Pub Date : 2013-12-02DOI: 10.1109/ICEEE.2013.6676058
Y. Shmaliy, D. Simon
Various iterative unbiased finite impulse response (UFIR) algorithms are proposed for filtering, smoothing, and prediction of discrete-time state-space models in white Gaussian noise. The distinctive property of UFIR algorithms is that noise statistics are completely ignored. Instead, an optimal window size is required for optimal performance. Under real-world operating conditions with uncertainties, non-Gaussian noise, and unknown noise statistics, the UFIR estimator generally demonstrates better robustness than the Kalman filter, even with suboptimal window size.
{"title":"Iterative algorithms for unbiased FIR state estimation in discrete time","authors":"Y. Shmaliy, D. Simon","doi":"10.1109/ICEEE.2013.6676058","DOIUrl":"https://doi.org/10.1109/ICEEE.2013.6676058","url":null,"abstract":"Various iterative unbiased finite impulse response (UFIR) algorithms are proposed for filtering, smoothing, and prediction of discrete-time state-space models in white Gaussian noise. The distinctive property of UFIR algorithms is that noise statistics are completely ignored. Instead, an optimal window size is required for optimal performance. Under real-world operating conditions with uncertainties, non-Gaussian noise, and unknown noise statistics, the UFIR estimator generally demonstrates better robustness than the Kalman filter, even with suboptimal window size.","PeriodicalId":400766,"journal":{"name":"21st European Signal Processing Conference (EUSIPCO 2013)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132078151","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-09-30DOI: 10.13140/RG.2.1.1392.1768
James Eaton, P. Naylor
In order to exploit the full dynamic range of communications and recording equipment, and to minimise the effects of noise and interference, input gain to a recording device is typically set as high as possible. This often leads to the signal exceeding the input limit of the equipment resulting in clipping. Communications devices typically rely on codecs such as GSM 06.10 to compress voice signals into lower bitrates. Although detecting clipping in a hard-clipped speech signal is straightforward due to the characteristic flattening of the peaks of the waveform, this is not the case for speech that has subsequently passed through a codec. We describe a novel clipping detection algorithm based on amplitude histogram analysis and least squares residuals which can estimate the clipped samples and the original signal level in speech even after the clipped speech has been perceptually coded.
{"title":"Detection of clipping in coded speech signals","authors":"James Eaton, P. Naylor","doi":"10.13140/RG.2.1.1392.1768","DOIUrl":"https://doi.org/10.13140/RG.2.1.1392.1768","url":null,"abstract":"In order to exploit the full dynamic range of communications and recording equipment, and to minimise the effects of noise and interference, input gain to a recording device is typically set as high as possible. This often leads to the signal exceeding the input limit of the equipment resulting in clipping. Communications devices typically rely on codecs such as GSM 06.10 to compress voice signals into lower bitrates. Although detecting clipping in a hard-clipped speech signal is straightforward due to the characteristic flattening of the peaks of the waveform, this is not the case for speech that has subsequently passed through a codec. We describe a novel clipping detection algorithm based on amplitude histogram analysis and least squares residuals which can estimate the clipped samples and the original signal level in speech even after the clipped speech has been perceptually coded.","PeriodicalId":400766,"journal":{"name":"21st European Signal Processing Conference (EUSIPCO 2013)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116772421","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
LTE the latest mobile network standard, is widely adopted and targets high spectral efficiency. Cognitive radio (CR) systems on the other hand enable smart use of wireless resources leading to significant performance and reliability improvement. Accordingly, adopting the LTE specifications in CR it is a reasonable choice to optimized the spectrum utilisation in wireless communications. In this paper, we investigate some issues in the real-time implementation of a TDD (time division duplex) LTE-based spatial interweave (IW) CR. Indeed, the IW-CR requires the channel state information (CSI) to opportunistically exploit spatial holes for cognitive transmissions. Preliminary works have illustrated the possibility to acquire the CSI through the calibration of the channel reciprocity inherent in TDD systems. However, they consider constant radio frequency (RF) filters, which leads to perturbations in the IW-CR. Hence, we propose a new tracking method to tackle the variation in the RF. The whole system is implemented and evaluated on an experimental platform, where the simulation results reveal performance enhancement using this new approach.
