STUDY OF SOME ADAPTIVE EIGENSPACE ALGORITHMS IN SENSOR ARRAYS

概要

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High-resolution algorithms for the dedection and estimation of Directions Of Arrival (DOA) such as MUSIC, lead to accurate results but require the computation of the noise-subspace through an expensive covariance matrix eigendecomposition. Adaptive estimators of the noise-subspace can be very useful in a non-stationary environment when the convergence is possible with a few number of snapshots. If this number is too large, a direct eigendecomposition would be preferable. Some adaptive methods are presented showing that an indirect noise-subspace estimation through a signal subspace estimation can be sometimes advantageous both in terms of convergence rate and computation complexity. Computer simulations showing performances in tems of complexity costs of different methods are provided.
社団法人電子情報通信学会の論文
1996-03-11