2219-5491. - 9783200001657 ; , s. 2163-2166
  • Konferensbidrag (refereegranskat)abstract
    • This paper provides a new analytic expression of the RMS (Root Mean Square) error and bias of the Maximum Likelihood (ML) Direction Of Arrival (DOA) estimator in the presence of steering vectors modeling errors. The reference [4] proposes a first order approximation of these performances which is adapted to small modeling errors. In order to take into account larger modeling errors and provide tools for designing experimental set-up, a more accurate and easily usable derivation of these performances is necessary For such an investigation, the DOA estimation errors are written as an hermitean form with a stochastic vector composed by the modeling errors. Finally, a closed form expression between the performances (bias and RMS error) and statistical moments of the model error are deduced from the statistics of the hermitean form. Simulations confirm the theoretical results.
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18.
  • Ferreol, A., et al. (författare)
  • Modeling error sensitivity of the MUSIC algorithm conditioned on resolved sources
  • 2008
  • Ingår i: European Signal Processing Conference. - 2219-5491.
  • Konferensbidrag (refereegranskat)abstract
    • When the correlation matrix is known, the resolution power of subspace algorithms is infinite. In the presence of modelling errors, even if the correlation matrix is known, sources can no longer be resolved with certainty. Focusing on the MUSIC algorithm [1], the purpose of this work is to provide closed form expression of bias and variance versus the model mismatch (these errors can be different for each source). Un-like previous work, these performance measures are derived conditioned on the success of a certain source resolution test. Among the resolution definitions proposed in [2], we investigate which one is more suitable for our purposes. Numerical results support the theoretical investigations. Our findings are of a great interest for the determination of the necessary antenna calibration accuracy to achieve specifications on the estimator performance.
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19.
  • Ghaemi, Hirad, 1980, et al. (författare)
  • CLEAN technique in strip-map SAR for high-quality imaging
  • 2009
  • Ingår i: IEEE Aerospace Conference Proceedings. - 1095-323X. - 9781424426225 ; , s. Art. no. 4839474-
  • Konferensbidrag (refereegranskat)abstract
    • The maximum obtainable resolution of a strip-map synthetic aperture radar (SAR) system can be retained by simply avoiding weighting, or tapering, data samples in the along-track compression process. However, this will lead to hazardous artifacts caused by strong sidelobes of the corresponding adjacent scatterers whose interference might severely weaken the desired targets or even introduce false targets. On the other hand, some residual artifacts, even after tapering process, may still deteriorate the quality (contrast) of the SAR image. These issues can be remedied by applying the so-called CLEAN technique, which can mitigate these ill-effects in strip-map SAR imagery while maintaining the maximum resolution. This, indeed, is carried out as a post processing step, i.e., after the azimuth compression is accomplished, in the SAR system. The objective of this paper is to extend the CLEAN technique to strip-map SAR system to produce high-quality images with a very good along-track resolution. The algorithm is then applied to data from a ground-based circular SAR (CSAR) system to verify its implementation as well as this new application of the CLEAN technique.
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20.
  • Ghaemi, Hirad, 1980, et al. (författare)
  • RELAX-based autofocus algorithm for high-resolution strip-map SAR
  • 2009
  • Ingår i: IEEE National Radar Conference - Proceedings. - 1097-5659. - 9781424428717 ; , s. 1 - 6
  • Konferensbidrag (refereegranskat)abstract
    • This paper addresses the non-iterative quality phase gradient autofocus (QPGA) technique which was originally proposed to remove one-dimensional phase errors in spotlight-mode synthetic aperture radar (SAR) imagery. By enriching the source pool, the method is modified in a way suitable for autofocus in stripmap-mode SAR system with the advantage of being independent of any priori assumptions. Unlike the QPGA the potential candidates, i.e., dominant scatterers located along azimuth in each specific range bin, are automatically selected by exploiting the one-dimensional RELAX algorithm. Furthermore, RELAX is capable of estimating the size of blur window which is, in fact, associated with the Doppler spread of signal spectrum. The corresponding model includes four parameters i.e., complex amplitude, delay, Doppler center and spectral width. The proposed method has been applied to data extracted by a ground-based rotating coherent Doppler radar operating in strip-mapping mode SAR, with the aim of high-resolution clutter detection.
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