{"title":"Enabling the implementation of spatial interweave LTE cognitive radio","authors":"B. Kouassi, D. Slock, I. Ghauri, L. Deneire","doi":"10.5281/ZENODO.43473","DOIUrl":"https://doi.org/10.5281/ZENODO.43473","url":null,"abstract":"LTE the latest mobile network standard, is widely adopted and targets high spectral efficiency. Cognitive radio (CR) systems on the other hand enable smart use of wireless resources leading to significant performance and reliability improvement. Accordingly, adopting the LTE specifications in CR it is a reasonable choice to optimized the spectrum utilisation in wireless communications. In this paper, we investigate some issues in the real-time implementation of a TDD (time division duplex) LTE-based spatial interweave (IW) CR. Indeed, the IW-CR requires the channel state information (CSI) to opportunistically exploit spatial holes for cognitive transmissions. Preliminary works have illustrated the possibility to acquire the CSI through the calibration of the channel reciprocity inherent in TDD systems. However, they consider constant radio frequency (RF) filters, which leads to perturbations in the IW-CR. Hence, we propose a new tracking method to tackle the variation in the RF. The whole system is implemented and evaluated on an experimental platform, where the simulation results reveal performance enhancement using this new approach.","PeriodicalId":400766,"journal":{"name":"21st European Signal Processing Conference (EUSIPCO 2013)","volume":"128 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115630432","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
SAR Interferograms illustrate an ambiguous (modulo 2π) and noisy phase. In this paper, we focus on the step of interferogram denoising using the Adaptive Switching Median Filter (ASMF) in the wavelet domain. Thus, we propose to filter the coefficients of the relative Discrete Packet Wavelet Transform (DPWT). Our main contribution in this paper concerns firstly, the methodology for computing the mask of noise corresponding to the InSAR phase. Secondly, the size of the median filter is computed considering the noise mask within a given neighborhood and taking into account the corresponding InSAR coherence values. This scheme is tested on simulated noisy interferograms as well as on a given pairs of single look complex (SLC) data from Envisat satellite. Validation was made by computing the Digital Elevation Model after unwrapping the filtered interferogram.
{"title":"A modification to the ASM filter for improving SAR interferograms","authors":"W. B. Abdallah, R. Abdelfattah","doi":"10.5281/ZENODO.43386","DOIUrl":"https://doi.org/10.5281/ZENODO.43386","url":null,"abstract":"SAR Interferograms illustrate an ambiguous (modulo 2π) and noisy phase. In this paper, we focus on the step of interferogram denoising using the Adaptive Switching Median Filter (ASMF) in the wavelet domain. Thus, we propose to filter the coefficients of the relative Discrete Packet Wavelet Transform (DPWT). Our main contribution in this paper concerns firstly, the methodology for computing the mask of noise corresponding to the InSAR phase. Secondly, the size of the median filter is computed considering the noise mask within a given neighborhood and taking into account the corresponding InSAR coherence values. This scheme is tested on simulated noisy interferograms as well as on a given pairs of single look complex (SLC) data from Envisat satellite. Validation was made by computing the Digital Elevation Model after unwrapping the filtered interferogram.","PeriodicalId":400766,"journal":{"name":"21st European Signal Processing Conference (EUSIPCO 2013)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123292265","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
G. Battistelli, L. Chisci, C. Fantacci, A. Farina, A. Graziano
The paper applies a recently developed Consensus Gaussian Mixture - Cardinalized Probability Hypothesis Density (CGM-CPHD) filter to distributed multitarget tracking with range and/or Doppler sensors. It is demonstrated via simulation results on realistic scenarios that the use of Doppler measurements provides a significant tracking performance improvement with respect to using low-accuracy range measurements only. On the other hand, effective distributed Doppler-only multitarget tracking is still an open issue to be investigated.
{"title":"Distributed multitarget tracking with Range-Doppler sensors","authors":"G. Battistelli, L. Chisci, C. Fantacci, A. Farina, A. Graziano","doi":"10.5281/ZENODO.43667","DOIUrl":"https://doi.org/10.5281/ZENODO.43667","url":null,"abstract":"The paper applies a recently developed Consensus Gaussian Mixture - Cardinalized Probability Hypothesis Density (CGM-CPHD) filter to distributed multitarget tracking with range and/or Doppler sensors. It is demonstrated via simulation results on realistic scenarios that the use of Doppler measurements provides a significant tracking performance improvement with respect to using low-accuracy range measurements only. On the other hand, effective distributed Doppler-only multitarget tracking is still an open issue to be investigated.","PeriodicalId":400766,"journal":{"name":"21st European Signal Processing Conference (EUSIPCO 2013)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123306601","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper investigates the discrimination between Photographic Images (PIM) and Computer Generated (CG) images. The proposed method exploits traces of Color Filter Array (CFA) interpolation, present in PIM images, together with the use of hypothesis testing theory. By using the Likelihood Ratio Test (LRT), the method proposed to distinguish PIM from CG images warrants a prescribed False Alarm Rate (FAR) and achieves the maximal detection power. Experimental results show the efficiency of the proposed methodology and the high robustness with respect to anti-forensic techniques.
