R.S. Loe, K. Jung, K. Anderson, A. Abatzoglou, J. Regan, H. Arnold, W. Lawton
{"title":"Status report on Wavelets in Signal Detection and Identification: Comparative Processing and Technology Evaluation","authors":"R.S. Loe, K. Jung, K. Anderson, A. Abatzoglou, J. Regan, H. Arnold, W. Lawton","doi":"10.1109/SSAP.1992.246845","DOIUrl":"https://doi.org/10.1109/SSAP.1992.246845","url":null,"abstract":"The goal of this DARPA program is to compare wavelet techniques with a variety of competing transforms such as the short-time Fourier transforms, the Wigner-Ville transform, constrained total least squares and Prony single-valued decomposition. The comparison domain is the detection and identification of passive underwater transient acoustic signals. This paper focuses on the comparison process. Preliminary classification results are shown with the current feature set, based on the analysis of a database collected in the laboratory.<<ETX>>","PeriodicalId":309407,"journal":{"name":"[1992] IEEE Sixth SP Workshop on Statistical Signal and Array Processing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125137901","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":"Estimation of seismic wave parameters by nonlinear regression","authors":"D. Maiwald, J. Bohme","doi":"10.1109/SSAP.1992.246897","DOIUrl":"https://doi.org/10.1109/SSAP.1992.246897","url":null,"abstract":"The authors model data by decaying complex sine waves. The good asymptotic properties of the estimates are verified. The application of the proposed algorithm to real seismic data is reported.<<ETX>>","PeriodicalId":309407,"journal":{"name":"[1992] IEEE Sixth SP Workshop on Statistical Signal and Array Processing","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134575470","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":"Non-Gaussian source localization via exploitation of higher-order cyclostationarity","authors":"G. Giannakis, S. Shamsunder","doi":"10.1109/SSAP.1992.246816","DOIUrl":"https://doi.org/10.1109/SSAP.1992.246816","url":null,"abstract":"Novel direction of arrival (DOA) estimation algorithms which exploits the non-Gaussian and cyclostationary nature of communication signals are explored. The proposed methods employ cyclic higher-order statistics (CHOS) of the array output and suppress additive Gaussian noise of unknown spectral content even when the noise shares common cycle frequencies with the nonGaussian signals of interest. CHOS are tolerant to non-Gaussian interferences with cycle frequencies other than those of the desired signals, and allow one to estimate consistently the DOAs of more sources (per cycle) with fewer sensors.<<ETX>>","PeriodicalId":309407,"journal":{"name":"[1992] IEEE Sixth SP Workshop on Statistical Signal and Array Processing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115901829","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":"An approximate maximum likelihood method for estimation of direction of arrival parameters","authors":"A. Satish, R. Kashyap","doi":"10.1109/SSAP.1992.246780","DOIUrl":"https://doi.org/10.1109/SSAP.1992.246780","url":null,"abstract":"The estimation of DOA and associated signal parameters from the observations received by isotropic sensors in additive noise medium is considered. The DOAs and signal parameters to be estimated are functions of number of snapshots (N), number of sensors(M), signal-to-noise ratio (SNR), separation, phi /sub d/ and correlation between the sources, theta . Different criterion functions for low and for high SNR are obtained by suitable approximations choosing relevant terms depending upon the nature of the parameters. In the first step, expressions are derived for the estimates of the signal power (spectral density in the wideband instance) and noise power. In step two, these are used to estimate the DOA angles. Simulation results for narrowband signals show the performance of the proposed method. The estimation approach could be extended for wideband signals.<<ETX>>","PeriodicalId":309407,"journal":{"name":"[1992] IEEE Sixth SP Workshop on Statistical Signal and Array Processing","volume":"706 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116511742","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":"Constrained ARMA method for magnetic resonance imaging","authors":"M.R. Smith","doi":"10.1109/SSAP.1992.246889","DOIUrl":"https://doi.org/10.1109/SSAP.1992.246889","url":null,"abstract":"Quantitative measurement on medical phantoms has shown that the transient error reconstruction approach (TERA), successfully reintroduces 40% to 50% of truncated energy. This indicates a considerable increase in resolution and reduction in image artifacts. The algorithm is not as successful on normal medical data. This paper suggests an approach to constrain the modeling algorithm to include a priori information and improve the modeling. Preliminary results are presented for a constraint that introduces additional edge information into the TERA algorithm.