The Experts below are selected from a list of 306 Experts worldwide ranked by ideXlab platform
Emanuel A. P. Habets - One of the best experts on this subject based on the ideXlab platform.
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A Method to Analyze the Spatial Response of Informed Spatial Filters
Speech Communication; 12. ITG Symposium, 2016Co-Authors: Soumitro Chakrabarty, Oliver Thiergart, Emanuel A. P. HabetsAbstract:Informed Spatial filters (ISF) aim to capture multiple sound sources with a desired Spatial Response while attenuating the undesired signals. The desired Spatial Response is an arbitrary function, based on which directional gains at each time-frequency instant are computed. In this work, we propose a method to analyze the obtained Spatial Response at the output of the ISF and the influence of direction-ofarrival (DOA) estimation errors. The proposed method considers two simultaneously active sound sources, where one source is kept static at a reference position while the other source is moved across the DOA space by placing it at discrete DOA points. For each position of the moving source, we compute the average directional array gain. Through analysis with simulated speech signals, we show that with perfect knowledge of the source DOAs the obtained Spatial Response matches the desired one, and also demonstrate the adverse effects of DOA estimation errors.
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A Bayesian approach to Spatial filtering and diffuse power estimation for joint dereverberation and noise reduction
2015 IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP), 2015Co-Authors: Soumitro Chakrabarty, Oliver Thiergart, Emanuel A. P. HabetsAbstract:A Spatial filter, with L linear constraints that are based on instantaneous narrowband direction-of-arrival (DOA) estimates, was recently proposed to obtain a desired Spatial Response for at most L sound sources. In noisy and reverberant environments, it becomes difficult to get reliable instantaneous DOA estimates and hence obtain the desired Spatial Response. In this work, we develop a Bayesian approach to Spatial filtering that is more robust to DOA estimation errors. The resulting filter is a weighted sum of Spatial filters pointed at a discrete set of DOAs, with the relative contribution of each filter determined by the posterior distribution of the discrete DOAs given the microphone signals. In addition, the proposed Spatial filter is able to reduce both reverberation and noise. In this work, the required diffuse sound power is estimated using the posterior distribution of the discrete set of DOAs. Simulation results demonstrate the ability of the proposed filter to achieve strong suppression of the undesired signal components with small amount of signal distortion, in noisy and reverberant conditions.
Soumitro Chakrabarty - One of the best experts on this subject based on the ideXlab platform.
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A Method to Analyze the Spatial Response of Informed Spatial Filters
Speech Communication; 12. ITG Symposium, 2016Co-Authors: Soumitro Chakrabarty, Oliver Thiergart, Emanuel A. P. HabetsAbstract:Informed Spatial filters (ISF) aim to capture multiple sound sources with a desired Spatial Response while attenuating the undesired signals. The desired Spatial Response is an arbitrary function, based on which directional gains at each time-frequency instant are computed. In this work, we propose a method to analyze the obtained Spatial Response at the output of the ISF and the influence of direction-ofarrival (DOA) estimation errors. The proposed method considers two simultaneously active sound sources, where one source is kept static at a reference position while the other source is moved across the DOA space by placing it at discrete DOA points. For each position of the moving source, we compute the average directional array gain. Through analysis with simulated speech signals, we show that with perfect knowledge of the source DOAs the obtained Spatial Response matches the desired one, and also demonstrate the adverse effects of DOA estimation errors.
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A Bayesian approach to Spatial filtering and diffuse power estimation for joint dereverberation and noise reduction
2015 IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP), 2015Co-Authors: Soumitro Chakrabarty, Oliver Thiergart, Emanuel A. P. HabetsAbstract:A Spatial filter, with L linear constraints that are based on instantaneous narrowband direction-of-arrival (DOA) estimates, was recently proposed to obtain a desired Spatial Response for at most L sound sources. In noisy and reverberant environments, it becomes difficult to get reliable instantaneous DOA estimates and hence obtain the desired Spatial Response. In this work, we develop a Bayesian approach to Spatial filtering that is more robust to DOA estimation errors. The resulting filter is a weighted sum of Spatial filters pointed at a discrete set of DOAs, with the relative contribution of each filter determined by the posterior distribution of the discrete DOAs given the microphone signals. In addition, the proposed Spatial filter is able to reduce both reverberation and noise. In this work, the required diffuse sound power is estimated using the posterior distribution of the discrete set of DOAs. Simulation results demonstrate the ability of the proposed filter to achieve strong suppression of the undesired signal components with small amount of signal distortion, in noisy and reverberant conditions.