{"title":"Image authentication by statistical analysis","authors":"T. Qiao, F. Retraint, R. Cogranne","doi":"10.5281/ZENODO.43411","DOIUrl":"https://doi.org/10.5281/ZENODO.43411","url":null,"abstract":"This paper investigates the discrimination between Photographic Images (PIM) and Computer Generated (CG) images. The proposed method exploits traces of Color Filter Array (CFA) interpolation, present in PIM images, together with the use of hypothesis testing theory. By using the Likelihood Ratio Test (LRT), the method proposed to distinguish PIM from CG images warrants a prescribed False Alarm Rate (FAR) and achieves the maximal detection power. Experimental results show the efficiency of the proposed methodology and the high robustness with respect to anti-forensic techniques.","PeriodicalId":400766,"journal":{"name":"21st European Signal Processing Conference (EUSIPCO 2013)","volume":"250 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123584515","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this paper, we examine the time-frequency representation (TFR) and sparse reconstruction of non-stationary signals in the presence of missing data samples. These samples lend themselves to missing entries in the instantaneous auto-correlation function (IAF) which, in turn, induce artifacts in the time-frequency distribution and ambiguity function. The artifacts are additive noise-like and, as such, can be mitigated by using proper time-frequency kernels. We show that the sparse signal reconstruction methods applied to the time-lag domain improve the TFR over the direct application of Fourier transform to the IAF. Additionally, the paper demonstrates that the use of signal-adaptive kernels provides superior performance compared to data-independent kernels when missing data are present.
{"title":"Reduced interference time-frequency representations and sparse reconstruction of undersampled data","authors":"Yimin D. Zhang, M. Amin, B. Himed","doi":"10.5281/ZENODO.43557","DOIUrl":"https://doi.org/10.5281/ZENODO.43557","url":null,"abstract":"In this paper, we examine the time-frequency representation (TFR) and sparse reconstruction of non-stationary signals in the presence of missing data samples. These samples lend themselves to missing entries in the instantaneous auto-correlation function (IAF) which, in turn, induce artifacts in the time-frequency distribution and ambiguity function. The artifacts are additive noise-like and, as such, can be mitigated by using proper time-frequency kernels. We show that the sparse signal reconstruction methods applied to the time-lag domain improve the TFR over the direct application of Fourier transform to the IAF. Additionally, the paper demonstrates that the use of signal-adaptive kernels provides superior performance compared to data-independent kernels when missing data are present.","PeriodicalId":400766,"journal":{"name":"21st European Signal Processing Conference (EUSIPCO 2013)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125553321","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A digital hologram is a 2-D recording of the diffraction fringes created by 3-D objects under coherent lighting. These fringes encode the shape and 3-D location information of the objects. By simulating re-lighting of the hologram, the 3-D wave field can be reconstructed and a volumetric image of the objects recovered. Rather than performing object detection and identification in this reconstructed volume, we consider direct recognition of diffraction-patterns in in-line holograms and show that it leads to superior performance. The huge variability of diffraction patterns with object shape and 3-D location makes diffraction-pattern matching computationally expensive. We suggest the use of a dimensionality reduction technique to circumvent this limitation and show good detection and recognition performance both on simulated and experimental holograms.
