Pub Date : 1992-10-07DOI: 10.1109/SSAP.1992.246864
J.M.M. Anderson, G. Giannakis
Given a single record, the authors consider the problem of estimating the harmonics of a signal buried in noise. The observed data is modeled as a superposition of sinusoids plus stationary, zero-mean additive Gaussian noise of unknown covariance. Novel higher-order statistics, referred to as 'mixed' cumulants, are appropriate for certain types of mixed processes. After a consistent HOS-based linear estimate, an improved estimate is computed via mixed-cumulant matching. Issues regarding quadratic coupling are addressed. The performance of the proposed method is examined via simulations.<>
{"title":"HOS-based harmonic retrieval: a deterministic formulation","authors":"J.M.M. Anderson, G. Giannakis","doi":"10.1109/SSAP.1992.246864","DOIUrl":"https://doi.org/10.1109/SSAP.1992.246864","url":null,"abstract":"Given a single record, the authors consider the problem of estimating the harmonics of a signal buried in noise. The observed data is modeled as a superposition of sinusoids plus stationary, zero-mean additive Gaussian noise of unknown covariance. Novel higher-order statistics, referred to as 'mixed' cumulants, are appropriate for certain types of mixed processes. After a consistent HOS-based linear estimate, an improved estimate is computed via mixed-cumulant matching. Issues regarding quadratic coupling are addressed. The performance of the proposed method is examined via simulations.<<ETX>>","PeriodicalId":309407,"journal":{"name":"[1992] IEEE Sixth SP Workshop on Statistical Signal and Array Processing","volume":"49 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":"132136755","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 : 1992-10-07DOI: 10.1109/SSAP.1992.246859
L.D. Rankin, E. Kesler, T. Dyson
A novel approach to the detection and estimation of directional signals incident upon a linear array of sensors uses the diverse dimensions of the array polynomials associated with the statistically independent beams output by the adaptive Gram-Schmidt processor. Zero patterns generated by these polynomials provide the information necessary to detect the number of incident signals and estimate their angles of arrival. L/sup 2/ norms based on phase differences between zeros in observed pairs of beams are critical in the detection process. Monte-Carlo results compare the performance of the proposed method with that of the Root MUSIC algorithm for one signal and two closely spaced signals in white stationary noise. These results cover varying SNR, number of snapshots, and signal spacing for the two signals. Single trial results for multiple strong jammers are presented.<>
{"title":"A novel use of Gram-Schmidt for detection and estimation","authors":"L.D. Rankin, E. Kesler, T. Dyson","doi":"10.1109/SSAP.1992.246859","DOIUrl":"https://doi.org/10.1109/SSAP.1992.246859","url":null,"abstract":"A novel approach to the detection and estimation of directional signals incident upon a linear array of sensors uses the diverse dimensions of the array polynomials associated with the statistically independent beams output by the adaptive Gram-Schmidt processor. Zero patterns generated by these polynomials provide the information necessary to detect the number of incident signals and estimate their angles of arrival. L/sup 2/ norms based on phase differences between zeros in observed pairs of beams are critical in the detection process. Monte-Carlo results compare the performance of the proposed method with that of the Root MUSIC algorithm for one signal and two closely spaced signals in white stationary noise. These results cover varying SNR, number of snapshots, and signal spacing for the two signals. Single trial results for multiple strong jammers are presented.<<ETX>>","PeriodicalId":309407,"journal":{"name":"[1992] IEEE Sixth SP Workshop on Statistical Signal and Array Processing","volume":"43 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":"131461002","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 : 1992-10-07DOI: 10.1109/SSAP.1992.246818
Eric Moulines, K. Choukri, M. Sharbit
These tests are based on quadratic form in deviations of certain sample statistics from their ensemble counterpart, minimised with respect to the unknown parameters. They are shown to converge under the null hypothesis to a chi-squared distribution. A specific test is developed on the basis of the difference between the sample estimate and the ensemble average characteristic functions. Preliminary results demonstrate the discriminative power of the test against various types of alternatives.<>