Javier Alda - One of the best experts on this subject based on the ideXlab platform.
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Application of tomographic techniques to the Spatial-Response mapping of antenna-coupled detectors in the visible.
Applied Optics, 2008Co-Authors: José María Rico-garcía, Luis Miguel Sanchez-brea, Javier AldaAbstract:A tomographiclike method based on the inverse radon transform is used to retrieve the irradiance map of a focused laser beam. The results obtained from multiple knife-edge measurements have been processed through a kriging technique. This technique allows us to map both the beam irradiance and the uncertainty associated with the measurement method. The results are compared with those achieved in the standard fitting of two orthogonal knife-edge profiles to a modeled beam. The application of the tomographiclike technique does not require any beam model and produces a higher signal-to-noise ratio than the conventional method. As a consequence, the quality of the estimation of the Spatial Response map of an antenna-coupled detector in the visible is improved.
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High-resolution Spatial-Response measurements of optical nano-antennas in the visible
2007 IEEE Antennas and Propagation Society International Symposium, 2007Co-Authors: Javier Alda, Jose M. Rico-garcia, Jose M. Lopez-alonso, Glenn D. BoremanAbstract:A few years ago, some of the authors of the paper demonstrated the resonance of optical antennas in the visible frequencies. The results of that paper were obtained using experimental techniques that were primarily developed for the measurement of antenna-coupled detectors in the infrared. In the present paper, we show the results of Spatial-Response mapping obtained by using a dedicated measurement station for the characterization of optical antennas in the visible. At the same time, the bottleneck in the Spatial responsivity calculation represented by the beam characterization has been approached from a different perspective. The proposed technique uses a collection of knife edge measurements in order to avoid the use of any model of the laser beam irradiance. By taking all this into account we present the Spatial responsivity of optical antennas measured with high Spatial resolution in the visible.
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Deconvolution method for two-dimensional Spatial-Response mapping of lithographic infrared antennas.
Applied Optics, 1999Co-Authors: Javier Alda, Christophe Fumeaux, Iulian Codreanu, Jason A. Schaefer, Glenn D. BoremanAbstract:The Spatial impulse Response of antenna-coupled infrared detectors with dimensions comparable with the wavelength is obtained from a two-dimensional scan of a tightly focused CO2-laser beam. The method uses an experimental setup with submicrometer resolution and an iterative deconvolution algorithm. The measured Spatial Response is compared with numerically computed near-field distributions of a dipole antenna, with good agreement. © 1999 Optical Society of America OCIS codes: 040.0040, 040.3060, 040.5570, 100.1830, 230.5440. Novel submicrometer-sized thin-film detectors have been demonstrated in the infrared ~IR! at wavelengths near 10 mm. Their sensing mechanism is based on the operation of metal‐ oxide‐metal ~MOM! diodes 1‐3 or microbolometers. 4 The power collection capability of these ultrasmall detectors is enhanced by the use of integrated antennas. The measured Response is closely related to the shape of the antenna ~e.g., dipole, bow tie, or spiral! and its physical dimensions. These detectors are the smallest currently available in the IR region. Characterization of their two-dimensional Spatial Response is therefore a challenging task. In this paper, we demonstrate a method to map the Spatial Response of these devices. The signal obtained from a detector is proportional to the irradiance distribution integrated over the collecting area of the device. For classical macroscopic IR sensors the photosensitive region is well defined and is usually described as an effective area within which a constant Spatial Response is assumed; the outside region is zero. To characterize such devices, one typically scans a probe beam across the photosensitive region, measuring the output of the detector as a function of the position of the probe beam. The measured output signal is, in general, the convolution of the sensor’s Spatial Response and the beam profile. If the dimensions of the photosensitive region are large compared with the beam, the detector’s Spatial Response can be approximated directly as the measured output signal. The subwavelength IR detectors used in our study are smaller than the waist dimensions of laser beams, even when low fy# focusing optics are used. Consequently, our problem involves the mapping of a structure smaller than the dimension of the probe beam used for the measurement. This problem has been addressed and solved in other areas of optics. The restoration of images produced by aberrated systems is possible when the transfer function of the optical system is well known. An interesting application of this principle was developed for the Hubble Space Telescope. 5 Its point-spread function ~PSF! was calculated with high accuracy, and blurred images were enhanced by use of the known PSF in a deconvolution procedure. The algorithms developed for this case have been adapted to retrieve the Spatial Response of our small IR detectors. Section 2 describes the theoretical foundations of the deconvolution method and shows the application of the iterative algorithm, along with the characterization method of the illuminating beam and the parameterization of the Spatial Response. To illustrate the deconvolution method, we present in Section 3 the determination of the thermal and the antenna Spatial Response of MOM antenna-coupled detectors. The practical problems of characterizing the beam before the deconvolution algorithm are discussed. We also analyze several methods to provide dimen
Oliver Thiergart - One of the best experts on this subject based on the ideXlab platform.