<<ETX>>","PeriodicalId":309407,"journal":{"name":"[1992] IEEE Sixth SP Workshop on Statistical Signal and Array Processing","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122107390","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":"A theoretical framework for a class of frequency estimation algorithms","authors":"R. Todd, J. R. Cruz","doi":"10.1109/SSAP.1992.246869","DOIUrl":"https://doi.org/10.1109/SSAP.1992.246869","url":null,"abstract":"This paper discusses a general class of algorithms for estimating the frequencies of a set of complex exponentials, and presents a corrected proof of the validity of the algorithms when applied to either real or complex data. The linear-prediction least-squares algorithms, involve the formulation of the estimation problem in terms of finding the roots of a polynomial in C(x) (the vector space of polynomials over the complex numbers C) that has minimum norm with respect to some inner product defined over C(x).<<ETX>>","PeriodicalId":309407,"journal":{"name":"[1992] IEEE Sixth SP Workshop on Statistical Signal and Array Processing","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124510117","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":"Correlation matrix estimation and order selection for spectrum estimation","authors":"W. Du, R. Kirlin","doi":"10.1109/SSAP.1992.246854","DOIUrl":"https://doi.org/10.1109/SSAP.1992.246854","url":null,"abstract":"This paper presents a novel covariance matrix estimator for frequency estimation in time sequence analysis. A preliminary covariance matrix of size M' is first calculated by the sample covariance matrix method, and then the final covariance of size M, with M<or=M' is determined by employing all available correlation information in the preliminary estimate. Generally the new covariance estimator can more effectively utilize temporal correlations among the data and provides more trade-off freedom in order selection. When the orders (sizes) of the covariance matrices are properly selected, this new estimator can obtain a statistically more stable estimate of covariance matrix than the conventional approach.<<ETX>>","PeriodicalId":309407,"journal":{"name":"[1992] IEEE Sixth SP Workshop on Statistical Signal and Array Processing","volume":"102 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114528134","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":"Electromagnetic vector sensor processing in the wave frame","authors":"A. Nehorai, E. Paldi","doi":"10.1109/SSAP.1992.246783","DOIUrl":"https://doi.org/10.1109/SSAP.1992.246783","url":null,"abstract":"The authors introduce a wave frame model and define the covariance of vector angular frame model (CVAE) in this frame. A lower bound is derived on the CVAE for source direction and orientation estimation. An explicit expression for the CVAE matrix bound is found to be diagonal, easy to interpret, and having only intrinsic singularities. A relationship is also provided between the CVAE and the mean-square angular error quality measure.<<ETX>>","PeriodicalId":309407,"journal":{"name":"[1992] IEEE Sixth SP Workshop on Statistical Signal and Array Processing","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129802823","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":"Instantaneous bandwidth and formant bandwidth","authors":"L. Cohen, K. Assaleh, A. Fineberg","doi":"10.1109/SSAP.1992.246837","DOIUrl":"https://doi.org/10.1109/SSAP.1992.246837","url":null,"abstract":"The concept of instantaneous bandwidth introduced by Cohen and Lee (1990) is used to explain 'formant bandwidth' as used in speech analysis. An explicit expression for the formant bandwidth in terms of the parameters of the components of the speech signal is given. The result is verified using real and simulated speech signals and a simple plausibility argument is given. It is argued that instantaneous bandwidth has greater applicability since it does not have to be defined only within a pitch period.<<ETX>>","PeriodicalId":309407,"journal":{"name":"[1992] IEEE Sixth SP Workshop on Statistical Signal and Array Processing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129632689","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":"Optimal array signal processing in unknown noise environments via parametric approaches","authors":"Qiang Wu, K. M. Wong, J. Reilly","doi":"10.1117/12.130934","DOIUrl":"https://doi.org/10.1117/12.130934","url":null,"abstract":"Under the assumption that noise correlation is spatially limited, using two separated arrays, the authors propose a new parametric approach for consistent directions-of-arrival estimations in unknown noise environments. The theoretical performance analysis of the proposed DOA estimations is presented. With the use of the theoretical performance, the best weighting matrices of the parametric criteria have been derived. More significantly, it has been shown that within the best weighted criteria, using canonical decomposition, one can achieve optimal performance among a large set of eigendecompositions.<<ETX>>","PeriodicalId":309407,"journal":{"name":"[1992] IEEE Sixth SP Workshop on Statistical Signal and Array Processing","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128460307","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}