{"title":"Testing that a multivariate stationary time-series is Gaussian","authors":"Eric Moulines, K. Choukri, M. Sharbit","doi":"10.1109/SSAP.1992.246818","DOIUrl":"https://doi.org/10.1109/SSAP.1992.246818","url":null,"abstract":"These tests are based on quadratic form in deviations of certain sample statistics from their ensemble counterpart, minimised with respect to the unknown parameters. They are shown to converge under the null hypothesis to a chi-squared distribution. A specific test is developed on the basis of the difference between the sample estimate and the ensemble average characteristic functions. Preliminary results demonstrate the discriminative power of the test against various types of alternatives.<<ETX>>","PeriodicalId":309407,"journal":{"name":"[1992] IEEE Sixth SP Workshop on Statistical Signal and Array Processing","volume":"2 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":"129424285","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 : 1992-10-07DOI: 10.1109/SSAP.1992.246820
N. Harned, H. M. Valenzuela
The paper focuses on the problem of a returning active sonar signal masked by environmental background noise. According to theory, if the original signal is sufficiently non-Gaussian the bispectrum of the received signal-plus-noise will contain only information due to the signal, and the white Gaussian noise will be suppressed. A bispectrum detector has been developed which utilizes the a priori knowledge of the input active sonar signal by selecting regions of the bispectral domain where the magnitude exceeds a significance test threshold. The presence of the returning sonar signal in noise is then detected by measuring bispectral content in those regions. Linear FM (chirp) signals of several frequencies and sweep ranges are generated to simulate active sonar input, and corrupted by additive white Gaussian noise to produce various signal-to-noise ratios. Receiver Operating Characteristic curves for these signals demonstrate that this new detector provides gain over a bispectrum detection method previously presented in the literature. Detection results are presented for the original signals with additional multipath returns.<>
{"title":"Detection of active linear FM sonar signals using the bispectrum","authors":"N. Harned, H. M. Valenzuela","doi":"10.1109/SSAP.1992.246820","DOIUrl":"https://doi.org/10.1109/SSAP.1992.246820","url":null,"abstract":"The paper focuses on the problem of a returning active sonar signal masked by environmental background noise. According to theory, if the original signal is sufficiently non-Gaussian the bispectrum of the received signal-plus-noise will contain only information due to the signal, and the white Gaussian noise will be suppressed. A bispectrum detector has been developed which utilizes the a priori knowledge of the input active sonar signal by selecting regions of the bispectral domain where the magnitude exceeds a significance test threshold. The presence of the returning sonar signal in noise is then detected by measuring bispectral content in those regions. Linear FM (chirp) signals of several frequencies and sweep ranges are generated to simulate active sonar input, and corrupted by additive white Gaussian noise to produce various signal-to-noise ratios. Receiver Operating Characteristic curves for these signals demonstrate that this new detector provides gain over a bispectrum detection method previously presented in the literature. Detection results are presented for the original signals with additional multipath returns.<<ETX>>","PeriodicalId":309407,"journal":{"name":"[1992] IEEE Sixth SP Workshop on Statistical Signal and Array Processing","volume":"52 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":"121856249","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 : 1992-10-07DOI: 10.1109/SSAP.1992.246806
L. G. Weiss, R. K. Young
For a nearfield sensor array, wideband signals, and moving scatterers or sensors, beamforming may not be valid. The signals received at different sensors may no longer be delayed versions of one another. To localize wideband, nearfield, and/or moving sources, a wideband spatial processor is presented. Applicable to both active and passive processing, it relies on a new relation that expresses the wideband correlation receiver output as an affine convolution of two wavelet transforms; the wideband spreading function is convolved with an auto ambiguity function. This new expression is then deconvolved to obtain a high resolution estimate of the wideband spreading function.<>
{"title":"Wideband spatial processing with wavelet transforms","authors":"L. G. Weiss, R. K. Young","doi":"10.1109/SSAP.1992.246806","DOIUrl":"https://doi.org/10.1109/SSAP.1992.246806","url":null,"abstract":"For a nearfield sensor array, wideband signals, and moving scatterers or sensors, beamforming may not be valid. The signals received at different sensors may no longer be delayed versions of one another. To localize wideband, nearfield, and/or moving sources, a wideband spatial processor is presented. Applicable to both active and passive processing, it relies on a new relation that expresses the wideband correlation receiver output as an affine convolution of two wavelet transforms; the wideband spreading function is convolved with an auto ambiguity function. This new expression is then deconvolved to obtain a high resolution estimate of the wideband spreading function.<<ETX>>","PeriodicalId":309407,"journal":{"name":"[1992] IEEE Sixth SP Workshop on Statistical Signal and Array Processing","volume":"55 7","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113981288","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 : 1992-10-07DOI: 10.1109/SSAP.1992.246865
