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Spatial and Temporal Frequency Estimation of Uncorrelated Signals Using Subspace Fitting
KTH, Superseded Departments, Signals, Sensors and Systems.
KTH, Superseded Departments, Signals, Sensors and Systems.ORCID iD: 0000-0002-6855-5868
KTH, Superseded Departments, Signals, Sensors and Systems.ORCID iD: 0000-0003-2298-6774
1996 (English)In: IEEE Signal Processing Workshop on Statistical Signal and Array Processing, 1996, 94-96 p.Conference paper, Published paper (Refereed)
Abstract [en]

We present a novel method for spatial and temporal frequency estimation in the case of uncorrelated sources. By imposing the diagonal structure given in the signal covariance matrix, it is possible to improve the performance of subspace based estimators. The proposed method combines ideas from subspace and covariance matching methods to yield a non-iterative frequency estimation algorithm. In a numerical example we show that the estimator has a lower small sample resolution threshold than root-MUSIC and similar large sample performance.

Place, publisher, year, edition, pages
1996. 94-96 p.
Keyword [en]
Additive white noise, Algorithm design and analysis, Array signal processing, Covariance matrix, Direction of arrival estimation, Frequency estimation, Multiple signal classification, Sensor arrays, Sensor systems, Signal processing
National Category
Signal Processing
Identifiers
URN: urn:nbn:se:kth:diva-86525DOI: 0.1109/SSAP.1996.534828OAI: oai:DiVA.org:kth-86525DiVA: diva2:500798
Conference
8th IEEE Signal Processing Workshop on Statistical Signal and Array Processing, Corfu, Greece, Jun. 1996
Note
NR 20140805Available from: 2012-02-13 Created: 2012-02-13 Last updated: 2012-02-13Bibliographically approved

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Jansson, MagnusOttersten, Björn

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