{"title":"CS based specular multipath exploitation in TWRI under wall position uncertainties","authors":"M. Leigsnering, F. Ahmad, M. Amin, A. Zoubir","doi":"10.1109/SAM.2014.6882447","DOIUrl":"https://doi.org/10.1109/SAM.2014.6882447","url":null,"abstract":"Through-the-wall radar imaging utilizes electromagnetic wave propagation to reveal the locations of obscured targets. Indirect signal propagation paths, usually considered a nuisance, may be used to improve the quality of through-the-wall radar images. However, imperfect knowledge of the surrounding scatterers, i.e. the interior walls of a building, has adverse effects on such multipath exploitation schemes. We propose a joint scene reconstruction and wall position estimation approach based on compressive sensing. This enables effective and reliable utilization of indirect propagation paths resulting in clutter-free images of stationary indoor scenes. Simulation results demonstrate the effectiveness of the proposed method.","PeriodicalId":141678,"journal":{"name":"2014 IEEE 8th Sensor Array and Multichannel Signal Processing Workshop (SAM)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124790560","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}
{"title":"Deterministic blind identification in antenna array processing","authors":"Souleymen Sahnoun, P. Comon","doi":"10.1109/SAM.2014.6882433","DOIUrl":"https://doi.org/10.1109/SAM.2014.6882433","url":null,"abstract":"The estimation of directions of arrival is formulated as the decomposition of a 3-way array into a sum of rank-one terms. However, a low-rank tensor approximation does not always exist. We propose an optimization technique based on differentiable angular constraints on the factors, ensuring the existence of the low-rank tensor decomposition. The efficiency of the proposed algorithm is demonstrated via numerical simulations, and compared to Cramér-Rao bounds.","PeriodicalId":141678,"journal":{"name":"2014 IEEE 8th Sensor Array and Multichannel Signal Processing Workshop (SAM)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122102979","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}
R. Boloix-Tortosa, F. J. Payan-Somet, J. J. Murillo-Fuentes
{"title":"Gaussian processes regressors for complex proper signals in digital communications","authors":"R. Boloix-Tortosa, F. J. Payan-Somet, J. J. Murillo-Fuentes","doi":"10.1109/SAM.2014.6882359","DOIUrl":"https://doi.org/10.1109/SAM.2014.6882359","url":null,"abstract":"In this paper we develop the complex-valued version of the Gaussian processes for regression (GPR) for proper complex signals. This tool has proved to be useful in the nonlinear detection in digital communications in real valued models. GPRs can be cast as nonlinear MMSE where hyperparameters can be tuned optimizing a marginal likelihood (ML). This feature allows for a flexible kernel that can easily adapt either to a linear or nonlinear solution. We introduce the complex-valued form of the GPR, and develop it for the proper complex case. We also deal with the optimization of the ML. Some experiments included illustrate the good performance of the proposal.","PeriodicalId":141678,"journal":{"name":"2014 IEEE 8th Sensor Array and Multichannel Signal Processing Workshop (SAM)","volume":"125 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126102812","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}
H. Achanta, Sampurna Biswas, S. Dasgupta, M. Jacob, Bhanumati N. Dasgupta, R. Mudumbai
{"title":"Coprime conditions for Fourier sampling for sparse recovery","authors":"H. Achanta, Sampurna Biswas, S. Dasgupta, M. Jacob, Bhanumati N. Dasgupta, R. Mudumbai","doi":"10.1109/SAM.2014.6882460","DOIUrl":"https://doi.org/10.1109/SAM.2014.6882460","url":null,"abstract":"This paper considers the spark of L × N submatrices of the N × N Discrete Fourier Transform (DFT) matrix. Here a matrix has spark m if every collection of its m - 1 columns are linearly independent. The motivation comes from such applications of compressed sensing as MRI and synthetic aperture radar, where device physics dictates the measurements to be Fourier samples of the signal. Consequently the observation matrix comprises certain rows of the DFT matrix. To recover an arbitrary k-sparse signal, the spark of the observation matrix must exceed 2k + 1. The technical question addressed in this paper is how to choose the rows of the DFT matrix so that its spark equals the maximum possible value L + 1. We expose certain coprimeness conditions that guarantee such a property.","PeriodicalId":141678,"journal":{"name":"2014 IEEE 8th Sensor Array and Multichannel Signal Processing Workshop (SAM)","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122385114","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}
{"title":"Localization and array shape estimation using software defined radio array testbed","authors":"Akinbiyi Akindoyin, Marc Willerton, A. Manikas","doi":"10.1109/SAM.2014.6882372","DOIUrl":"https://doi.org/10.1109/SAM.2014.6882372","url":null,"abstract":"The emergence of software defined radio (SDR) aims to increase flexibility as well as reduce cost, size, weight and power (SWAP) inherent in traditional hardware radios. This paper is concerned with addressing issues associated with the formation of an array system from multiple SDR boards where each has an independent local oscillators (LO) in a multi-antenna system using representative examples such as localization and array shape estimation. In particular, practical experimental results are initially presented for estimating the unknown location of a single source using an SDR array of known array geometry. Furthermore, in the case that the SDR array geometry is unknown, a novel array shape estimation algorithm is proposed. The proposed algorithm estimates the antenna locations without requiring any external sources. This is achieved by allowing the array elements operate as transceivers.","PeriodicalId":141678,"journal":{"name":"2014 IEEE 8th Sensor Array and Multichannel Signal Processing Workshop (SAM)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116321236","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}
J. Rodríguez-Piñeiro, Pedro Suárez-Casal, J. García-Naya, L. Castedo, C. Briso-Rodríguez, J. Alonso