C. Zala, J. Ozard
Matched-field processing of underwater acoustic array data requires a knowledge of the environment and the use of a suitable propagation model from which field replicas can be computed. For range-dependent environment, parabolic equation or mode-based propagation modelling techniques may be used to provide these replicas. A comparison is presented for environments with sloping bottoms, using the order 3 Pade wide angle approximation for the parabolic equation to ensure precision. The numerical simulations involved generation of 'measured' covariance matrices using PE fields; these were then matched with replicas computed using adiabatic modes. The results showed that for slopes up to 2 degrees , the two techniques yield similar matches, but the adiabatic model provides up to a 100-fold speed advantage.<>
{"title":"Comparison of parabolic equation and adiabatic mode propagation models for matched-field processing in range-dependent environments","authors":"C. Zala, J. Ozard","doi":"10.1109/SSAP.1992.246865","DOIUrl":"https://doi.org/10.1109/SSAP.1992.246865","url":null,"abstract":"Matched-field processing of underwater acoustic array data requires a knowledge of the environment and the use of a suitable propagation model from which field replicas can be computed. For range-dependent environment, parabolic equation or mode-based propagation modelling techniques may be used to provide these replicas. A comparison is presented for environments with sloping bottoms, using the order 3 Pade wide angle approximation for the parabolic equation to ensure precision. The numerical simulations involved generation of 'measured' covariance matrices using PE fields; these were then matched with replicas computed using adiabatic modes. The results showed that for slopes up to 2 degrees , the two techniques yield similar matches, but the adiabatic model provides up to a 100-fold speed advantage.<<ETX>>","PeriodicalId":309407,"journal":{"name":"[1992] IEEE Sixth SP Workshop on Statistical Signal and Array Processing","volume":"13 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":"117184786","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 : 1992-10-07DOI: 10.1109/SSAP.1992.246782
S. Sathyanarayana Rao, R. Raman
Xu and Kailath have proposed (1992) a fast algorithm for signal subspace decomposition that exploits the special matrix structure associated with signal subspace algorithms. This work presents some modifications which eliminate the need to estimate the noise eigenvalue in order to estimate the orthonormal basis of an ideal covariance matrix. The algorithm yields the exact signal subspace and in so doing yields the exact subspace dimension. The modifications presented reduce the computational load by at least a factor of four.<>
{"title":"Signal subspace decomposition of ideal covariance matrices","authors":"S. Sathyanarayana Rao, R. Raman","doi":"10.1109/SSAP.1992.246782","DOIUrl":"https://doi.org/10.1109/SSAP.1992.246782","url":null,"abstract":"Xu and Kailath have proposed (1992) a fast algorithm for signal subspace decomposition that exploits the special matrix structure associated with signal subspace algorithms. This work presents some modifications which eliminate the need to estimate the noise eigenvalue in order to estimate the orthonormal basis of an ideal covariance matrix. The algorithm yields the exact signal subspace and in so doing yields the exact subspace dimension. The modifications presented reduce the computational load by at least a factor of four.<<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":"127434823","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 : 1992-10-07DOI: 10.1109/SSAP.1992.246773
C. Tsai, J. Yang
The authors formulate the wideband minimum variance distortionless response (MVDR) as the auto-focusing criterion. By emulation results of single-group and multi-group sources, they show that the optimal focusing angles can achieve the wideband MVDR criterion and result in minimum output power of the beamformer. The steepest descent algorithm is suggested for iteratively updating the focusing angles for beamformers to null both stationary and nonstationary interferences. For direction finding applications, the same auto-focusing procedures can be applied directly by presuming a dummy looking direction. Simulation results show that the performances of beamforming and direction finding applications are greatly improved by the proposed auto-focusing algorithm.<>
