Analysis of Algorithms for Sensor Arrays with Invariance Structure
1990 (English)Report (Other academic)
The problem of estimating signal parameters from sensor array data is addressed. If the array is composed of two identical subarrays, (i.e. one invariance) the ESPRIT algorithm is known to yield parameter estimates in a very cost efficient manner. Recently, the total least squares (TLS) version of ESPRIT has been formulated in a subspace fitting framework. In this formulation, the ESPRIT concept is easily generalized to arrays exhibiting more than one invariance. The asymptotic properties for this class of algorithms are derived. The estimates are shown to be statistically efficient under certain assumptions. The case of a uniform linear array is studied in more detail, and a generalization of the ESPRIT algorithm is proposed by introducing row weighting of the subspace estimate.
Place, publisher, year, edition, pages
Linköping: Linköping University , 1990. , 5 p.
LiTH-ISY-I, ISSN 8765-4321 ; 1053
Parameter estimation, Signal processing, Sensor arrays, Invariance structure
IdentifiersURN: urn:nbn:se:liu:diva-104030OAI: oai:DiVA.org:liu-104030DiVA: diva2:694414