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A Method to Analyze the Spatial Response of Informed Spatial Filters
Speech Communication; 12. ITG Symposium, 2016Co-Authors: Soumitro Chakrabarty, Oliver Thiergart, Emanuel A. P. HabetsAbstract:Informed Spatial filters (ISF) aim to capture multiple sound sources with a desired Spatial Response while attenuating the undesired signals. The desired Spatial Response is an arbitrary function, based on which directional gains at each time-frequency instant are computed. In this work, we propose a method to analyze the obtained Spatial Response at the output of the ISF and the influence of direction-ofarrival (DOA) estimation errors. The proposed method considers two simultaneously active sound sources, where one source is kept static at a reference position while the other source is moved across the DOA space by placing it at discrete DOA points. For each position of the moving source, we compute the average directional array gain. Through analysis with simulated speech signals, we show that with perfect knowledge of the source DOAs the obtained Spatial Response matches the desired one, and also demonstrate the adverse effects of DOA estimation errors.
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A Bayesian approach to Spatial filtering and diffuse power estimation for joint dereverberation and noise reduction
2015 IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP), 2015Co-Authors: Soumitro Chakrabarty, Oliver Thiergart, Emanuel A. P. HabetsAbstract:A Spatial filter, with L linear constraints that are based on instantaneous narrowband direction-of-arrival (DOA) estimates, was recently proposed to obtain a desired Spatial Response for at most L sound sources. In noisy and reverberant environments, it becomes difficult to get reliable instantaneous DOA estimates and hence obtain the desired Spatial Response. In this work, we develop a Bayesian approach to Spatial filtering that is more robust to DOA estimation errors. The resulting filter is a weighted sum of Spatial filters pointed at a discrete set of DOAs, with the relative contribution of each filter determined by the posterior distribution of the discrete DOAs given the microphone signals. In addition, the proposed Spatial filter is able to reduce both reverberation and noise. In this work, the required diffuse sound power is estimated using the posterior distribution of the discrete set of DOAs. Simulation results demonstrate the ability of the proposed filter to achieve strong suppression of the undesired signal components with small amount of signal distortion, in noisy and reverberant conditions.
Xin Wang - One of the best experts on this subject based on the ideXlab platform.
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Spatial-Response Matched Filter and Its Application in Radiometric Accuracy Improvement of FY-2 Satellite Thermal Infrared Band
IEEE Transactions on Geoscience and Remote Sensing, 2015Co-Authors: Xin WangAbstract:The adjacent effect caused by a nonideal system point spread function (PSF) is an important source generating additional errors in radiometric measurements. Traditional recovery methods, i.e., inverse and Wiener filters, are attempted to restore the scene without the influence of RSF, which is inexistent in real observations and usually leads to the ringing artifact as well as uncertainties in noise amplification (NA). In this paper, a novel Spatial-Response matched filter (SRMF) and its processing method are established, where the aimed scene is supposed to be observed by instruments with higher PSF performance. Also, NA effects triggered by SRMF are precisely modeled and used for the further evaluation of radiometric accuracy (RA) variation after SRMF processing. Simulation results indicate that the SRMF method is more suitable for images with lower noise level and greater variation in the targets' radiation, where RA performance could be improved in a certain extent. Meanwhile, when the imager in a Multifunctional Transport Satellite is selected as the reference one with high-performance PSF, the SRMF for Fengyun-2 satellite is set up and applied for observations in thermal infrared band during April and May 2013. After SRMF processing, the recovered images show significant improvements in both visual effects and RA, where the increase of RA is expected to be 2-6 K at 190 K in statistics. Such a progress is believed to be beneficial to tropical cyclone intensity estimation as well as for other relevant products, i.e., cloud classification generation.
