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11
Gain Calibration Methods for Radio Telescope Arrays
 IEEE Tr. Signal Processing
, 2003
"... In radio telescope arrays, the complex receiver gains and sensor noise powers are initially unknown and have to be calibrated. Gain calibration can enhance the quality of astronomical sky images and, moreover, improve the effectiveness of array signal processing techniques for interference mitigatio ..."
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Cited by 13 (7 self)
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In radio telescope arrays, the complex receiver gains and sensor noise powers are initially unknown and have to be calibrated. Gain calibration can enhance the quality of astronomical sky images and, moreover, improve the effectiveness of array signal processing techniques for interference mitigation and spatial filtering. A challenging aspect is that the signaltonoise ratio (SNR) is usually well below 0 dB, even for the brightest sky sources. The calibration method considered here consists of observing a single point source and extracting the gain and noise parameters from the estimated covariance matrix. We present several closedform and iterative identification algorithms for this. Weighted versions of the algorithms are proven to be asymptotically efficient. The algorithms are validated by simulations and application to experimental data observed at the Westerbork Synthesis Radio Telescope (WSRT).
Multichannel detection of gaussian signals with uncalibrated receivers
 IEEE Signal Processing Letters
, 2001
"... Abstract—We consider the detection of unknown Gaussian signals received by an array of uncalibrated nonidentical sensors, which is a problem that appears in radio astronomy. The problem is formulated as a test on the covariance structure, the generalized likelihood ratio test (GLRT) for this problem ..."
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Cited by 10 (1 self)
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Abstract—We consider the detection of unknown Gaussian signals received by an array of uncalibrated nonidentical sensors, which is a problem that appears in radio astronomy. The problem is formulated as a test on the covariance structure, the generalized likelihood ratio test (GLRT) for this problem is stated and related to a simpler adhoc detector. We compare the method to the conventional multichannel subspace detector and show its robustness to nonidentical channels on data collected with the Westerbork radio telescope. I.
Model selection in electromagnetic source analysis with an application to VEF’s
 IEEE Transactions on Biomedical Engineering
, 2002
"... Abstract — In electromagnetic source analysis it is necessary to determine how many sources are required to describe the EEG or MEG adequately. Model selection procedures (MSP’s, or goodness of fit procedures) give an estimate of the required number of sources. Existing and new MSP’s are evaluated i ..."
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Cited by 7 (4 self)
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Abstract — In electromagnetic source analysis it is necessary to determine how many sources are required to describe the EEG or MEG adequately. Model selection procedures (MSP’s, or goodness of fit procedures) give an estimate of the required number of sources. Existing and new MSP’s are evaluated in different source and noise settings: two sources which are close or distant, and noise which is uncorrelated or correlated. The commonly used MSP residual variance is seen to be ineffective, that is it often selects too many sources. Alternatives like the adjusted Hotelling’s test, Bayes information criterion, and the Wald test on source amplitudes are seen to be effective. The adjusted Hotelling’s test is recommended if a conservative approach is taken, and MSP’s such as Bayes information criterion or the Wald test on source amplitudes are recommended if a more liberal approach is desirable. The MSP’s are applied to empirical data (visual evoked fields). I.
Multiantenna GLR detection of rankone signals with known power spectrum in white noise with unknown spatial correlation
 IEEE Trans. Signal Process
, 2012
"... Abstract—Multipleantenna detection of a Gaussian signal with spatial rank one in temporally white Gaussian noise with arbitrary and unknown spatial covariance is considered. This is motivated by spectrum sensing problems in the context of dynamic spectrum access in which several secondary networks ..."
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Cited by 6 (1 self)
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Abstract—Multipleantenna detection of a Gaussian signal with spatial rank one in temporally white Gaussian noise with arbitrary and unknown spatial covariance is considered. This is motivated by spectrum sensing problems in the context of dynamic spectrum access in which several secondary networks coexist but do not cooperate, creating a background of spatially correlated broadband interference. When the temporal correlation of the signal of interest is assumed known up to a scale factor, the corresponding Generalized Likelihood Ratio Test is shown to yield a scalar optimization problem. Closedform expressions of the test are obtained for the general signal spectrum case in the low signaltonoise ratio (SNR) regime, as well as for signals with binaryvalued power spectrum in arbitrary SNR. The two resulting detectors turn out to be equivalent. An asymptotic approximation to the test distribution for the lowSNR regime is derived, closely matching empirical results from spectrum sensing simulation experiments. Index Terms—Capon beamformer, cognitive radio, correlated noise, detection, GLR test, multiantenna array, noise uncertainty, spectral flatness measure, spectrum sensing. I.
