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FourthOrder Cumulant Structure Forcing. Application to Blind Array Processing
, 1992
"... In blind array processing, the array manifold is unknown but, under the signal independence assumption, the signal parameters can be estimated by resorting to higherorder information. We consider the 4thorder cumulant tensor and show that sample cumulant enhancement based on rank and symmetry prop ..."
Abstract

Cited by 11 (8 self)
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In blind array processing, the array manifold is unknown but, under the signal independence assumption, the signal parameters can be estimated by resorting to higherorder information. We consider the 4thorder cumulant tensor and show that sample cumulant enhancement based on rank and symmetry properties yields cumulant estimates with the exact theoretical structure. Any identification procedure based on enhanced cumulants is then equivalent to cumulant matching, bypassing the need for initialization and optimization. 1. INTRODUCTION This paper deals with a linear data model where a m dimensional complex vector x(t) is assumed to be the superposition of n linear components, possibly corrupted by additive noise. An observation can then be written as: x(t) = X p=1;n sp(t) ap +N(t) (1) where each sp(t) is a complex stationary scalar process, each ap is a deterministic m21 vector, and the m21 vector N(t) represents additive noise. This is the standard model in narrow band array p...