{"title":"Experimental validation of ICI-Aware OFDM receivers under time-varying conditions","authors":"J. Rodríguez-Piñeiro, Pedro Suárez-Casal, J. García-Naya, L. Castedo, C. Briso-Rodríguez, J. Alonso","doi":"10.1109/SAM.2014.6882411","DOIUrl":"https://doi.org/10.1109/SAM.2014.6882411","url":null,"abstract":"Orthogonal Frequency Division Multiplexing (OFDM) communications under highly time-selective channels are severely affected by Inter-Carrier Interference (ICI). Estimation and cancellation of ICI in OFDM systems has been thoroughly studied, but few empirical measurements of the performance of such techniques have been done. We present a wireless communication testbed and a methodology to evaluate the performance of OFDM transmissions in real-world scenarios affected by large Doppler spreads. We show that it is possible to induce such large Doppler spreads while conducting experiments with a moving vehicle at a low speed.","PeriodicalId":141678,"journal":{"name":"2014 IEEE 8th Sensor Array and Multichannel Signal Processing Workshop (SAM)","volume":"92 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127055506","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}
{"title":"Scalar-gain distributed estimators for Hermitian systems","authors":"U. Khan","doi":"10.1109/SAM.2014.6882378","DOIUrl":"https://doi.org/10.1109/SAM.2014.6882378","url":null,"abstract":"In this paper, we consider distributed estimation of discrete-time, LTI state-spaces, restricted to Hermitian (or symmetric) system matrices. We assume that the underlying system is monitored by a group of agents, sparsely connected via an undirected communication graph, and no agent may possess enough measurements (in its neighborhood) to estimate the entire state-vector. In this context, we analyze an estimation protocol that only requires a single design parameter: a scalar-gain, α ∈ R. We design this scalar-gain, α, with the help of some eigenvalue (Weyl's) inequalities and derive the conditions under which a scalar-gain is sufficient to estimate the underlying system with bounded estimation error.","PeriodicalId":141678,"journal":{"name":"2014 IEEE 8th Sensor Array and Multichannel Signal Processing Workshop (SAM)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128788318","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}
{"title":"Truncated nuclear norm minimization for tensor completion","authors":"Longting Huang, H. So, Yuan Chen, Wen-qin Wang","doi":"10.1109/SAM.2014.6882431","DOIUrl":"https://doi.org/10.1109/SAM.2014.6882431","url":null,"abstract":"In this paper, a tensor n-mode matrix unfolding truncated nuclear norm is proposed, which is extended from the matrix truncated nuclear norm, to tensor completion problem. The alternating direction method of multipliers is utilized to solve this optimization problem. Meanwhile, the original two-step solution of the matrix truncated nuclear norm is reduced to one step. Employing the intermediate results returned by singular value shrinkage operator, rank information of each tensor unfolding matrix is not required and thus the computational complexity of the devised approach is not demanding. Computer simulation results demonstrate the effectiveness of the proposed method.","PeriodicalId":141678,"journal":{"name":"2014 IEEE 8th Sensor Array and Multichannel Signal Processing Workshop (SAM)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122186413","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}
{"title":"State estimation with sampling offsets in Wide Area Measurement Systems","authors":"Hoi-To Wai, A. Scaglione","doi":"10.1109/SAM.2014.6882335","DOIUrl":"https://doi.org/10.1109/SAM.2014.6882335","url":null,"abstract":"An implicit assumption made in studies on state estimation is that the time and frequency at which these measurements are taken is consistent across all the distributed sensing sites. For instance, in the literatures on Wide Area Measurement Systems (WAMS) deployed in the power grid, where the sensors equipped with Global Positioning Signals (GPS), the sensing sites are deemed capable to provide perfectly synchronous readings at the various sampling sites. The validity of the assumption may need to be re-examined with the recent advancements in decentralized state estimation algorithms. Importantly, when there are timing offsets between sampling devices, the effects on the measurement system's performance can be catastrophic. The prevalent point of view is to either study the resulting error, or to resort to Kalman filtering for aligning the measurements. Taking on this view typically requires additional information about the underlying state. In this paper, we revisit the problem of state estimation and propose a new model for data acquisition under asynchronous sampling. The key idea is to apply sampling theory and to exploit the redundancy in the spatial sampling to interpolate the system state. We provide a necessary and sufficient condition for identifiability of the time offsets and propose an algorithm for the joint regression on state and timing offsets. The efficacy of the proposed algorithm is shown by numerical simulations.","PeriodicalId":141678,"journal":{"name":"2014 IEEE 8th Sensor Array and Multichannel Signal Processing Workshop (SAM)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130735132","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}
{"title":"Bandwidth expansion analog joint source-channel coding with channel inversion and multiple receive antennas","authors":"E. Hodgson, G. Brante, R. Souza, J. Garcia-Frías","doi":"10.1109/SAM.2014.6882388","DOIUrl":"https://doi.org/10.1109/SAM.2014.6882388","url":null,"abstract":"We investigate the performance of bandwidth expansion analog joint source-channel coding (JSCC) over fading channels. Non-linear spiral-like curves and maximum likelihood detector with linear minimum mean square error estimator are considered. Under Rayleigh fading this scheme presents a gap to the theoretical limit which increases with the channel signal to noise ratio (CSNR), while the same scheme on additive white Gaussian noise (AWGN) channel presents much smaller gap. This is completely different from bandwidth compression, where the performance in both fading and AWGN channels is close to optimal. We present two strategies that can make bandwidth expansion analog JSCC more feasible: channel inversion and receive diversity. The first requires channel state information at the transmitter, while the second does not. Both strategies are shown to considerably reduce the gap to the theoretical limit.","PeriodicalId":141678,"journal":{"name":"2014 IEEE 8th Sensor Array and Multichannel Signal Processing Workshop (SAM)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116607630","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}