Hierarchical SpaceTime Block Code Recognition Using Correlation Matrices
 IEEE Transactions on Wireless Communications
, 2008
"... Abstract—The blind recognition of communication parameters is a key research issue for commercial and military communication systems. The results of numerous investigations about symbol timing estimation, modulation recognition as well as identification of the number of transmitters have been report ..."
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Cited by 3 (1 self)
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Abstract—The blind recognition of communication parameters is a key research issue for commercial and military communication systems. The results of numerous investigations about symbol timing estimation, modulation recognition as well as identification of the number of transmitters have been reported in the literature. But, to our knowledge, none of them have dealt with the recognition of the SpaceTime Block Codes (STBC) used in multiple transmitter communications. In order to blindly recognize the STBC of a wireless communication, this paper proposes a method based on the spacetime correlations of the received signals. Under perfect timing synchronization and under ideal conditions (full rank channel and a number of receivers greater or equal to the number of transmitters), it shows that the Frobenius norms of these statistics present nonnull values whose positions only depend on the STBC at the transmitter side. A classifier for the spacetime code recognition of 5 linear STBC (Spatial Multiplexing, Alamouti Coding, and 3 Orthogonal STBC using 3 antennas) is presented. Simulations show that the proposed method performs well even at low signaltonoise ratios. Index Terms—MIMO, spacetime coding, electronic warfare. I.
The Extended Invariance Principle for Signal Parameter Estimation in an Unknown Spatial Field
 IEEE Transactions on Signal Processing
, 2011
"... Abstract—This paper treats the problem of joint estimation of timedelay, Doppler frequency, and spatial (directionofarrival or DOA) parameters of several replicas of a known signal in an unknown spatially correlated noise field. Both spatially unstructured and structured data models have been pr ..."
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Cited by 2 (2 self)
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Abstract—This paper treats the problem of joint estimation of timedelay, Doppler frequency, and spatial (directionofarrival or DOA) parameters of several replicas of a known signal in an unknown spatially correlated noise field. Both spatially unstructured and structured data models have been proposed for this problem and corresponding maximum likelihood (ML) estimators have been derived. However, structured models require a high computational complexity and are sensitive to the antenna array response, while unstructured models are unable to achieve good performance in some scenarios. In this paper, it is shown how the extended invariance principle (EXIP) can be applied to obtain estimates with the quality of a spatially structured model, but with much lower complexity than directly utilizing a structured model and with greater robustness to errors in the model of the array response. EXIP improves the quality of the timedelay and Doppler frequency estimates obtained with a spatially unstructured model by introducing DOA estimates which are obtained in a second step through an innovative reparametrization. Simulation results for timedelay and Doppler frequency estimation for Global Positioning System (GPS) signals are presented and confirm that the proposed twostep approach attains the CramerRao lower bound (CRLB) of the spatially structured model. Index Terms—Antenna arrays, CramerRao lower bound (CRLB), direction of arrival (DOA), Doppler frequency, extended invariance principle, highresolution array signal processing, maximum likelihood estimation, multipath channel, propagation timedelay. I.
On the Distribution of Roy’s Largest Root Test in MANOVA and in Signal Detection in Noise ∗
, 2011
"... Roy’s largest root is a common test in multivariate analysis of variance (MANOVA), with applications in several other problems, such as signal detection in noise. In this paper, assuming multivariate Gaussian observations, we derive a simple yet accurate approximation for the distribution of Roy’s l ..."
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Cited by 2 (1 self)
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Roy’s largest root is a common test in multivariate analysis of variance (MANOVA), with applications in several other problems, such as signal detection in noise. In this paper, assuming multivariate Gaussian observations, we derive a simple yet accurate approximation for the distribution of Roy’s largest root test, in the extreme case of concentrated noncentrality, where the signal or difference between groups is concentrated in a single direction. Our main result is that in the MANOVA setting, up to centering and scaling, Roy’s largest root test approximately follows a noncentral F distribution whereas in the signal detection application, it approximately follows a modified central F distribution (of the form (s+χ 2 a)/χ 2 b). Our results allow power calculations for Roy’s test, as well as estimates of sample size required to detect a given (rankone) group difference by this test, both of which are important quantities in hypothesisdriven research. 1
Model Selection Procedures in Electromagnetic Source Analysis
"... This paper examines with a simulation study to what extent the results of criteria on linear models are robust to nonlinear functions ..."
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This paper examines with a simulation study to what extent the results of criteria on linear models are robust to nonlinear functions