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Viberg, Mats, et al.
(författare)
Sensor Array Processing based on Subspace Fitting
1989
Rapport (övrigt vetenskapligt/konstnärligt) abstract
Algorithms for estimating unknown signal parameters from the measured output of a sensor array are considered in connection with the subspace fitting problem. The methods considered are the deterministic maximum likelihood method (ML), ESPRIT, and a recently proposed multidimensional signal subspace method. These methods are formulated in a subspace-fitting-based framework, which provides insight into their algebraic and asymptotic relations. It is shown that by introducing a specific weighting matrix, the multidimensional signal subspace method can achieve the same asymptotic properties as the ML method. The asymptotic distribution of the estimation error is derived for a general subspace weighting, and the weighting that provides minimum variance estimates is identified. The resulting optimal technique is termed the weighted subspace fitting (WSF) method. Numerical examples indicate that the asymptotic variance of the WSF estimates coincides with the Cramer-Rao bound. The performance improvement compared to the other techniques is found to be most prominent for highly correlated signals.
4.
Ottersten, Björn, et al.
(författare)
Stochastic maximum likelihood estimation in sensor arrays by weighted subspace fitting
1989
Ingår i: Conference Record - Asilomar Conference on Circuits, Systems & Computers. - Pacific Grove, CA, USA : Linköping University. ; , s. 599-603, s. 599-603
Konferensbidrag (refereegranskat) abstract
The problem of estimating parameters of multiple narrowband emitter signals from sensor array data is considered. Under the assumption of Gaussian distributed emitter signals, the stochastic maximum-likelihood (ML) technique is known to provide statistically efficient estimates, i.e., it achieves the Cramer-Rao bound (CRB). A multidimensional signal subspace method, termed weighted subspace fitting (WSF), has recently been proposed. It is shown that the WSF and ML estimates are asymptotically identical (for large data records). As a consequence, the WSF method is asymptotically efficient, assuming temporally white Gaussian signal waveforms and noise.
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Ottersten, Björn, et al.
(författare)
Asymptotic Results for Sensor Array Processing
1989
Ingår i: Proceedings of the 1989 International Conference on Acoustics, Speech and Signal Processing. - Linköping : Linköping University. ; , s. 2266-2269
Rapport (övrigt vetenskapligt/konstnärligt) abstract
The emphasis of this study is on direction-of-arrival (DOA) estimation of narrowband emitter signals. There are two main signal models that have been used in the sensor array problem, namely, stochastic and deterministic. A discussion is presented of the models, their effect on the Cramer-Rao lower bounds (CRB), cases where the maximum likelihood (ML) estimator asymptotically achieves this bound, and how the bounds are related. It is shown that the asymptotic variance of the ML method based on the stochastic model is lower than that of the ML method based on the deterministic model. The stochastic ML variance and CRB are based on the assumption of Gaussian emitter signals, which can be an unrealistic assumption when narrowband signals are assumed. The authors show that the ML estimator based on the Gaussian signal model achieves the stochastic CRB asymptotically, regardless of the signal distribution. Numerical evaluations of the theoretical variances for different scenarios are presented to clarify the relationship between the methods and bounds discussed.
6.
Viberg, Mats, et al.
(författare)
Detection and Estimation in Sensor Arrays using Weighted Subspace Fitting
1989
Rapport (övrigt vetenskapligt/konstnärligt) abstract
The problem of signal parameter estimation of narrowband emitter signals impinging on an array of sensors is addressed. A multidimensional estimation procedure that applies to arbitrary array structures and signal correlation is proposed. The method is based on the recently introduced weighted subspace fitting (WSF) criterion and includes schemes for both detecting the number of sources and estimating the signal parameters. A Gauss-Newton-type method is presented for solving the multidimensional WSF and maximum-likelihood optimization problems. The global and local properties of the search procedure are investigated through computer simulations. Most methods require knowledge of the number of coherent/noncoherent signals present. A scheme for consistently estimating this is proposed based on an asymptotic analysis of the WSF cost function. The performance of the detection scheme is also investigated through simulations.
7.
Ottersten, Björn, et al.
(författare)
Analysis of Subspace Fitting based Methods for Sensor Array Processing
1989
Ingår i: Proceedings of the 1989 International Conference on Acoustics, Speech and Signal Processing. - Linköping : Linköping University. ; , s. 2807-2810
Konferensbidrag (refereegranskat) abstract
The problem of estimating signal parameters from sensor array measurements is addressed. A general multidimensional signal subspace method, called the weighted subspace fitting (WSF) method, is proposed. The relationship of WSF to other signal subspace methods as well as the relation to the deterministic maximum-likelihood (ML) method is discussed. The asymptotic properties of WSF are presented for a general weighting. This result includes the properties of ML as a special case. The weighting that minimizes the estimation error covariance is given, resulting in a method that always outperforms ML. A numerical example is presented, demonstrating that the optimally weighted WSF method can give notably lower variance for highly correlated signals. Simulations are included to substantiate the analysis.
8.
Lindeberg, Tony, 1964-
(författare)
Scale-space for discrete images
1989
Ingår i: Scandinavian Conference on Image Analysis. ; , s. 1098-1107
Konferensbidrag (refereegranskat) abstract
This article addresses the formulation of a scale-space theory for one-dimensional discrete images. Two main subjects are treated:Which linear transformations remove structure in the sense that the number of local extrema (or zero-crossings) in the output image does not exceed the number of local extrema (or zero-crossings) in the original image?How should one create a multi-resolution family of representations with the property that an image at a coarser level of scale never contains more structure than an image at a finer level of scale?We propose that there is only one reasonable way to define a scale-space for discrete images comprising a continuous scale parameter, namely by (discrete) convolution with the family of kernels T(n; t) = e^{-t} I_n(t),, where $I_n$ are the modified Bessel functions of integer order. Similar arguments applied in the continuous case uniquely lead to the Gaussian kernel.Some obvious discretizations of the continuous scale-space theory are discussed in view of the results presented. An important result is that scale-space violations might occur in the family of representations generated by discrete convolution with the sampled Gaussian kernel.
9.
Leblanc, James, et al.
(författare)
Management unit for reliable power supply stations for use in telecommunication facilities
1989
Ingår i: Eleventh International Telecommunications Energy Conference. INTELEC '89. Conference Proceedings. - Poscataway, NJ : IEEE Communications Society. ; , s. 9.3/1-9.3/4
Konferensbidrag (refereegranskat) abstract
Following a general presentation of the system architectures for two types of reliable energy stations, GEODE and ALFATEL, used in telecommunication facilities, the authors describe the concept of a centralized management system covering several energy stations situated at different geographical locations. The role of communication with the power supply station monitoring units is then described. This makes it possible to define the functions carried out by the management unit, some of which may be operated through remote control by staff on standby duty. The functions of remote monitoring of processes, statistical studies, inventories, background records, man/machine relationships, and maintenance assistance are backed up by a PC-type machine .
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