{"title":"Auto-focusing and tracking techniques for enhancement of coherent signal-subspace methods","authors":"C. Tsai, J. Yang","doi":"10.1109/SSAP.1992.246773","DOIUrl":"https://doi.org/10.1109/SSAP.1992.246773","url":null,"abstract":"The authors formulate the wideband minimum variance distortionless response (MVDR) as the auto-focusing criterion. By emulation results of single-group and multi-group sources, they show that the optimal focusing angles can achieve the wideband MVDR criterion and result in minimum output power of the beamformer. The steepest descent algorithm is suggested for iteratively updating the focusing angles for beamformers to null both stationary and nonstationary interferences. For direction finding applications, the same auto-focusing procedures can be applied directly by presuming a dummy looking direction. Simulation results show that the performances of beamforming and direction finding applications are greatly improved by the proposed auto-focusing algorithm.<<ETX>>","PeriodicalId":309407,"journal":{"name":"[1992] IEEE Sixth SP Workshop on Statistical Signal and Array Processing","volume":"30 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":"126416647","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 : 1992-10-07DOI: 10.1109/SSAP.1992.246856
M. Shao, C. Nikias
An important class of statistical models for nonGaussian phenomena is that of so-called heavy-tailed distributions, whose density functions decay in the tails less rapidly than the Gaussian density function. These distributions tend to produce large-amplitude excursions from the average value more frequently than the Gaussian distribution. Among all the heavy-tailed distributions, the family of stable distributions has been found to provide useful models for phenomena observed in many diverse fields, such as economics, physics and electrical engineering. It is capable of modeling a wide variety of nonGaussian phenomena, from those similar to the Gaussian to those similar to the Cauchy. This paper presents some preliminary results on signal detection and estimation under the nonGaussian stable assumption.<>
{"title":"Detection and adaptive estimation of stable processes with fractional lower-order moments","authors":"M. Shao, C. Nikias","doi":"10.1109/SSAP.1992.246856","DOIUrl":"https://doi.org/10.1109/SSAP.1992.246856","url":null,"abstract":"An important class of statistical models for nonGaussian phenomena is that of so-called heavy-tailed distributions, whose density functions decay in the tails less rapidly than the Gaussian density function. These distributions tend to produce large-amplitude excursions from the average value more frequently than the Gaussian distribution. Among all the heavy-tailed distributions, the family of stable distributions has been found to provide useful models for phenomena observed in many diverse fields, such as economics, physics and electrical engineering. It is capable of modeling a wide variety of nonGaussian phenomena, from those similar to the Gaussian to those similar to the Cauchy. This paper presents some preliminary results on signal detection and estimation under the nonGaussian stable assumption.<<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":"125862921","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 : 1992-10-07DOI: 10.1109/SSAP.1992.246803
E.J. Baranoski
A new source-independent subspace technique for adaptive array processing applications incorporates sidelobe control in the subspace selection process. The subspace is determined solely by the desired mainbeam width and a priori knowledge of the array manifold, and is therefore independent of the directional interference environment. This technique achieves significant computational savings since a data-dependent subspace does not have to computed. Due to the subspace construction, the algorithm provides enhanced sidelobe control while still achieving nulling performance comparable with other subspace techniques.<>
{"title":"Source-independent subspace projection","authors":"E.J. Baranoski","doi":"10.1109/SSAP.1992.246803","DOIUrl":"https://doi.org/10.1109/SSAP.1992.246803","url":null,"abstract":"A new source-independent subspace technique for adaptive array processing applications incorporates sidelobe control in the subspace selection process. The subspace is determined solely by the desired mainbeam width and a priori knowledge of the array manifold, and is therefore independent of the directional interference environment. This technique achieves significant computational savings since a data-dependent subspace does not have to computed. Due to the subspace construction, the algorithm provides enhanced sidelobe control while still achieving nulling performance comparable with other subspace techniques.<<ETX>>","PeriodicalId":309407,"journal":{"name":"[1992] IEEE Sixth SP Workshop on Statistical Signal and Array Processing","volume":"69 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":"125197262","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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