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Keywords
(10)
Ambient Noise
Colored Noise
Computer Simulation
Covariance Matrix
Cramer Rao Bound
Direction of Arrival
Efficient Estimation
Hermitian Matrices
Maximum Likelihood Estimate
Direction Finding
Related Publications
(5)
Direction estimation in partially unknown noise fields
Maximumlikeliho...
Covariance Matching Estimation Techniques for Array Signal Processing Applications
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Direction finding using noise covariance modeling
Direction finding using noise covariance modeling,10.1109/78.398717,IEEE Transactions on Signal Processing,Benjamin Friedlander,Anthony J. Weiss
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Direction finding using noise covariance modeling
(
Citations: 41
)
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Benjamin Friedlander
,
Anthony J. Weiss
We consider the problem of
direction finding
in the presence of
colored noise
whose
covariance matrix
is unknown. We show that the
ambient noise
covariance matrix
can be modeled by a sum of
Hermitian matrices
known up to a multiplicative scalar. Using this model, we estimate jointly the directions of arrival of the signals and the noise model parameters. We show that under certain conditions, it is possible to obtain unbiased and efficient estimates of the signal direction. The CramerRao bound is used as the principal analysis tool. Computer simulations using the
maximum likelihood
estimator provide a validation of the analytical results
Journal:
IEEE Transactions on Signal Processing  TSP
, vol. 43, no. 7, pp. 15571567, 1995
DOI:
10.1109/78.398717
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Citation Context
(24)
...<{[SECTION]}>[
6
] H. Aghvami, N. Sattari, O. Holland, and P. Pangalos, “Group handover...
Lu Lu
,
et al.
Robust Expectation–Maximization DirectionofArrival Estimation Algori...
...The covariance matching approach is well suited for problems where the parameter set can be separated into linear and nonlinear parameters: The array covariance matrix depends linearly on the linear parameters and nonlinearly on the nonlinear parameters, for example, in situations with linearly parameterized noise fields [
21
], distributed source signals [22], uncorrelated source signals [23], and ocean surface velocity estimation [24]...
Sen Zhang
,
et al.
Image Autocoregistration and Interferogram Estimation Using Extended C...
...For spatially correlated noise, We refer to Wong et al. (1992), LeCadre (1989), Ye and DeGroat (1995),
Friedlander and Weiss (1995)
, Göansson and Ottersten (1999), Viberg et al. (1995, 1997), Stoica et al. (1996), Agrawal and Prasad (2000), Pesavento and Gershman (2001), Wu and Wong (1994), Belouchrani et al. (1997), Vorobyov et al. (2005) for references...
Chen Gu
,
et al.
Efficient 2D DOA estimation of coherent signals in spatially correlate...
...ML estimators for the source and instrument parameters under a generalized noise covariance parameterization is provided in [9,
10
], whereas nonlinear least squares estimators were studied in [10–12]...
...It is known that with W = R 1/2 this estimator is asymptotically unbiased and asymptotically efficient [
10
,12]...
...Indeed, the simulations in [
10
] show only a small improvement of the ML solution as compared to the WLS solution...
Stefan J. Wijnholds
,
et al.
SelfCalibration of Radio Astronomical Arrays With NonDiagonal Noise ...
...This strategy is widely used, e.g., in [11], [
15
]—[16], and [23]—[24]...
...The spatial pseudospectrum of the noise is shown in Fig. 2. The same noise modeling and parameters are used in [
15
]...
Minghui Li
,
et al.
Maximum likelihood DOA estimation in unknown colored noise fields
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(
Citations: 191
)
William S Burdic
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Multiple emitter location and signal parameter estimation
(
Citations: 2702
)
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Journal:
IEEE Transactions on Antennas and Propagation  IEEE TRANS ANTENNAS PROPAGAT
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Eigenstructure methods for direction of arrival estimation in the presence of unknown noise fields
(
Citations: 72
)
AROGYASWAMI PAULRAJ
,
THOMAS KAILATH
Journal:
IEEE Transactions on Acoustics, Speech, and Signal Processing
, vol. 34, no. 1, pp. 1320, 1986
On least squares methods for direction of arrival estimation in the presence of unknown noise fields
(
Citations: 27
)
J. F. Bohme
,
D. Kraus
Conference:
International Conference on Acoustics, Speech, and Signal Processing  ICASSP
, pp. 28332836 vol.5, 1988
Maximum likelihood direction finding of stochastic sources: a separable solution
(
Citations: 54
)
A. G. Jaffer
Conference:
International Conference on Acoustics, Speech, and Signal Processing  ICASSP
, pp. 28932896 vol.5, 1988
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Citations
(41)
Robust Expectation–Maximization DirectionofArrival Estimation Algorithm for Wideband Source Signals
Lu Lu
,
HsiaoChun Wu
Journal:
IEEE Transactions on Vehicular Technology  IEEE TRANS VEH TECHNOL
, vol. 60, no. 5, pp. 23952400, 2011
Localization of NarrowBand Sources in Unknown Spatially Correlated Noise
(
Citations: 1
)
Salah Bourennane
,
Caroline Fossati
,
Julien Marot
Journal:
Eurasip Journal on Advances in Signal Processing  EURASIP J ADV SIGNAL PROCESS
, vol. 2010, pp. 112, 2010
Image Autocoregistration and Interferogram Estimation Using Extended COMETEXIP Method
Sen Zhang
,
Jinsong Tang
,
Ming Chen
,
Sanwen Zhu
,
Hailiang Yang
Journal:
IEEE Transactions on Geoscience and Remote Sensing  IEEE TRANS GEOSCI REMOT SEN
, vol. 48, no. 12, pp. 42044218, 2010
Efficient 2D DOA estimation of coherent signals in spatially correlated noise using electromagnetic vector sensors
Chen Gu
,
Jin He
,
Xiaohua Zhu
,
Zhong Liu
Journal:
Multidimensional Systems and Signal Processing  MULTIDIMENSION SYST SIGN PROC
, vol. 21, no. 3, pp. 239254, 2010
SelfCalibration of Radio Astronomical Arrays With NonDiagonal Noise Covariance Matrix
Stefan J. Wijnholds
,
AlleJan van der Veen
Published in 2010.