| 1. |
- Bengtsson, Tomas, 1983, et al.
(författare)
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Regularized Optimization for Joint Super-Resolution and High Dynamoc Range Image Reconstruction in a Percetually Uniform Domain.
- 2012
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Ingår i: ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings. - 1520-6149. - 9781467300469 ; , s. 1097-1100
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Konferensbidrag (refereegranskat)abstract
- This paper discusses resolution enhancement of a set of images with varying exposure durations, having a high combined dynamic range. So far, little has been said in relation to the Human Visual System when it comes to Super-Resolution and High Dynamic Range fusion, unlike the case for traditional Super-Resolution where errors are measured with respect to human perception in the pixel domain. We propose a Super-Resolution method in the L*a*b* domain to bridge the gap and present some image reconstruction results.
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| 2. |
- Cerullo, Livia, 1982, et al.
(författare)
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Concurrent estimation of space and frequency variation for dielectrics: a microwave tomography system for process sensing applications
- 2011
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Ingår i: Proceedings of the 9th International Conference on Electromagnetic Wave Interaction with Water and Moist Substances, Kansas City, MO USA, May 31 - June 3, 2011. - 9781629934556 ; , s. 177-184
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Konferensbidrag (refereegranskat)abstract
- In many powder processing operations, the effective complex permittivity of the material under processing yields important information concerning the state of the process. This complex permittivity varies in general with respect to both space and frequency. For an accurate estimation of the process material parameters, it is important to be able to incorporate these dependencies in the estimation algorithm. Here, we present a rather general type of parameterization that is tailored for this type of situation. The parameterization is described in terms of a parameterization mesh, which makes it feasible to refine the computational mesh without influencing the number of degrees of freedom in the estimation problem. A test case demonstrates that our approach can yield accurate reconstructions.
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| 3. |
- Cerullo, Livia, 1982, et al.
(författare)
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Determination of model order for inverse scattering applications
- 2010
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Ingår i: Proceedings of the V European Conference on Computational Fluid Dynamics ECCOMAS CFD 2010 J. C. F. Pereira, A. Sequeira and J. M. C. Pereira (Eds) Lisbon, Portugal,14-17 June 2010. - 9789899677814
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Konferensbidrag (refereegranskat)
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| 4. |
- Cerullo, Livia, 1982, et al.
(författare)
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Inverse scattering for a closed cavity equipped with microwave antenna sensors
- 2012
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Ingår i: AntennEMB, 5-8 March, Stockholm.
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- Pharmaceutical processes are often hosted by completely closed vessels that are difficult of access by means of measurement equipment. In particular, it is challenging to assess the interior or global process state with sensors placed on the vessel enclosing the process. This information about the process would allow for a better process monitoring and control. Here, a novel application of microwave sensing for process tomography is presented.
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| 5. |
- Cerullo, Livia, 1982, et al.
(författare)
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Microwave Measurements for Metal Vessels
- 2013
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Ingår i: 7th European Conference on Antennas and Propagation, EuCAP 2013, Gothenburg, Sweden, 8-12 April 2013. - 2164-3342. - 9781467321877 ; , s. 3869 - 3873
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Konferensbidrag (refereegranskat)abstract
- We present two different measurement techniques intended for closed metal vessels, where the objective is to measure the permittivity inside the metal vessel. This problem is relevant for many applications found in e.g. process industry. The first approach exploits the measurement of resonance frequencies, where the metal vessel is used as a microwave resonator. In the second approach, we let the boundary of the metal vessel be equipped with aperture antennas, where the aperture antennas are implemented in terms of rectangular waveguides. The waveguide apertures loads the cavity significantly and we exploit the scattering matrix parameters for the solution of the inverse problem.
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| 6. |
- Chung, P. J., et al.
(författare)
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Broadband ML estimation under model order uncertainty
- 2010
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Ingår i: Signal Processing. - : Elsevier BV. - 0165-1684. ; 90:5, s. 1350-1356
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Tidskriftsartikel (refereegranskat)abstract
- The number of signals hidden in data plays a crucial role in array processing. When this information is not available, conventional approaches apply information theoretic criteria or multiple hypothesis tests to simultaneously estimate model order and parameter. These methods are usually computationally intensive, since ML estimates are required for a hierarchy of nested models. In this contribution, we propose a computationally efficient solution to avoid this full search procedure and address issues unique to the broadband case. Our max-search approach computes ML estimates only for the maximally hypothesized number of signals, and selects relevant components through hypothesis testing. Furthermore, we introduce a criterion based on the rank of the steering matrix to reduce indistinguishable components caused by overparameterization. Numerical experiments show that despite model order uncertainty, the proposed method achieves comparable estimation and detection accuracy as standard methods, but at much lower computational expense. (C) 2009 Elsevier B.V. All rights reserved.
