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Asymptotic Results for Multidimensional Sensor Array Processing
Stanford University, CA, USA.
Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan. Stanford University, CA, USA.
1988 (engelsk)Inngår i: Proceedings of the 22nd Asilomar Conference on Signals, Systems and Computers, 1988, s. 833-837Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

The problem of estimating signal parameters from the output of a sensor array is adressed. The Maximum Likelihood estimation procedure is a systematic approach to many parameter estimation problems. The deterministic ML method has been formulated and several methods for maximizing the cos function have been proposed. However, the asymptotic distribution of the estimation error has not ben reported for the general case. The distribution will be derived in this paper. Multidimensional signal subspace methods have been proposed recently with advantages over conventional one-dimensional subspace methods. We examine the asymptotic properties of a weighted subspace fitting problem. A weighting matrix is proposed which gives the subspace fitting method the same asymptotic distribution as the ML method.

sted, utgiver, år, opplag, sider
1988. s. 833-837
Emneord [en]
Multidimensional sensor array processing, Asymptotic distribution, Maximum Likelihood estimation
HSV kategori
Identifikatorer
URN: urn:nbn:se:liu:diva-100581DOI: 10.1109/ACSSC.1988.754666OAI: oai:DiVA.org:liu-100581DiVA, id: diva2:663117
Konferanse
22nd Asilomar Conference on Signals, Systems and Computers, November, 1988, Monterey, USA
Tilgjengelig fra: 2013-11-09 Laget: 2013-11-09 Sist oppdatert: 2014-02-08

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