{"title":"Fast diffraction-pattern matching for object detection and recognition in digital holograms","authors":"M. Seifi, L. Denis, C. Fournier","doi":"10.5281/ZENODO.43328","DOIUrl":"https://doi.org/10.5281/ZENODO.43328","url":null,"abstract":"A digital hologram is a 2-D recording of the diffraction fringes created by 3-D objects under coherent lighting. These fringes encode the shape and 3-D location information of the objects. By simulating re-lighting of the hologram, the 3-D wave field can be reconstructed and a volumetric image of the objects recovered. Rather than performing object detection and identification in this reconstructed volume, we consider direct recognition of diffraction-patterns in in-line holograms and show that it leads to superior performance. The huge variability of diffraction patterns with object shape and 3-D location makes diffraction-pattern matching computationally expensive. We suggest the use of a dimensionality reduction technique to circumvent this limitation and show good detection and recognition performance both on simulated and experimental holograms.","PeriodicalId":400766,"journal":{"name":"21st European Signal Processing Conference (EUSIPCO 2013)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114499050","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A. Florescu, É. Chouzenoux, J. Pesquet, P. Ciuciu, S. Ciochină
Complex-valued data are encountered in many application areas of signal and image processing. In the context of optimization of functions of real variables, subspace algorithms have recently attracted much interest, due to their efficiency in solving large-size problems while simultaneously offering theoretical convergence guarantees. The goal of this paper is to show how some of these methods can be successfully extended to the complex case. More precisely, we investigate the properties of the proposed complex-valued Majorize-Minimize Memory Gradient (3MG) algorithm. An important practical application of these results arises for image reconstruction in Parallel Magnetic Resonance Imaging (PMRI). Comparisons with existing optimization methods confirm the good performance of our approach for PMRI reconstruction.
{"title":"A complex-valued Majorize-Minimize Memory Gradient method with application to parallel MRI","authors":"A. Florescu, É. Chouzenoux, J. Pesquet, P. Ciuciu, S. Ciochină","doi":"10.5281/ZENODO.43695","DOIUrl":"https://doi.org/10.5281/ZENODO.43695","url":null,"abstract":"Complex-valued data are encountered in many application areas of signal and image processing. In the context of optimization of functions of real variables, subspace algorithms have recently attracted much interest, due to their efficiency in solving large-size problems while simultaneously offering theoretical convergence guarantees. The goal of this paper is to show how some of these methods can be successfully extended to the complex case. More precisely, we investigate the properties of the proposed complex-valued Majorize-Minimize Memory Gradient (3MG) algorithm. An important practical application of these results arises for image reconstruction in Parallel Magnetic Resonance Imaging (PMRI). Comparisons with existing optimization methods confirm the good performance of our approach for PMRI reconstruction.","PeriodicalId":400766,"journal":{"name":"21st European Signal Processing Conference (EUSIPCO 2013)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129624182","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Beampattern synthesis with antenna selection is cast as linear inverse problem (LIP) in this paper and an iterative shrinkage based optimization method is proposed to solve this problem effectively for large antenna array. The proposed method can be used to synthesize arbitrary shaped beampattern, including multibeam forming and radiation suppression within several angular regions. Since the iterative shrinkage method converges much faster compared with other considered methods, null positions can be changed adaptively according to real-time scenarios. In order to balance the trade-off between sidelobe level and null depth, the beampattern synthesis error is reweighted by an emphasis vector. A continuation strategy is also utilised to accelerate convergence rate of the proposed algorithm and the number of selected antennas is controllable by tuning the trade-off parameter value either forward or backward during iteration progress. Numerical results assess efficiency and practicality of the proposed approach for designing non-uniformly spaced arrays adaptively of up to a few hundred antennas.
{"title":"Adaptive beampattern synthesis with antenna selection by Iterative Shrinkage Continuation method","authors":"Xiangrong Wang, E. Aboutanios","doi":"10.5281/ZENODO.43562","DOIUrl":"https://doi.org/10.5281/ZENODO.43562","url":null,"abstract":"Beampattern synthesis with antenna selection is cast as linear inverse problem (LIP) in this paper and an iterative shrinkage based optimization method is proposed to solve this problem effectively for large antenna array. The proposed method can be used to synthesize arbitrary shaped beampattern, including multibeam forming and radiation suppression within several angular regions. Since the iterative shrinkage method converges much faster compared with other considered methods, null positions can be changed adaptively according to real-time scenarios. In order to balance the trade-off between sidelobe level and null depth, the beampattern synthesis error is reweighted by an emphasis vector. A continuation strategy is also utilised to accelerate convergence rate of the proposed algorithm and the number of selected antennas is controllable by tuning the trade-off parameter value either forward or backward during iteration progress. Numerical results assess efficiency and practicality of the proposed approach for designing non-uniformly spaced arrays adaptively of up to a few hundred antennas.","PeriodicalId":400766,"journal":{"name":"21st European Signal Processing Conference (EUSIPCO 2013)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129653592","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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