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| 7. |
- Chung, Pei-Jung, et al.
(författare)
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DOA Estimation Methods and Algorithms
- 2014
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Ingår i: Academic Press Library in Signal Processing: Volume 3 Array and Statistical Signal Processing. - 9780124115972 ; , s. 599-650
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Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract
- Estimation of direction of arrival (DOA) from data collected by sensor arrays is of fundamental importance to a variety of applications such as radar, sonar, wireless communications, geophysics and biomedical engineering. Significant progress in the development of algorithms has been made over the last three decades. This article provides an overview of DOA estimation methods that are relevant in theory and practice. We will present estimators based on beamforming, subspace and parametric approaches and compare their performance in terms of estimation accuracy, resolution capability and computational complexity. Methods for processing broadband data and signal detection will be discussed as well. Finally, a brief discussion will be given to application specific algorithms.
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| 8. |
- Costa, Mario, et al.
(författare)
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Array Processing in the Face of Nonidealities
- 2014
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Ingår i: Academic Press Library in Signal Processing: Volume 3 Array and Statistical Signal Processing. - 9780124115972 ; , s. 819-857
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Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract
- Real-world sensor arrays are typically composed of elements with individual directional beampatterns and are subject to mutual coupling, cross-polarization effects as well as mounting platform reflections. Errors in the array elements’ positions are also common in sensor arrays built in practice. Such nonidealities need to be taken into account for optimal array signal processing and in finding related performance bounds. Moreover, problems related to beam-steering and cancellation of the signal-of-interest in beamforming applications may be prevented. Otherwise, an array processor may experience a significant performance degradation. In this chapter we provide techniques that allow the practitioner to acquire the steering vector model of real-world sensor arrays so that various nonidealities are taken into account. Consequently, array processing algorithms may avoid performance losses caused by array modeling errors. These techniques include model-based calibration and auto-calibration methods, array interpolation, as well as the wavefield modeling principle or manifold separation technique. Robust methods are also briefly considered since they are useful when the array nonidealities are not described by the employed steering vector model. Extensive array processing examples related to direction-finding and beamforming are included demonstrating that optimal or close-to optimal performance may be achieved despite the array nonidealities.
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| 9. |
- Ferreol, A., et al.
(författare)
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Statistical Analysis of the MUSIC Algorithm in the Presence of Modeling Errors, Taking Into Account the Resolution Probability
- 2010
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Ingår i: IEEE Transactions on Signal Processing. - 1941-0476 .- 1053-587X. ; 58:8, s. 4156-4166
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Tidskriftsartikel (refereegranskat)abstract
- This paper considers the statistical performance of the MUSIC method under the condition that two closely spaced sources impinging on an array of sensors are effectively resolved, i.e., the spectrum exhibits two peaks in the neighborhood of the true directions-of-arrival (DOA). The MUSIC algorithm is known to have an infinite resolution power in theory. However, in the presence of modeling errors, sources can not be resolved with certainty, even if the array correlation matrix is perfectly known. The focus of this paper is to predict the bias and variance of the DOA estimates taking into account the possible resolution failure of MUSIC. This performance prediction, based on our recent mathematical investigation, is new to the best of our knowledge. A general mathematical framework to derive closed form expressions of the bias and variance versus the model mismatch, conditioned on a general statistical resolution test is proposed. In order to illustrate our mathematical approach, statistical tests with one and two conditions, respectively, are investigated. The accuracy of the performance prediction is illustrated in a simulation study. It is found that the proposed approach outperforms the "classical" technique, which ignores the possible resolution failure of the MUSIC algorithm. Therefore, our results provide better tools for determining the necessary antenna calibration accuracy to achieve some targeted specifications on the estimator performance.
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| 10. |
- Johansson, Eija, 1982, et al.
(författare)
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Interpolation based on stationary and adaptive AR(1) modeling
- 2011
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Ingår i: ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings. - 1520-6149. - 9781457705397 ; , s. 4052-4055
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Konferensbidrag (refereegranskat)abstract
- In this paper, we describe a minimal mean square error (MMSE) optimal interpolation filter for discrete random signals. We explicitly derive the interpolation filter for a first-order autoregressive process (AR(1)), and show that the filter depends only on the two adjacent points. The result is extended by developing an algorithm called local AR approximation (LARA), where a random signal is locally estimated as an AR(1) process. Experimental evaluation illustrates that LARA interpolation yields a lower mean square error than other common interpolation techniques, including linear, spline and local polynomial approximation (LPA).
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